[ { "id": "Musleh_PhD", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/224040", "title": "Guided Visual Analytics for Decision Making under Uncertainty", "date": "2026-03", "abstract": "Visual Analytics (VA) has emerged from the need to optimize decision making by involving human reasoning in sense making. The development of VA has been facilitated by significant technological advances in modern computer graphics and data processing capabilities. Involving humans in the loop aims to address high-risk scenarios where artificial intelligence (AI) automated approaches are insufficient. One active area of research with VA is the development of methods that enable the user to make efficient and effective decisions under high uncertainty. Yet, the field of VA research has not fully understood how user attitude, namely trust and confidence, interplay in VA decision making under uncertainty. Properties of the user attitude play a crucial role in optimizing VA decision making, but they are challenging to externalize and evaluate. For instance, user confidence in their decision emerges as an important indicator of effectiveness when the correctness of the decision cannot be measured. In this dissertation, we explore the use of guidance techniques to address uncertainties in VA decision making, focusing on scenarios where the correctness of decisions cannot be definitively established. Throughout this work, we learned that a multidimensional guidance mechanism can address uncertainties more effectively when uncertainties are challenging to quantify and visualize, especially in the case of subjective uncertainty. However, evaluating the effectiveness of guidance approaches requires a more comprehensive analysis of the interplay between trust and confidence within the sense-making process. Using provenance networks and SNA metrics can provide a more reliable and comprehensive assessment of user confidence, indicating that such approaches can be employed to support co-adaptive guidance.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "title,abstract,date,keywords", "repositum_presentation_id": null, "authors": [ 1867 ], "ac_number": "AC17745765", "date_end": "2025", "date_start": "2021", "doi": "10.34726/hss.2026.137814", "open_access": "yes", "pages": "185", "reviewer_1": [ 5252 ], "reviewer_2": [ 5243 ], "rigorosum": "2025-11", "supervisor": [ 1410 ], "research_areas": [ "InfoVis", "MedVis" ], "keywords": [ "Visualization", "Visual Analytics", "Guidance", "Trust", "Confidence" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Musleh_PhD-thesis.pdf", "type": "application/pdf", "size": 6169556, "path": "Publication:Musleh_PhD", "url": "https://www.cg.tuwien.ac.at/research/publications/2026/Musleh_PhD/Musleh_PhD-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2026/Musleh_PhD/Musleh_PhD-thesis:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2026/Musleh_PhD/", "__class": "Publication" }, { "id": "tekaya-2025-amo", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/221607", "title": "A Matter of Time: Revealing the Structure of Time in Vision-Language Models", "date": "2025-10-27", "abstract": "Large-scale vision-language models (VLMs) such as CLIP have gained popularity for their generalizable and expressive multimodal representations. By leveraging large-scale training data with diverse textual metadata, VLMs acquire open-vocabulary capabilities, solving tasks beyond their training scope. This paper investigates the temporal awareness of VLMs, assessing their ability to position visual content in time. We introduce TIME10k, a benchmark dataset of over 10,000 images with temporal ground truth, and evaluate the time-awareness of 37 VLMs by a novel methodology. Our investigation reveals that temporal information is structured along a low-dimensional, non-linear manifold in the VLM embedding space. Based on this insight, we propose methods to derive an explicit ''timeline'' representation from the embedding space. These representations model time and its chronological progression and thereby facilitate temporal reasoning tasks. Our timeline approaches achieve competitive to superior accuracy compared to a prompt-based baseline while being computationally efficient. All code and data are available at https://tekayanidham.github.io/timeline-page/.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1536, "image_height": 458, "name": "tekaya-2025-amo-teaser.png", "type": "image/png", "size": 4646052, "path": "Publication:tekaya-2025-amo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/tekaya-2025-amo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/tekaya-2025-amo-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,keywords,projects", "repositum_presentation_id": null, "authors": [ 5330, 1110, 5370 ], "booktitle": "MM '25: Proceedings of the 33rd ACM International Conference on Multimedia", "date_from": "2025-10-27", "date_to": "2025-10-31", "doi": "10.1145/3746027.3758163", "event": "ACM International Conference on Multimedia 2025", "isbn": "979-8-4007-2035-2", "lecturer": [ 5330 ], "location": "Dublin", "open_access": "yes", "pages": "10", "pages_from": "12371", "pages_to": "12380", "research_areas": [ "InfoVis" ], "keywords": [ "Multimodal representations", "Vision-language models", "Time modeling", "Time estimation", "Benchmark dataset" ], "weblinks": [ { "href": "https://tekayanidham.github.io/timeline-page/", "caption": null, "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1536, "image_height": 458, "name": "tekaya-2025-amo-teaser.png", "type": "image/png", "size": 4646052, "path": "Publication:tekaya-2025-amo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/tekaya-2025-amo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/tekaya-2025-amo-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9522", "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/", "__class": "Publication" }, { "id": "komon-2025-webigeo", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/221523", "title": "weBIGeo: Interaktive Lawinensimulation im Web", "date": "2025-10", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2556, "image_height": 1303, "name": "komon-2025-webigeo-teaser.png", "type": "image/png", "size": 5204641, "path": "Publication:komon-2025-webigeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,projects", "repositum_presentation_id": null, "authors": [ 1859, 1869, 5510, 5511, 5512, 5513, 1013, 1110 ], "ac_number": "AC17717665", "booktitle": "Tagungsband des 6. internationalen Lawinensymposiums", "date_from": "2025-10-18", "date_to": "2025-10-18", "doi": "10.34726/11439", "event": "6. Lawinen Symposium Graz 2025", "lecturer": [ 1859, 1110 ], "location": "Graz", "open_access": "yes", "pages": "4", "pages_from": "150", "pages_to": "153", "research_areas": [ "InfoVis", "Modeling" ], "keywords": [ "Visualisierung", "Lawinen", "3D Karten" ], "weblinks": [ { "href": "https://webigeo.alpinemaps.org/", "caption": "demo", "description": "weBIGeo demo: requires WebGPU-ready browser! ", "main_file": 1 }, { "href": "https://lawinensymposium.naturfreunde.at/", "caption": "Lawinensymposium", "description": "Lawinensymposium", "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "komon-2025-webigeo-paper.pdf", "type": "application/pdf", "size": 1611394, "path": "Publication:komon-2025-webigeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2556, "image_height": 1303, "name": "komon-2025-webigeo-teaser.png", "type": "image/png", "size": 5204641, "path": "Publication:komon-2025-webigeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9555", "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/", "__class": "Publication" }, { "id": "huber-2025-eed", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/220017", "title": "Enhancing Environmental Data Communication Through VR", "date": "2025-09-12", "abstract": "This paper examines how environmental data can be effectively communicated to non-experts in interactive, immersive 3D spaces. Utilizing a use case centered on global spatio-temporal CO2 emissions and population dynamics over the past six decades, we explore techniques for presenting both absolute (country-level) and per capita data within meaningful spatial and temporal contexts. We developed a VR prototype visualizing these data on an interactive 3D globe and conducted a qualitative user study to evaluate its clarity and interpretability for non-expert audiences. Our findings suggest that incorporating clear geographical context, intuitive representations, and user-centered interactions can enhance engagement and certain aspects of understanding. We thereby offer a practical contribution to tackling environmental data visualization and communication in immersive environments. This promotes transparency and mitigates the risk of misinterpretation or misinformation in data communication across emerging digital media platforms.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 3835, "image_height": 1551, "name": "huber-2025-eed-teaser.PNG", "type": "image/png", "size": 4027742, "path": "Publication:huber-2025-eed", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,pages_from,pages_to", "repositum_presentation_id": null, "authors": [ 5456, 1653, 1030, 5485 ], "ac_number": "AC17672916", "booktitle": "Computer Graphics & Visual Computing (CGVC) 2025 : Eurographics UK Chapter Proceedings : Liverpool John Moores University, UK : 11 - 12 September 2025", "date_from": "2025-09-11", "date_to": "2025-09-12", "doi": "10.2312/cgvc.20251220", "event": "Computer Graphics & Visual Computing 2025 (CGVC 2025)", "isbn": "978-3-03868-293-6", "lecturer": [ 5456 ], "location": "Liverpool John Moores University", "open_access": "yes", "pages": "5", "pages_from": "1", "pages_to": "5", "publisher": "The Eurographics Association", "research_areas": [ "InfoVis", "VR" ], "keywords": [ "Human-centered computing", "User studies", "Virtual reality", "Information visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "huber-2025-eed-paper.pdf", "type": "application/pdf", "size": 4585623, "path": "Publication:huber-2025-eed", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 3835, "image_height": 1551, "name": "huber-2025-eed-teaser.PNG", "type": "image/png", "size": 4027742, "path": "Publication:huber-2025-eed", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d10164" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/", "__class": "Publication" }, { "id": "ellhotka-2025-ipo", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Improving the Performance of Edge-Path Bundling With WebGPU", "date": "2025-09", "abstract": "Visualizing large graphs is often challenging due to visual clutter, which obscures important patterns. While Spanner-based Edge-Path Bundling (S-EPB) is an effective technique\nfor mitigating this issue, its CPU-based implementation is too slow for interactive use, particularly in web environments. This thesis presents a Parallel Edge-Path Bundling (P-EPB) algorithm that addresses this performance limitation by utilizing the massively parallel processing capabilities of modern Graphics Processing Unit (GPU)s through the WebGPU API.\n\nThe proposed algorithm reengineers the S-EPB technique for parallel execution, with a focus on finding and then optimizing the most computationally demanding tasks: spanner construction and shortest-path calculations. A parallelized Floyd–Warshall algorithm, together with different spanner construction methods (greedy and theta-graph), is employed in implementing the P-EPB algorithm as an interactive web application. \n\nA detailed evaluation compares the WebGPU-based P-EPB algorithm to the CPU-based S-EPB implementation. Results show that the P-EPB approach, particularly when using a theta-spanner, delivers substantial speedups on dense graphs. This work highlights the potential of WebGPU to enable high-performance, interactive graph visualization and analysis in web-based environments.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "name": "ellhotka-2025-ipo-teaser.png", "type": "image/png", "size": 615750, "path": "Publication:ellhotka-2025-ipo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5498 ], "date_end": "2025-09", "date_start": "2025-03", "matrikelnr": "11776184", "supervisor": [ 166, 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://github.com/YannicEl/edge_bundling_webgpu", "caption": "GitHub", "description": null, "main_file": 1 }, { "href": "https://bachelor.yannic.at/app?graph=airlines&spannerAlgorithm=theta&renderingMode=quality", "caption": "demo", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "name": "ellhotka-2025-ipo-teaser.png", "type": "image/png", "size": 615750, "path": "Publication:ellhotka-2025-ipo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "ellhotka-2025-ipo-thesis.pdf", "type": "application/pdf", "size": 8099963, "path": "Publication:ellhotka-2025-ipo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/", "__class": "Publication" }, { "id": "Braunsperger-2025_bsc", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Data-Centric Methods for Efficient Deep Assembly Verification: A Case Study in Electronic Lock Manufacturing", "date": "2025-06", "abstract": "This thesis investigates data-efficient deep learning methods for visual assembly ver-\nification in a highly customizable electronic lock production line. We examine three\ndata-centric strategies. First, ROI-based methods leverage the fixed geometry of the\nworkpiece carriers by reformulating object detection as a set of classification or regression\ntasks over predefined regions. Second, pseudo bounding boxes are created by combining\nimage-level labels with known part positions to automatically generate object detection\nannotations without manual labelling. Third, synthetic training data is produced by\ncompositing cropped part images with background scenes, thereby increasing dataset\ndiversity and reducing the need for extensive manual data collection.\nThese methods are evaluated on a real-world dataset collected during regular production\nto assess their effectiveness in reducing manual annotation effort. We provide a compre-\nhensive comparison of data-centric approaches, highlighting their respective strengths\nand limitations. The results demonstrate that leveraging the structured nature of the\nassembly environment enables accurate model performance with substantially reduced\nannotation requirements.", "authors_et_al": false, "substitute": null, "main_image": { "description": "An example from the dataset presented in the thesis showing a Double-sided hybrid Euro cylinder with electronic thumbturn and keyway", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1012, "image_height": 888, "name": "Braunsperger-2025_bsc-teaser.png", "type": "image/png", "size": 1577249, "path": "Publication:Braunsperger-2025_bsc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5475 ], "date_end": "2025-06", "date_start": "2024-09", "matrikelnr": "11909911", "supervisor": [ 1813, 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": "An example from the dataset presented in the thesis showing a Double-sided hybrid Euro cylinder with electronic thumbturn and keyway", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1012, "image_height": 888, "name": "Braunsperger-2025_bsc-teaser.png", "type": "image/png", "size": 1577249, "path": "Publication:Braunsperger-2025_bsc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Braunsperger-2025_bsc-thesis.pdf", "type": "application/pdf", "size": 69351689, "path": "Publication:Braunsperger-2025_bsc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/", "__class": "Publication" }, { "id": "eschner-2025-ide", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/216865", "title": "Interactive Discovery and Exploration of Visual Bias in Generative Text‐to‐Image Models", "date": "2025-06", "abstract": "Bias in generative Text-to-Image (T2I) models is a known issue, yet systematically analyzing such models' outputs to uncover it remains challenging. We introduce the Visual Bias Explorer (ViBEx) to interactively explore the output space of T2I models to support the discovery of visual bias. ViBEx introduces a novel flexible prompting tree interface in combination with zero-shot bias probing using CLIP for quick and approximate bias exploration. It additionally supports in-depth confirmatory bias analysis through visual inspection of forward, intersectional, and inverse bias queries. ViBEx is model-agnostic and publicly available. In four case study interviews, experts in AI and ethics were able to discover visual biases that have so far not been described in literature.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2578, "image_height": 1292, "name": "eschner-2025-ide-image.png", "type": "image/png", "size": 1659146, "path": "Publication:eschner-2025-ide", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-image:thumb{{size}}.png" }, "sync_repositum_override": "title,date,projects,event,lecturer,location,number,volume", "repositum_presentation_id": null, "authors": [ 1653, 5490, 5370, 1110 ], "ac_number": "AC17579673", "articleno": "e70135", "doi": "10.1111/cgf.70135", "event": "EuroVis 2025", "issn": "1467-8659", "journal": "Computer Graphics Forum", "lecturer": [ 1653 ], "location": "Luxembourg", "number": "3", "open_access": "yes", "pages": "20", "publisher": "WILEY", "volume": "44", "research_areas": [ "InfoVis" ], "keywords": [ "Visualization", "Bias", "Artificial Intelligence" ], "weblinks": [ { "href": "https://vibex.jde.cg.tuwien.ac.at", "caption": "live demo", "description": "Live demo of the ViBEx application", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2578, "image_height": 1292, "name": "eschner-2025-ide-image.png", "type": "image/png", "size": 1659146, "path": "Publication:eschner-2025-ide", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "eschner-2025-ide-paper.pdf", "type": "application/pdf", "size": 46238959, "path": "Publication:eschner-2025-ide", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/", "__class": "Publication" }, { "id": "matt-2025-scv", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/216286", "title": "Scalable Class-Centric Visual Interactive Labeling", "date": "2025-06", "abstract": "Large unlabeled datasets demand efficient and scalable data labeling solutions, in particular when the number of instances and classes is large. This leads to significant visual scalability challenges and imposes a high cognitive load on the users. Traditional instance-centric labeling methods, where (single) instances are labeled in each iteration struggle to scale effectively in these scenarios. To address these challenges, we introduce cVIL, a Class-Centric Visual Interactive Labeling methodology designed for interactive visual data labeling. By shifting the paradigm from assigning-classes-to-instances to assigning-instances-to-classes, cVIL reduces labeling effort and enhances efficiency for annotators working with large, complex and class-rich datasets. We propose a novel visual analytics labeling interface built on top of the conceptual cVIL workflow, enabling improved scalability over traditional visual labeling. In a user study, we demonstrate that cVIL can improve labeling efficiency and user satisfaction over instance-centric interfaces. The effectiveness of cVIL is further demonstrated through a usage scenario, showcasing its potential to alleviate cognitive load and support experts in managing extensive labeling tasks efficiently.", "authors_et_al": false, "substitute": null, "main_image": { "description": "class-centric visual interactive labeling workflow", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1667, "image_height": 624, "name": "matt-2025-scv-teaser.png", "type": "image/png", "size": 254694, "path": "Publication:matt-2025-scv", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/matt-2025-scv-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/matt-2025-scv-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5263, 5487, 1851, 5370, 1110 ], "articleno": "104240", "doi": "10.1016/j.cag.2025.104240", "issn": "1873-7684", "journal": "COMPUTERS & GRAPHICS-UK", "pages": "14", "publisher": "PERGAMON-ELSEVIER SCIENCE LTD", "volume": "129", "research_areas": [ "InfoVis" ], "keywords": [ "Class-centric labeling", "Interactive machine learning", "Property measures", "Visual analytics", "Visual-interactive data labeling" ], "weblinks": [], "files": [ { "description": "class-centric visual interactive labeling workflow", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1667, "image_height": 624, "name": "matt-2025-scv-teaser.png", "type": "image/png", "size": 254694, "path": "Publication:matt-2025-scv", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/matt-2025-scv-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/matt-2025-scv-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/", "__class": "Publication" }, { "id": "steinschorn-2025-parameter", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/216467", "title": "Parameter Optimization for Surface Reconstruction", "date": "2025-06", "abstract": "In this thesis, we compare different parameter-optimization algorithms on the example of Screened Poisson Surface Reconstruction. To do this, we first implemented five state-of-the-art algorithms. GEIST is a graph-based algorithm that splits the parameter space into an `optimal' and a `non-optimal' set to select new configurations. Iterated F-Race places a normal distribution of selection probabilities on the best configurations of the last iteration and uses that to choose the next configurations. ParamILS uses iterative local search to select a better neighbor and find an optimum this way. PostSelection uses a shortened version of an algorithm to find promising candidates and a second, more detailed one to evaluate these. As a simple baseline we also implemented Brute-Force.\n\nFor all of these algorithms, we first conduct several tests to find a good configuration to run them with. After that, we test them on point clouds from two datasets. Each dataset contains each cloud in different qualities, so we are able to test varying input qualities as well as types. We show that each of the implemented algorithms is able to find better parameter configurations than the default Screened Poisson Surface Reconstruction configuration. In most cases, GEIST and PostSelection lead to the best results but also have the longest run times, while ParamILS and Iterated F-Race lead to good results in a far shorter time period. Brute-Force is not competitive when it comes to high-quality configurations, but still leads to an improvement over the default in most cases.\n\nTo summarize the results over different types and qualities, the default configuration yields acceptable but not ideal results for point clouds of smooth meshes with little noise and we suggest an alternative. If the surface is rougher, the importance weight of the points should ideally be set higher. If there is a lot of noise, this weight as well as the Octree depth should be reduced.\n\nWe discuss the advantages and disadvantages of each implemented algorithm and compare their results to recommend which one to use. We describe our implementations of each and quickly mention what work could be done to expand on this thesis. Finally, we give recommendations as to which configurations to use for different types of point clouds. For data with higher accuracy, depth and pointWeight should be higher than for data with lower accuracy. If the topology of the object is very complex, pointWeight is best set very high in comparison to simpler point clouds. We find that for most cases, IF-Race is the best compromise to use between speed and resulting quality of reconstruction. If time is of no concern, GEIST is an alternative that yields high-quality results.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Armadillo input point cloud, reconstruction with default parameters, reconstruction with optimized parameters", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2444, "image_height": 927, "name": "steinschorn-2025-parameter-teaser.png", "type": "image/png", "size": 935638, "path": "Publication:steinschorn-2025-parameter", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-teaser:thumb{{size}}.png" }, "sync_repositum_override": "abstract,keywords,ac_number", "repositum_presentation_id": null, "authors": [ 1757 ], "ac_number": "AC17567674", "date_end": "2025-06", "date_start": "2020-04-02", "diploma_examina": "2025-06-16", "doi": "10.34726/hss.2025.80083", "matrikelnr": "1227109", "open_access": "yes", "pages": "96", "supervisor": [ 193, 1395 ], "research_areas": [ "InfoVis", "Modeling" ], "keywords": [ "parameter optimization", "deep learning", "surface reconstruction", "Autotuning", "Point Clouds" ], "weblinks": [ { "href": "https://github.com/thefloff/ppsurf_param_opt", "caption": "Repository", "description": null, "main_file": 1 } ], "files": { "1": { "description": "Armadillo input point cloud, reconstruction with default parameters, reconstruction with optimized parameters", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2444, "image_height": 927, "name": "steinschorn-2025-parameter-teaser.png", "type": "image/png", "size": 935638, "path": "Publication:steinschorn-2025-parameter", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-teaser:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "thesis_large", "main_file": false, "use_in_gallery": false, "access": "public", "name": "steinschorn-2025-parameter-thesis_large.pdf", "type": "application/pdf", "size": 18678215, "path": "Publication:steinschorn-2025-parameter", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-thesis_large.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-thesis_large:thumb{{size}}.png" }, "3": { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "steinschorn-2025-parameter-thesis.pdf", "type": "application/pdf", "size": 2695388, "path": "Publication:steinschorn-2025-parameter", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/", "__class": "Publication" }, { "id": "musleh-2025-trustme", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/215604", "title": "TrustME: A Context-Aware Explainability Model to Promote User Trust in Guidance", "date": "2025-04-21", "abstract": "Guidance-enhanced approaches are used to support users in making sense of their data and overcoming challenging analytical scenarios. While recent literature underscores the value of guidance, a lack of clear explanations to motivate system interventions may still negatively impact guidance effectiveness. Hence, guidance-enhanced VA approaches require meticulous design, demanding contextual adjustments for developing appropriate explanations. Our paper discusses the concept of explainable guidance and how it impacts the user-system relationship-specifically, a user's trust in guidance within the VA process. We subsequently propose a model that supports the design of explainability strategies for guidance in VA. The model builds upon flourishing literature in explainable AI, available guidelines for developing effective guidance in VA systems, and accrued knowledge on user-system trust dynamics. Our model responds to challenges concerning guidance adoption and context-effectiveness by fostering trust through appropriately designed explanations. To demonstrate the model's value, we employ it in designing explanations within two existing VA scenarios. We also describe a design walk-through with a guidance expert to showcase how our model supports designers in clarifying the rationale behind system interventions and designing explainable guidance.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 703, "image_height": 706, "name": "musleh-2025-trustme-.png", "type": "image/png", "size": 75894, "path": "Publication:musleh-2025-trustme", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/musleh-2025-trustme-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/musleh-2025-trustme-:thumb{{size}}.png" }, "sync_repositum_override": "event,number,pages_from,pages_to,volume", "repositum_presentation_id": null, "authors": [ 1867, 1410, 5418 ], "doi": "10.1109/TVCG.2025.3562929", "event": "IEEE Vis 2025", "issn": "1941-0506", "journal": "IEEE Transactions on Visualization and Computer Graphics", "number": "10", "open_access": "yes", "pages": "17", "pages_from": "8040", "pages_to": "8056", "publisher": "IEEE COMPUTER SOC", "volume": "31", "research_areas": [ "InfoVis" ], "keywords": [ "Explainability", "Explainable Guidance", "User Trust", "Visual Analytics" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 703, "image_height": 706, "name": "musleh-2025-trustme-.png", "type": "image/png", "size": 75894, "path": "Publication:musleh-2025-trustme", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/musleh-2025-trustme-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/musleh-2025-trustme-:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/", "__class": "Publication" }, { "id": "komon-kimmersdorfer-2025-weBIGeo", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "weBIGeo: real-time avalanche simulation and visualization using WebGPU", "date": "2025-03", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": "Possible avalanche traces on Schneeberg", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "name": "komon-kimmersdorfer-2025-weBIGeo-teaser.png", "type": "image/png", "size": 6536942, "path": "Publication:komon-kimmersdorfer-2025-weBIGeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/komon-kimmersdorfer-2025-weBIGeo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/komon-kimmersdorfer-2025-weBIGeo-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1859, 1869 ], "date_end": "2025-03", "date_start": "2024-02", "matrikelnr": "11808210, 01326608", "supervisor": [ 1110, 1013 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://webigeo.alpinemaps.org/", "caption": "weBIGeo", "description": "weBIGeo avalanche simulation demo", "main_file": 1 }, { "href": "https://www.netidee.at/webigeo", "caption": "project page", "description": "NetIdee project page, including end report and blog posts", "main_file": 1 }, { "href": "https://github.com/weBIGeo/webigeo/tree/release/netidee6745", "caption": "GitHub", "description": "Code and documentation", "main_file": 0 } ], "files": [ { "description": "Possible avalanche traces on Schneeberg", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "name": "komon-kimmersdorfer-2025-weBIGeo-teaser.png", "type": "image/png", "size": 6536942, "path": "Publication:komon-kimmersdorfer-2025-weBIGeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/komon-kimmersdorfer-2025-weBIGeo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/komon-kimmersdorfer-2025-weBIGeo-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9555" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/", "__class": "Publication" }, { "id": "walchhofer_ar_flowmaps", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "AR Visualization of Migration Flows in Europe", "date": "2025-03", "abstract": "Origin-Destination (OD) flow maps are a tool for visualizing movement patterns in domains such as transportation, trade, or migration. OD flow maps visualize movement using a network of directional and weighted curves. Traditional 2D OD flow maps often suffer from visual clutter and occlusion, limiting their ffectiveness in conveying complex spatial relationships. This thesis explores the use of Augmented Reality (AR) for OD flow map visualization of migration data to enhance interactivity, data comprehensibility, and spatial awareness. By extending OD flow maps to the third dimension of time, users can interact with the data dynamically and view OD connections from multiple perspectives across a span of years. This thesis develops an approach to visualize and encode the time component using a Space-Time Cube (STC), which encodes the time as\nan additional spatial dimension. The research involves the implementation of a force-directed layout algorithm based on work by Jenny et al. and the development of a marker-based AR phone application prototype capable of visualizing migration data for EU countries spanning from 2008-2022. This thesis contributes to the fields of data visualization, computer graphics, and human-computer interaction, providing insights into how immersive technologies can enhance spatio-temporal data visualization", "authors_et_al": false, "substitute": null, "main_image": { "description": "A 3D migration flow map of Central Europe with stacked flow lines representing individual years.", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1318, "image_height": 977, "name": "walchhofer_ar_flowmaps-teaser.png", "type": "image/png", "size": 584452, "path": "Publication:walchhofer_ar_flowmaps", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5452 ], "date_end": "2025-03", "date_start": "2024-09", "matrikelnr": "12024752", "supervisor": [ 1813, 1410 ], "research_areas": [ "InfoVis", "VR" ], "keywords": [], "weblinks": [], "files": [ { "description": "A 3D migration flow map of Central Europe with stacked flow lines representing individual years.", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1318, "image_height": 977, "name": "walchhofer_ar_flowmaps-teaser.png", "type": "image/png", "size": 584452, "path": "Publication:walchhofer_ar_flowmaps", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1318, "preview_image_height": 977, "name": "walchhofer_ar_flowmaps-thesis.pdf", "type": "application/pdf", "size": 26253749, "path": "Publication:walchhofer_ar_flowmaps", "preview_name": "walchhofer_ar_flowmaps-thesis:preview.png", "preview_type": "image/png", "preview_size": 584452, "url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/", "__class": "Publication" }, { "id": "holzer-edo", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Enhancing Dashboard Onboarding via LLMs", "date": "2025-01-03", "abstract": "Data visualization offers powerful insights that drive better decision-making, but its\ninherent complexity can often be challenging. To understand these visualizations, an\neffective onboarding process is essential, providing clear guidance on the purpose and\nfunctionality of visualizations for users of all experience levels. Traditional onboarding\napproaches, such as static tutorials, frequently fall short in addressing the unique needs\nof diverse users, leading to confusion and inefficiency. This thesis presents an innovative\nonboarding solution powered by Large Language Models (LLMs), designed to provide\npersonalized, context-aware assistance that adapts dynamically to each user.\nOur approach harnesses the capabilities of prompt engineering, adaptive sequencing, and\nconversational interactions to create a dynamic, engaging onboarding experience. Key\nfeatures include custom prompts to clarify complex visual elements, adaptive sequencing\nthat responds to user behavior, and tailored narratives that adjust to users’ expertise\nlevels. We implemented these features into a prototype system, powered by Llama 3.1\nand ChatGPT 4o, to provide real-time, responsive assistance.\nBy transforming dashboards into more approachable tools, this work makes data visualization\naccessible to a wider audience, ultimately enhancing the way users interact with\nand extract insights from complex data.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1459, "image_height": 853, "name": "holzer-edo-image.PNG", "type": "image/png", "size": 251472, "path": "Publication:holzer-edo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5432 ], "date_end": "2025-01", "date_start": "2024-02", "matrikelnr": "12028208", "supervisor": [ 1892 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1459, "image_height": 853, "name": "holzer-edo-image.PNG", "type": "image/png", "size": 251472, "path": "Publication:holzer-edo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis-bachelor", "main_file": false, "use_in_gallery": false, "access": "public", "name": "holzer-edo-thesis-bachelor.pdf", "type": "application/pdf", "size": 3829629, "path": "Publication:holzer-edo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-thesis-bachelor.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-thesis-bachelor:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/", "__class": "Publication" }, { "id": "stoff-2025-pvu", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/209541", "title": "Prototypical Visualization: Using Prototypical Networks for Visualizing Large Unstructured Data", "date": "2025", "abstract": "Making sense of data is something that many professionals are required to do on a daily basis. This can be a difficult task if the amount of data is so large that it can not be easily examined. One effective method of quickly getting an overview of data structure is visualization, but this is not always a feasible solution with large data due to the sheer amount of data and also the potentially high dimensionality. Machine learning models can help with with the organization and classification of data, but they often require large quantities of labeled training data, which is frequently not readily available. This is why models that can reliably classify data based on only few examples for each class are an interesting topic of research. One such kind of model are prototypical networks. They utilize few samples to create an embedding space in fewer dimensions, in which similar data points cluster around a single class prototype. In this thesis, we investigate if the embedding space of a prototypical network makes for a good approach for the purpose of visualizing high-dimensional, unstructured data. The goal is to reduce the dimensionality of the data in such a way that the highdimensional relations and structures between data points are preserved, resulting in 2D representations of the data that form coherent class clusters in a scatter plot visualization. This approach is compared with, and evaluated against, other well known supervised and unsupervised dimensionality reduction techniques. Through quantitative experiments relying on statistical measures, as well as a qualitative evaluation of our results, we find that our ProtoNet is capable of producing point embeddings in which the spatial separation of classes is as good or better than the other methods.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 1865 ], "ac_number": "AC17416388", "doi": "10.34726/hss.2025.119321", "open_access": "yes", "pages": "62", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [ "Dimensionality Reduction", "Data Visualization", "Prototypical Network", "ProtoNet", "Class Separation", "Scatter Plot" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "stoff-2025-pvu-thesis.pdf", "type": "application/pdf", "size": 1529952, "path": "Publication:stoff-2025-pvu", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/stoff-2025-pvu/stoff-2025-pvu-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/stoff-2025-pvu/stoff-2025-pvu-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/stoff-2025-pvu/", "__class": "Publication" }, { "id": "meka-2024-lpi", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/202164", "title": "Line Perception in Parallel Coordinates under different Aspect Ratios", "date": "2024-10", "abstract": "This thesis investigates the impact of different aspect ratios on the perception of angles and lines in parallel coordinates. Parallel coordinates are a visualization technique for representing multivariate data where each variable is drawn as a parallel axis, and data points are connected by lines across these axes. This method allows for the simultaneous visualization of more than two variables and enables the interpretation of correlation patterns within a given dataset.However, the reliability and accuracy of this interpretation can be significantly influenced by the aspect ratio of the plot. This thesis aims to explore how variations in aspect ratios affect the accuracy and confidence of users in perceiving correlations within parallel coordinates.The methodological approach comprises three components: the development of a web-based visualization tool, a statistical analysis of line and angle parameters, and an empirical user study. The visualization tool enables users to display parallel coordinates in various aspect ratios and analyze the geometric properties of the lines in the plot. The statistical analysis reveals that aspect ratios significantly correlate with the minimum and maximum angles in parallel coordinates, which in turn affects the visual perception and interpretation of the data. These findings are validated through a web-based user study, demonstrating that specific aspect ratios lead to more accurate and reliable correlation estimates. The results underscore considerate usage of flexible aspect ratios to minimize distortion and ensure the reliability of visual data interpretation in parallel coordinates.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1199, "image_height": 556, "name": "meka-2024-lpi-Teaser.png", "type": "image/png", "size": 738921, "path": "Publication:meka-2024-lpi", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/meka-2024-lpi/meka-2024-lpi-Teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/meka-2024-lpi/meka-2024-lpi-Teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,projects", "repositum_presentation_id": null, "authors": [ 5397 ], "co_supervisor": [ 950 ], "date_end": "2024-10", "date_start": "2024-02", "diploma_examina": "2024-10-09", "doi": "10.34726/hss.2024.119265", "matrikelnr": "12045662", "open_access": "yes", "pages": "113", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "Parallel Coordinates", "Aspect Ratio", "Perception" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1199, "image_height": 556, "name": "meka-2024-lpi-Teaser.png", "type": "image/png", "size": 738921, "path": "Publication:meka-2024-lpi", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/meka-2024-lpi/meka-2024-lpi-Teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/meka-2024-lpi/meka-2024-lpi-Teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "meka-2024-lpi-Thesis.pdf", "type": "application/pdf", "size": 5693734, "path": "Publication:meka-2024-lpi", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/meka-2024-lpi/meka-2024-lpi-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/meka-2024-lpi/meka-2024-lpi-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/meka-2024-lpi/", "__class": "Publication" }, { "id": "klaffenboeck-2024-rva", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/209323", "title": "RSVP for VPSA : A Meta Design Study on Rapid Suggestive Visualization Prototyping for Visual Parameter Space Analysis", "date": "2024-09-12", "abstract": "Visual Parameter Space Analysis (VPSA) enables domain scientists to explore input-output relationships of computational models. Existing VPSA applications often feature multi-view visualizations designed by visualization experts for a specific scenario, making it hard for domain scientists to adapt them to their problems without professional help. We present RSVP, the Rapid Suggestive Visualization Prototyping system encoding VPSA knowledge to enable domain scientists to prototype custom visualization dashboards tailored to their specific needs. The system implements a task-oriented, multi-view visualization recommendation strategy over a visualization design space optimized for VPSA to guide users in meeting their analytical demands. We derived the VPSA knowledge implemented in the system by conducting an extensive meta design study over the body of work on VPSA. We show how this process can be used to perform a data and task abstraction, extract a common visualization design space, and derive a task-oriented VisRec strategy. User studies indicate that the system is user-friendly and can uncover novel insights.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 586, "image_height": 568, "name": "klaffenboeck-2024-rva-image.png", "type": "image/png", "size": 169141, "path": "Publication:klaffenboeck-2024-rva", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/klaffenboeck-2024-rva/klaffenboeck-2024-rva-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/klaffenboeck-2024-rva/klaffenboeck-2024-rva-image:thumb{{size}}.png" }, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 1598, 5247, 1072, 193, 196 ], "doi": "10.1109/TVCG.2024.3431930", "first_published": "2024-09-12", "issn": "1941-0506", "journal": "IEEE Transactions on Visualization and Computer Graphics", "open_access": "yes", "pages": "18", "publisher": "IEEE COMPUTER SOC", "research_areas": [ "InfoVis" ], "keywords": [ "input-output model", "literature analysis", "mixed-initiative system", "unobtrusive visualization recommendation", "user study" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 586, "image_height": 568, "name": "klaffenboeck-2024-rva-image.png", "type": "image/png", "size": 169141, "path": "Publication:klaffenboeck-2024-rva", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/klaffenboeck-2024-rva/klaffenboeck-2024-rva-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/klaffenboeck-2024-rva/klaffenboeck-2024-rva-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "klaffenboeck-2024-rva-paper.pdf", "type": "application/pdf", "size": 12681537, "path": "Publication:klaffenboeck-2024-rva", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/klaffenboeck-2024-rva/klaffenboeck-2024-rva-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/klaffenboeck-2024-rva/klaffenboeck-2024-rva-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/klaffenboeck-2024-rva/", "__class": "Publication" }, { "id": "wolf-2024-jhd", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Joint Human-Machine Data Exploration Sandbox", "date": "2024-09", "abstract": "Data analysis exploration is becoming increasingly challenging as datasets grow in scale and complexity. The Joint Human-Machine Data Exploration (JDE) framework offers a novel solution for analyzing large, unstructured datasets by integrating human insight with machine learning. The framework facilitates dynamic user interaction and visual exploration through three interconnected views: the data view, frame view, and knowledge view. These views enable users to align data exploration with evolving knowledge models. Implemented as a flexible, modular system using a client-server architecture, the JDE framework supports interactive data manipulation and real-time feedback. This project developed a functional prototype, the JDE sandbox, showcasing the system's potential for enhancing exploratory data analysis. Future work will focus on expanding the framework's capabilities and improving accessibility for a broader audience.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 7680, "image_height": 3915, "name": "wolf-2024-jhd-teaser.png", "type": "image/png", "size": 2648227, "path": "Publication:wolf-2024-jhd", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/wolf-2024-jhd/wolf-2024-jhd-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/wolf-2024-jhd/wolf-2024-jhd-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5238 ], "date_end": "2024-09", "date_start": "2023-09", "matrikelnr": "00925239", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://gitlab.tuwien.ac.at/e193-02-jde/jde-sandbox", "caption": "GitLab", "description": null, "main_file": 1 }, { "href": "https://sandbox.jde.cg.tuwien.ac.at/sandbox", "caption": "demo", "description": "Online demo of the sandbox", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "report", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wolf-2024-jhd-report.pdf", "type": "application/pdf", "size": 8752213, "path": "Publication:wolf-2024-jhd", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/wolf-2024-jhd/wolf-2024-jhd-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/wolf-2024-jhd/wolf-2024-jhd-report:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 7680, "image_height": 3915, "name": "wolf-2024-jhd-teaser.png", "type": "image/png", "size": 2648227, "path": "Publication:wolf-2024-jhd", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/wolf-2024-jhd/wolf-2024-jhd-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/wolf-2024-jhd/wolf-2024-jhd-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/wolf-2024-jhd/", "__class": "Publication" }, { "id": "melcher-2024-asi", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Acoustics Simulation in the Browser - Making Roommode Calculation with the Finite Element Method Accessible for Non-Experts", "date": "2024-06-27", "abstract": "Rooms that are used for communication or entertainment need suitable room acoustics.\nOften acoustics simulation is a fundamental part of the design of such rooms. While\nexpensive and/or hard to use software packages exist that have a wide range of scientific\napplications, cheap and easy to use possibilities have not been available in the past.\nIn the course of this work, a prototype was developed that aims to simplify the specific\nuse case of calculating and visualizing room modes, a specific undesirable phenomenon in\nroom acoustics.\nIf possible, meaningful values are automatically assumed without user input. High\nautomation and good user guidance are the focus.\nInterviews with test users have shown that not only do they manage to visualize room\nmodes without instruction, but also that they only need 1-2 minutes during their first\nuse to obtain their first calculation result.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "melcher-2024-asi-image.png", "type": "image/png", "size": 206234, "path": "Publication:melcher-2024-asi", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/melcher-2024-asi/melcher-2024-asi-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/melcher-2024-asi/melcher-2024-asi-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5447 ], "date_end": "2024-06", "date_start": "2024-01", "matrikelnr": "00004876", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "bachelor-thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "melcher-2024-asi-bachelor-thesis.pdf", "type": "application/pdf", "size": 2621026, "path": "Publication:melcher-2024-asi", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/melcher-2024-asi/melcher-2024-asi-bachelor-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/melcher-2024-asi/melcher-2024-asi-bachelor-thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "melcher-2024-asi-image.png", "type": "image/png", "size": 206234, "path": "Publication:melcher-2024-asi", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/melcher-2024-asi/melcher-2024-asi-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/melcher-2024-asi/melcher-2024-asi-image:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/melcher-2024-asi/", "__class": "Publication" }, { "id": "pahr-2024-ieo", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/199161", "title": "Investigating the Effect of Operation Mode and Manifestation on Physicalizations of Dynamic Processes", "date": "2024-06", "abstract": "We conducted a study to systematically investigate the communication of complex dynamic processes along a two-dimensional design space, where the axes represent a representation's manifestation (physical or virtual) and operation (manual or automatic). We exemplify the design space on a model embodying cardiovascular pathologies, represented by a mechanism where a liquid is pumped into a draining vessel, with complications illustrated through modifications to the model. The results of a mixed-methods lab study with 28 participants show that both physical manifestation and manual operation have a strong positive impact on the audience's engagement. The study does not show a measurable knowledge increase with respect to cardiovascular pathologies using manually operated physical representations. However, subjectively, participants report a better understanding of the process—mainly through non-visual cues like haptics, but also auditory cues. The study also indicates an increased task load when interacting with the process, which, however, seems to play a minor role for the participants. Overall, the study shows a clear potential of physicalization for the communication of complex dynamic processes, which only fully unfold if observers have to chance to interact with the process.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2634, "image_height": 1232, "name": "pahr-2024-ieo-teaser.png", "type": "image/png", "size": 172079, "path": "Publication:pahr-2024-ieo", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/pahr-2024-ieo/pahr-2024-ieo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/pahr-2024-ieo/pahr-2024-ieo-teaser:thumb{{size}}.png" }, "sync_repositum_override": "projects,date_from,date_to,event,lecturer,pages_from,pages_to", "repositum_presentation_id": null, "authors": [ 1813, 1850, 1464, 1110, 1410 ], "articleno": "e15106", "date_from": "2024-06-27", "date_to": "2024-06-31", "doi": "10.1111/cgf.15106", "event": "EUROVIS", "issn": "1467-8659", "journal": "Computer Graphics Forum", "lecturer": [ 1813 ], "number": "3", "pages": "12", "pages_from": "1", "pages_to": "12", "publisher": "WILEY", "volume": "43", "research_areas": [ "InfoVis", "MedVis", "Perception" ], "keywords": [ "Data Physicalization", "Study", "Cardiovascular Diseases", "Edutainment", "Human Computer Interaction (HCI)", "Mixed Methods" ], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2634, "image_height": 1232, "name": "pahr-2024-ieo-teaser.png", "type": "image/png", "size": 172079, "path": "Publication:pahr-2024-ieo", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/pahr-2024-ieo/pahr-2024-ieo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/pahr-2024-ieo/pahr-2024-ieo-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/pahr-2024-ieo/", "__class": "Publication" }, { "id": "matt-2024-cvil", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/199888", "title": "cVIL: Class-Centric Visual Interactive Labeling", "date": "2024-05-27", "abstract": "We present cVIL, a class-centric approach to visual interactive labeling, which facilitates human annotation of large and complex image data sets. cVIL uses different property measures to support instance labeling for labeling difficult instances and batch labeling to quickly label easy instances. Simulated experiments reveal that cVIL with batch labeling can outperform traditional labeling approaches based on active learning. In a user study, cVIL led to better accuracy and higher user preference compared to a traditional instance-based visual interactive labeling approach based on 2D scatterplots.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Screenshot of cVIL as employed in the user study", "filetitle": "cVIL teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1104, "image_height": 449, "name": "matt-2024-cvil-cVIL teaser.png", "type": "image/png", "size": 293869, "path": "Publication:matt-2024-cvil", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/matt-2024-cvil/matt-2024-cvil-cVIL teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/matt-2024-cvil/matt-2024-cvil-cVIL teaser:thumb{{size}}.png" }, "sync_repositum_override": "abstract,projects,open_access", "repositum_presentation_id": null, "authors": [ 5263, 5370, 1110 ], "booktitle": "Eurographics Proceedings", "date_from": "2024-05-27", "date_to": "2024-05-27", "doi": "10.2312/eurova.20241113", "editor": "El-Assady, Mennatallah and Schulz, Hans-Jorg", "event": "EuroVis Workshop on Visual Analytics (EuroVA 2024)", "isbn": "978-3-03868-056-7", "lecturer": [ 5263 ], "location": "Aarhus", "open_access": "yes", "pages": "6", "publisher": "Eurographics", "research_areas": [ "InfoVis" ], "keywords": [ "Visual Analytics", "Interactive Machine Learning", "User Interface Design" ], "weblinks": [ { "href": "https://diglib.eg.org/server/api/core/bitstreams/c18fafcc-b4b4-4e51-bd2f-cec056c6d93a/content", "caption": "paper", "description": null, "main_file": 1 }, { "href": "https://gitlab.tuwien.ac.at/e193-02-jde/lava", "caption": "GitLab", "description": null, "main_file": 1 } ], "files": [ { "description": "Screenshot of cVIL as employed in the user study", "filetitle": "cVIL teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1104, "image_height": 449, "name": "matt-2024-cvil-cVIL teaser.png", "type": "image/png", "size": 293869, "path": "Publication:matt-2024-cvil", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/matt-2024-cvil/matt-2024-cvil-cVIL teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/matt-2024-cvil/matt-2024-cvil-cVIL teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/matt-2024-cvil/", "__class": "Publication" }, { "id": "eichner-2024-erv", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Effizientes Rendern von Wäldern mittels Gruppierter Detailgrade in 3D-Geoinformationssystemen", "date": "2024-05-15", "abstract": "Interactive visualization is important for many workflows. Especially so in the context\nof 3D geo-informations systems, where large quantities of data have to be processed\nand presented to the user at interactive speeds for productivity and orientation in the\ngeo-spatial context. In heavily forested countries like Austria enormous amounts of\ngeometry have to be drawn when visualizing forests. Naïve rendering approaches fail,\neven when using heavily simplified geometry for the individual trees. The region in which\ndetails are necessary is small and changes frequently. A major part of the scene is far\naway and needs little detail. These constraints are what this thesis attempts to find a\nsolution for. Thus each tree is represented by a billboard, if not close to the camera. To\ndecrease the computational complexity of selecting the appropriate level of detail for all\ntrees, they are grouped into batches, for which frustum culling and level of detail selection\nhappens. This new approach is implemented, qualitatively evaluated, and compared with\nexisting alternative approaches. Comparison of the approaches on a stress test scene\nshows that our new approach can be between 1.7 and 6 times faster than the approaches\ntested against depending on the scenario, while barely reducing visual quality.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "eichner-2024-erv-image.png", "type": "image/png", "size": 984848, "path": "Publication:eichner-2024-erv", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/eichner-2024-erv/eichner-2024-erv-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/eichner-2024-erv/eichner-2024-erv-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5448 ], "date_end": "2024-05", "date_start": "2024-01", "matrikelnr": "11808244", "supervisor": [ 166 ], "research_areas": [ "InfoVis", "Rendering" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "bachelor-thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "eichner-2024-erv-bachelor-thesis.pdf", "type": "application/pdf", "size": 6457572, "path": "Publication:eichner-2024-erv", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/eichner-2024-erv/eichner-2024-erv-bachelor-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/eichner-2024-erv/eichner-2024-erv-bachelor-thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "eichner-2024-erv-image.png", "type": "image/png", "size": 984848, "path": "Publication:eichner-2024-erv", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/eichner-2024-erv/eichner-2024-erv-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/eichner-2024-erv/eichner-2024-erv-image:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/eichner-2024-erv/", "__class": "Publication" }, { "id": "heim-2024-accustripes", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/197495", "title": "AccuStripes: Visual exploration and comparison of univariate data distributions using color and binning", "date": "2024-04", "abstract": "Understanding and analyzing univariate distributions of data in terms of their shapes as well as their specific characteristics, regarding gaps, spikes, or outliers, is crucial in many scientific disciplines. In this paper, we propose a design space composed of the visual channels position and color for representing accumulated distributions. The designs are a mixture of color-coded stripes with density lines. The width and coloring of the stripes is based on the applied binning technique. In a crowd-sourced experiment we explore a subspace, called the AccuStripes (i.e., “accumulated stripes”) design space, consisting of nine representations. These AccuStripes designs integrate three composition strategies (color only, overlay, filled curve) with three binning techniques, one uniform (UB) and two adaptive methods, namely Bayesian Blocks (BB) and Jenks’ Natural Breaks (NB). We evaluate the accuracy, efficiency, and confidence ratings of the nine AccuStripes designs for structural estimation and comparison tasks. Across all study tasks, the overlay composition was found to be most accurate and preferred by observers. Furthermore, the results demonstrate that while no binning method performed best in both identification and comparison, detection of structures using adaptive binning was the most accurate one. For validation we compared the best AccuStripes’ design, i.e., the overlay composition, to line charts. Our results show that the AccuStripes’ design outperformed the line charts in accuracy for all study tasks.", "authors_et_al": false, "substitute": null, "main_image": { "description": "AccuStripes - Graphical Abstract", "filetitle": "accuStripes", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1333, "image_height": 428, "name": "heim-2024-accustripes-accuStripes.png", "type": "image/png", "size": 366335, "path": "Publication:heim-2024-accustripes", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/heim-2024-accustripes/heim-2024-accustripes-accuStripes.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/heim-2024-accustripes/heim-2024-accustripes-accuStripes:thumb{{size}}.png" }, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 1354, 1355, 1110, 166, 611 ], "articleno": "103906", "doi": "10.1016/j.cag.2024.103906", "issn": "1873-7684", "journal": "COMPUTERS & GRAPHICS-UK", "publisher": "PERGAMON-ELSEVIER SCIENCE LTD", "volume": "119", "research_areas": [ "InfoVis" ], "keywords": [ "Adaptive binning", "Crowd-sourced experiment", "Univariate data distributions", "Visual analysis" ], "weblinks": [ { "href": "https://www.sciencedirect.com/science/article/pii/S0097849324000414", "caption": "paper", "description": null, "main_file": 1 } ], "files": [ { "description": "AccuStripes - Graphical Abstract", "filetitle": "accuStripes", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1333, "image_height": 428, "name": "heim-2024-accustripes-accuStripes.png", "type": "image/png", "size": 366335, "path": "Publication:heim-2024-accustripes", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/heim-2024-accustripes/heim-2024-accustripes-accuStripes.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/heim-2024-accustripes/heim-2024-accustripes-accuStripes:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/heim-2024-accustripes/", "__class": "Publication" }, { "id": "wagner-2024-par", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Pixel Art Restoration", "date": "2024-03-20", "abstract": "Games developed in the 8 and 16-bit era of computing used low-resolution images called\nsprites for displaying game worlds and their objects. This art style is often referred to as\nPixel-Art and evolved into its own subgenre of games with new games still getting released\nto this day. While modern Pixel-Art games incorporate the visual fidelity of modern\nLiquid Crystal Display (LCD) monitors into their design, games from the Cathode Ray\nTube (CRT) era often look worse when displayed on an LCD monitor. Understandable,\nsince games at that time were designed to look good on CRT TVs and Monitors which\nfunction in very different ways compared to modern Displays.\nSince the upcoming of retro game console emulators, a lot of effort was put into reproducing\nthe effects of CRT monitors when playing back these old game files on LCD monitors. This\noften requires the use of upscaling algorithms to improve the look of the low-resolution\ngame assets on higher-resolution monitors. Upscaling in general but also tailored towards\nPixel-Art is still an unsolved problem and the focus of many recent publications.\nIn this work, we will explore what effects CRT monitors have on Pixel-Art and how to\nuse this information to guide the upscaling of 8 and 16-bit era Pixel-Art to improve\nvisual fidelity when displayed on modern LCD monitors.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1424, "image_height": 748, "name": "wagner-2024-par-teaser.jpg", "type": "image/jpeg", "size": 194244, "path": "Publication:wagner-2024-par", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/wagner-2024-par/wagner-2024-par-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/wagner-2024-par/wagner-2024-par-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5340 ], "date_end": "2024-03-20", "date_start": "2023", "matrikelnr": "11907095", "supervisor": [ 193 ], "research_areas": [ "InfoVis", "Rendering" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1424, "image_height": 748, "name": "wagner-2024-par-teaser.jpg", "type": "image/jpeg", "size": 194244, "path": "Publication:wagner-2024-par", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/wagner-2024-par/wagner-2024-par-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/wagner-2024-par/wagner-2024-par-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wagner-2024-par-thesis.pdf", "type": "application/pdf", "size": 104824143, "path": "Publication:wagner-2024-par", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/wagner-2024-par/wagner-2024-par-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/wagner-2024-par/wagner-2024-par-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/wagner-2024-par/", "__class": "Publication" }, { "id": "ehlers-2024-vgs", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/196069", "title": "Visualizing Group Structure in Compound Graphs: The Current State, Lessons Learned, and Outstanding Opportunities", "date": "2024-03-11", "abstract": "Compound graphs are common across domains, from social science to biochemical pathway studies, and their visualization is important to both their exploration and analysis. However, effectively visualizing a compound graph's topology and group structure requires careful consideration, as evident by the many different approaches to this particular problem. To better understand the current advancements in compound graph visualization, we have consolidated and streamlined existing surveys' taxonomies. More specifically, we aim to disentangle the visual relationship between graph topology and group structure from the visual encoding used to visualize its group structure in order to identify interesting gaps in the literature. In so doing, we are able to enumerate a number of lessons learned and gain a better understanding of the outstanding research opportunities and practical implications across domains.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 1850, 1848, 1464, 1410 ], "booktitle": "Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1, HUCAPP and IVAPP", "date_from": "2024-02-27", "date_to": "2024-02-29", "doi": "10.5220/0012431200003660", "event": "19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications", "isbn": "978-989-758-679-8", "lecturer": [ 1850 ], "location": "Rom", "pages": "12", "pages_from": "697", "pages_to": "708", "research_areas": [ "InfoVis", "NetVis" ], "keywords": [ "compound graph visualization", "literature survey", "group structure visualization" ], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/ehlers-2024-vgs/", "__class": "Publication" }, { "id": "eitler-2024-sos", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/205306", "title": "Spatial Organization Strategies in Exploratory Analysis of Unstructured Data", "date": "2024", "abstract": "As not only the amount but also the complexity of data increases, there is a growing need to support humans in the analysis of data that is not structured in a way that can be easily interpreted by machines. So-called “knowledge-assisted visual analytics” (KAVA) tools aim to address these challenges by integrating the knowledge of the analyst into their system to support the analysis process.In this thesis, we investigate the spatial organization strategies that users employ when exploring unstructured data. We aim to characterize the types of strategies that users employ, how they change over time, and how we can use them to infer the users’ knowledge of the data. To answer these questions, we first conduct a user study in which the participants explore an image dataset on a multitouch tabletop interface imitating an analogue setting and externalize their findings into concept maps. We observe their organization strategies and analyse their methods in a mixed-methods approach, combining qualitative analysis of the participants’ interview statements with quantitative analysis of the interaction logs.We find that the participants’ spatial organization strategies can be characterized by four features: semantic clusters, type of layout, uncovering process, and reorganization of the data. While most participants prefer layouts that give them an overview of the data, only about half create semantic clusters (i.e., grouping similar images together). The participants also mostly uncovered all images — which were initially on a stack — in the task right away before externalizing their knowledge, and only a few reorganized the images. We further find that the participants generally did not change their organization strategies over time, and that the resulting spatial arrangements do not necessarily provide valuable insights into the users’ knowledge of the data.Finally, we discuss our findings and list the limitations of our study. As this thesis is embedded in a research project that aims to develop a tool for knowledge-assisted visual analytics, we discuss potential design implications for the development of such a tool.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 5419 ], "doi": "10.34726/hss.2024.117186", "open_access": "yes", "pages": "95", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [ "visual analytics", "unstructured data", "spatial organization", "exploratory analysis", "knowledge-assisted visual analytics", "semantic interaction", "knowledge externalization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "eitler-2024-sos-thesis.pdf", "type": "application/pdf", "size": 2087980, "path": "Publication:eitler-2024-sos", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/eitler-2024-sos/eitler-2024-sos-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/eitler-2024-sos/eitler-2024-sos-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/eitler-2024-sos/", "__class": "Publication" }, { "id": "irendorfer-2024-uat", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/202525", "title": "User Approaches to Knowledge Externalization in Visual Analytics of Unstructured Data", "date": "2024", "abstract": "Traditional machine learning approaches for analyzing large unstructured data often depend on labelled training data and well-defined target definitions. However, these may not be available or feasible when dealing with unknown and unstructured data. It requires human reasoning and domain knowledge to interpret it. Interactive systems that combine human analytical abilities with machine learning techniques can address this limitation. However, to incorporate human knowledge in such systems, we need a better understanding of the semantic information and structures that users observe and expect while exploring unstructured data, as well as how they make their tacit knowledge explicit. This thesis aims to narrow the gap between human cognition and (knowledge-assisted) visual analytics. In a qualitative and exploratory user study, this thesis investigates how individuals explore a large unstructured dataset and which strategies they apply to externalize their mental models. By analyzing users' externalized mental models, we aim to better understand how their knowledge evolves during data exploration. We evaluate the comprehensiveness, detail and evolution of users' external knowledge representations by applying quantitative and qualitative methods, including a crowdsourcing step. The results show that users' externalized structures are able to represent a given dataset comprehensively and to a high degree of detail. While these knowledge representations are highly subjective and show various individual differences, we could identify structural similarities between individuals. In addition to the insights about how users externalize their tacit knowledge during data exploration, we propose design guidelines for (knowledge-assisted) visual analytics systems.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 5399 ], "doi": "10.34726/hss.2024.115066", "open_access": "yes", "pages": "80", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [ "Knowledge Externalization", "Knowledge-Assisted Visualization", "Visual Analytics", "Unstructured Data", "Concept Maps", "Mental Models", "User Study", "Data Exploration" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "irendorfer-2024-uat-thesis.pdf", "type": "application/pdf", "size": 1981913, "path": "Publication:irendorfer-2024-uat", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/irendorfer-2024-uat/irendorfer-2024-uat-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/irendorfer-2024-uat/irendorfer-2024-uat-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/irendorfer-2024-uat/", "__class": "Publication" }, { "id": "turner-aso", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "A Study on the Impact of Uncertainties on the Analytical Process", "date": "2023-12", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 708, "preview_image_height": 333, "name": "turner-aso-.pdf", "type": "application/pdf", "size": 2585393, "path": "Publication:turner-aso", "preview_name": "turner-aso-:preview.JPG", "preview_type": "image/jpeg", "preview_size": 45281, "url": "https://www.cg.tuwien.ac.at/research/publications/2023/turner-aso/turner-aso-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/turner-aso/turner-aso-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5331 ], "date_end": "2023", "date_start": "2023", "matrikelnr": "11908540", "supervisor": [ 1410 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 708, "preview_image_height": 333, "name": "turner-aso-.pdf", "type": "application/pdf", "size": 2585393, "path": "Publication:turner-aso", "preview_name": "turner-aso-:preview.JPG", "preview_type": "image/jpeg", "preview_size": 45281, "url": "https://www.cg.tuwien.ac.at/research/publications/2023/turner-aso/turner-aso-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/turner-aso/turner-aso-:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2023/turner-aso/", "__class": "Publication" }, { "id": "eschner-2023-evl", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Echtzeitvisualisierung von Lawinenrisiko basierend auf hochauflösenden Geodaten", "date": "2023-11-18", "abstract": "Um das Lawinenrisiko auf Touren abzuschätzen, konsultieren Tourengeher·innen typischerweise vorab den aktuellen Lawinenlagebericht (LLB) sowie die Geländeeigenschaften, wie Hangneigung, Höhe und Exposition der geplanten Tour auf einer Karte. Reduktionsmethoden wie Stop-or-Go oder die SnowCard können sowohl bei der Planung als auch vor Ort angewandt werden, um das Risiko abzuschätzen. Bei korrekter Anwendung dieser Methoden könnte ein Großteil der Todesfälle vermieden werden. Die Anwendung umfasst jedoch mehrere kognitiv aufwändige Schritte: Im ersten Schritt müssen Tourengeher·innen die Informationen aus LLB und Karte korrekt verknüpfen und anhand der gewählten Methode interpretieren, um potenziell kritische Regionen entlang der Route vorab identifizieren zu können. Im zweiten Schritt müssen potenziell kritische Regionen auch während der Tour als solche wiedererkannt und vor Ort beurteilt werden. \nUm die Anwendung von Reduktionsmethoden für Wintersportler·innen zu vereinfachen, können die Informationen aus LLB computergestützt mit den Geländeeigenschaften ausgewertet und direkt in einer Karte dargestellt werden. Skitourenguru, beispielsweise, berechnet das Lawinenrisiko entlang vorgegebener Routen und stellt diese in einer 2D Karte dar. Im Vergleich zu 2D Karten erleichtert eine dreidimensionale Darstellung jedoch die Interpretation des Geländes und das Finden von Routen. Unsere Hypothese ist daher, dass eine direkte Visualisierung des Lawinenrisikos auf einer detaillierten 3D Karte die Identifikation von potenziell kritischen Regionen einer Route in der Planungsphase, sowie deren Wiedererkennung während der Tour, erleichtert.\nWir stellen eine integrierte 3D Risikovisualisierung vor, welche Daten aus dem aktuellen LLB mit einem hochauflösenden Geländemodell kombiniert und existierende Reduktionsmethoden in Echtzeit auswertet, um das Ergebnis auf einer interaktiven Webseite zu visualisieren.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2076, "image_height": 1192, "name": "eschner-2023-evl-.png", "type": "image/png", "size": 4716902, "path": "Publication:eschner-2023-evl", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/eschner-2023-evl/eschner-2023-evl-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/eschner-2023-evl/eschner-2023-evl-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1653, 1013, 1110 ], "booktitle": "Lawinensymposium 2023", "cfp": { "name": "lawinensymposium_cfp.pdf", "type": "application/pdf", "error": "0", "size": "3319607", "orig_name": "lawinensymposium_cfp.pdf", "ext": "pdf" }, "event": "Lawinensymposium 2023", "lecturer": [ 1653 ], "location": "Graz", "pages_from": "38", "pages_to": "43", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://alpinemaps.cg.tuwien.ac.at/ ", "caption": "online demo", "description": " Demo version of the avalanche risk visualization ", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2076, "image_height": 1192, "name": "eschner-2023-evl-.png", "type": "image/png", "size": 4716902, "path": "Publication:eschner-2023-evl", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/eschner-2023-evl/eschner-2023-evl-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/eschner-2023-evl/eschner-2023-evl-:thumb{{size}}.png" }, { "description": null, "filetitle": "paper preprint", "main_file": true, "use_in_gallery": false, "access": "public", "name": "eschner-2023-evl-paper preprint.pdf", "type": "application/pdf", "size": 21355472, "path": "Publication:eschner-2023-evl", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/eschner-2023-evl/eschner-2023-evl-paper preprint.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/eschner-2023-evl/eschner-2023-evl-paper preprint:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2023/eschner-2023-evl/", "__class": "Publication" }, { "id": "medeiros-2023-gwf", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/193561", "title": "Going with the flow: using immersive analytics to support lifetime predictions of hydropower turbines", "date": "2023-10-13", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 536, "image_height": 320, "name": "medeiros-2023-gwf-teaser.png", "type": "image/png", "size": 116775, "path": "Publication:medeiros-2023-gwf", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/medeiros-2023-gwf/medeiros-2023-gwf-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/medeiros-2023-gwf/medeiros-2023-gwf-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5326, 5327, 5328, 5329, 950 ], "booktitle": "Proceedings SUI 2023 ACM : Symposium on Spatial User Interaction", "date_from": "2023-10-13", "date_to": "2023-10-15", "doi": "10.1145/3607822.3618009", "editor": "Huang, Tony and Sra, Misha and Argelaguet, Ferran and Lopes, Pedro and Barrera Machuca, Mayra Donaji", "event": "SUI '23: ACM Symposium on Spatial User Interaction", "isbn": "979-8-4007-0281-5", "lecturer": [ 5326 ], "location": "Sydney", "open_access": "no", "pages": "2", "publisher": "Association for Computing Machinery", "research_areas": [ "InfoVis", "VR" ], "keywords": [ "Data visualization", "Virtual Reality", "Egocentric Navigation" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "medeiros-2023-gwf-paper.pdf", "type": "application/pdf", "size": 1351229, "path": "Publication:medeiros-2023-gwf", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/medeiros-2023-gwf/medeiros-2023-gwf-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/medeiros-2023-gwf/medeiros-2023-gwf-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 536, "image_height": 320, "name": "medeiros-2023-gwf-teaser.png", "type": "image/png", "size": 116775, "path": "Publication:medeiros-2023-gwf", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/medeiros-2023-gwf/medeiros-2023-gwf-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/medeiros-2023-gwf/medeiros-2023-gwf-teaser:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2023/medeiros-2023-gwf/", "__class": "Publication" }, { "id": "arbesser_ba_2023", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visualizing the Flow of Healthcare Data", "date": "2023-06", "abstract": "The flow of medical data in a modern and interconnected society between large numbers\nof stakeholders and institutions forms an intricate network. Due to size and complexity,\nthis network is hard to traverse for anyone wishing to gain insight into where their\nmedical data ends up. Visualisation can be used as a powerful tool, in order to make this\nflow of data more accessible and easier to understand for experts and everyday people,\nincreasing transparency and readability. This work aims to explore ways to visualise\nparts of this network and provide a framework that visualises the connections between\nthe different stakeholders in it and the data they exchange. The implementation will\nbe done as a web application which provides interactivity to improve user experience.\nThis interactivity will implement the visual information-seeking mantra, by giving an\noverview first and allowing zooming, filtering and showing details on demand. Whether\nthe set requirements were met will be determined by gathering feedback from expert\nusers about their experience in using the application.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1229, "image_height": 412, "name": "arbesser_ba_2023-teaser.png", "type": "image/png", "size": 133874, "path": "Publication:arbesser_ba_2023", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/arbesser_ba_2023/arbesser_ba_2023-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/arbesser_ba_2023/arbesser_ba_2023-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5279 ], "date_end": "2023-06", "date_start": "2022-11", "matrikelnr": "01625725", "supervisor": [ 1110 ], "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1229, "image_height": 412, "name": "arbesser_ba_2023-teaser.png", "type": "image/png", "size": 133874, "path": "Publication:arbesser_ba_2023", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/arbesser_ba_2023/arbesser_ba_2023-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/arbesser_ba_2023/arbesser_ba_2023-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "arbesser_ba_2023-thesis.pdf", "type": "application/pdf", "size": 2885571, "path": "Publication:arbesser_ba_2023", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/arbesser_ba_2023/arbesser_ba_2023-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/arbesser_ba_2023/arbesser_ba_2023-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2023/arbesser_ba_2023/", "__class": "Publication" }, { "id": "indirectBiasLanguageModels-2023", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/187890", "title": "Visual Exploration of Indirect Bias in Language Models", "date": "2023-06", "abstract": "Language models are trained on large text corpora that often include stereotypes. This can lead to direct or indirect bias in downstream applications. In this work, we present a method for interactive visual exploration of indirect multiclass bias learned by contextual word embeddings. We introduce a new indirect bias quantification score and present two interactive visualizations to explore interactions between multiple non-sensitive concepts (such as sports, occupations, and beverages) and sensitive attributes (such as gender or year of birth) based on this score.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1904, "image_height": 619, "name": "indirectBiasLanguageModels-2023-teaser.png", "type": "image/png", "size": 81826, "path": "Publication:indirectBiasLanguageModels-2023", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/indirectBiasLanguageModels-2023/indirectBiasLanguageModels-2023-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/indirectBiasLanguageModels-2023/indirectBiasLanguageModels-2023-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,location,keywords", "repositum_presentation_id": null, "authors": [ 5211, 1110 ], "booktitle": "EuroVis 2023 - 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DNNs are a type of Artificial Neural Network (ANN) that consist of an\ninput layer, an output layer, and multiple hidden layers. They are able to make predictions\nor decisions based on unseen observations, but the way that they arrive at these\ndecisions can often be opaque, or difficult to interpret. By exploring the similarities of\nfeature vectors in the latent space created by the network, it is possible to gain insight\ninto how the network organizes and classifies observations with similar properties that are\nalso interpretable to the human eye.\n\nThe goal of this work is to develop a prototype that enables interactive exploration\nof data clusterings in high-dimensional feature spaces, instead of the traditional twodimensional\nvisual representation.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1425, "image_height": 904, "name": "wolf-2023-cc-teaser.png", "type": "image/png", "size": 184141, "path": "Publication:wolf-2023-cc", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/wolf-2023-cc/wolf-2023-cc-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/wolf-2023-cc/wolf-2023-cc-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5238 ], "date_end": "2023-03", "date_start": "2022-03", "matrikelnr": "0925239", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "report", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wolf-2023-cc-report.pdf", "type": "application/pdf", "size": 2221475, "path": "Publication:wolf-2023-cc", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/wolf-2023-cc/wolf-2023-cc-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/wolf-2023-cc/wolf-2023-cc-report:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1425, "image_height": 904, "name": "wolf-2023-cc-teaser.png", "type": "image/png", "size": 184141, "path": "Publication:wolf-2023-cc", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/wolf-2023-cc/wolf-2023-cc-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/wolf-2023-cc/wolf-2023-cc-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2023/wolf-2023-cc/", "__class": "Publication" }, { "id": "sMolBoxes_2022", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/81180", "title": "sMolBoxes: Dataflow Model for Molecular Dynamics Exploration", "date": "2022-10", "abstract": "We present sMolBoxes, a dataflow representation for the exploration and analysis of long molecular dynamics (MD) simulations. When MD simulations reach millions of snapshots, a frame-by-frame observation is not feasible anymore. Thus, biochemists rely to a large extent only on quantitative analysis of geometric and physico-chemical properties. However, the usage of abstract methods to study inherently spatial data hinders the exploration and poses a considerable workload. sMolBoxes link quantitative analysis of a user-defined set of properties with interactive 3D visualizations. They enable visual explanations of molecular behaviors, which lead to an efficient discovery of biochemically significant parts of the MD simulation. sMolBoxes follow a node-based model for flexible definition, combination, and immediate evaluation of properties to be investigated. Progressive analytics enable fluid switching between multiple properties, which facilitates hypothesis generation. Each sMolBox provides quick insight to an observed property or function, available in more detail in the bigBox View. The case studies illustrate that even with relatively few sMolBoxes, it is possible to express complex analytical tasks, and their use in exploratory analysis is perceived as more efficient than traditional scripting-based methods.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1604, "image_height": 942, "name": "sMolBoxes_2022-teaser.png", "type": "image/png", "size": 417094, "path": "Publication:sMolBoxes_2022", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/sMolBoxes_2022/sMolBoxes_2022-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/sMolBoxes_2022/sMolBoxes_2022-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5182, 1110, 1733, 1498, 5183, 1248, 1254 ], "date_from": "2022-10", 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Despite its accuracy, manual labeling is time-consuming and tedious-hence, the potential of automatic approaches, such as deep learning models, is being investigated. A promising trend in deep learning tumor segmentation is cross-modal domain adaptation, where knowledge learned on one source distribution (e.g., one modality) is transferred to another distribution. Yet, artificial intelligence (AI) engineers developing such models, need to thoroughly assess the robustness of their approaches, which demands a deep understanding of the model(s) behavior. In this paper, we propose a web-based visual analytics application that supports the visual assessment of the predictive performance of deep learning-based models built for cross-modal brain tumor segmentation. Our application supports the multi-level comparison of multiple models drilling from entire cohorts of patients down to individual slices, facilitates the analysis of the relationship between image-derived features and model performance, and enables the comparative exploration of the predictive outcomes of the models. All this is realized in an interactive interface with multiple linked views. We present three use cases, analyzing differences in deep learning segmentation approaches, the influence of the tumor size, and the relationship of other data set characteristics to the performance. From these scenarios, we discovered that the tumor size, i.e., both volumetric in 3D data and pixel count in 2D data, highly affects the model performance, as samples with small tumors often yield poorer results. 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"name": "stritzel2022-.JPG", "type": "image/jpeg", "size": 21887, "path": "Publication:stritzel2022", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/stritzel2022/stritzel2022-.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/stritzel2022/stritzel2022-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5188, 1410 ], "booktitle": "Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM2022).", "cfp": { "name": "Full, Short & Survey Papers.pdf", "type": "application/pdf", "error": "0", "size": "195197", "orig_name": "Full, Short & Survey Papers.pdf", "ext": "pdf" }, "event": "EG VCBM 2022", "lecturer": [ 1410 ], "pages_from": "129", "pages_to": "133", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [ { "href": "https://diglib.eg.org/handle/10.2312/vcbm20221196", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 479, "image_height": 175, "name": "stritzel2022-.JPG", "type": "image/jpeg", "size": 21887, "path": "Publication:stritzel2022", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/stritzel2022/stritzel2022-.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/stritzel2022/stritzel2022-:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 409, "preview_image_height": 458, "name": "stritzel2022-paper.pdf", "type": "application/pdf", "size": 1904424, "path": "Publication:stritzel2022", "preview_name": "stritzel2022-paper:preview.PNG", "preview_type": "image/png", "preview_size": 67566, "url": "https://www.cg.tuwien.ac.at/research/publications/2022/stritzel2022/stritzel2022-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/stritzel2022/stritzel2022-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "supplementarty images ", "main_file": false, "use_in_gallery": false, "access": "public", "name": "stritzel2022-supplementarty images .pdf", "type": "application/pdf", "size": 364096, "path": "Publication:stritzel2022", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/stritzel2022/stritzel2022-supplementarty images .pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/stritzel2022/stritzel2022-supplementarty images :thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/stritzel2022/", "__class": "Publication" }, { "id": "martorell2022", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/150213", "title": "Breast cancer patient characterisation and visualisation using deep learning and fisher information networks", "date": "2022-08-17", "abstract": "Breast cancer is the most commonly diagnosed female malignancy globally, with better survival rates if diagnosed early. Mammography is the gold standard in screening programmes for breast cancer, but despite technological advances, high error rates are still reported. Machine learning techniques, and in particular deep learning (DL), have been successfully used for breast cancer detection and classification. However, the added complexity that makes DL models so successful reduces their ability to explain which features are relevant to the model, or whether the model is biased. The main aim of this study is to propose a novel visualisation to help characterise breast cancer patients using Fisher Information Networks on features extracted from mammograms using a DL model. In the proposed visualisation, patients are mapped out according to their similarities and can be used to study new patients as a 'patient-like-me' approach. When applied to the CBIS-DDSM dataset, it was shown that it is a competitive methodology that can (i) facilitate the analysis and decision-making process in breast cancer diagnosis with the assistance of the FIN visualisations and 'patient-like-me' analysis, and (ii) help improve diagnostic accuracy and reduce overdiagnosis by identifying the most likely diagnosis based on clinical similarities with neighbouring patients.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1283, "image_height": 829, "name": "martorell2022-.JPG", "type": "image/jpeg", "size": 126972, "path": "Publication:martorell2022", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/martorell2022/martorell2022-.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/martorell2022/martorell2022-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5189, 5190, 5191, 1410, 5192, 5193, 5194, 5195, 5196 ], "doi": "10.1038/s41598-022-17894-6", "issn": "2045-2322", "journal": "Scientific Reports", "open_access": "yes", "pages": "14", "publisher": "Nature Publishing", "volume": "12", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [ "Breast", "Female", "Humans", "Information Services", "Mammography", "Breast Neoplasms", "Deep Learning" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1283, "image_height": 829, "name": "martorell2022-.JPG", "type": "image/jpeg", "size": 126972, "path": "Publication:martorell2022", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/martorell2022/martorell2022-.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/martorell2022/martorell2022-:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/martorell2022/", "__class": "Publication" }, { "id": "musleh-2022-mam5", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/142512", "title": "Visual analysis of blow molding machine multivariate time series data", "date": "2022-07-11", "abstract": "The recent development in the data analytics field provides a boost in production for modern industries. Small-sized factories intend to take full advantage of the data collected by sensors used in their machinery. The ultimate goal is to minimize cost and maximize quality, resulting in an increase in profit. In collaboration with domain experts, we implemented a data visualization tool to enable decision-makers in a plastic factory to improve their production process. The tool is an interactive dashboard with multiple coordinated views supporting the exploration from both local and global perspectives. In summary, we investigate three different aspects: methods for preprocessing multivariate time series data, clustering approaches for the already refined data, and visualization techniques that aid domain experts in gaining insights into the different stages of the production process. Here we present our ongoing results grounded in a human-centered development process. We adopt a formative evaluation approach to continuously upgrade our dashboard design that eventually meets partners’ requirements and follows the best practices within the field. We also conducted a case study with a domain expert to validate the potential application of the tool in the real-life context. Finally, we assessed the usability and usefulness of the tool with a two-layer summative evaluation that showed encouraging results.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Graphical Abstract", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 685, "image_height": 462, "name": "musleh-2022-mam5-Graphical Abstract.webp", "type": "image/webp", "size": 41652, "path": "Publication:musleh-2022-mam5", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/musleh-2022-mam5/musleh-2022-mam5-Graphical Abstract.webp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/musleh-2022-mam5/musleh-2022-mam5-Graphical Abstract:thumb{{size}}.png" }, "sync_repositum_override": "abstract,date", "repositum_presentation_id": null, "authors": [ 1867, 5213, 5214 ], "doi": "10.1007/s12650-022-00857-4", "issn": "1875-8975", "journal": "Journal of Visualization", "open_access": "yes", "pages": "14", "pages_from": "1329", "pages_to": "1342", "publisher": "Springer", "volume": "25", "research_areas": [ "InfoVis" ], "keywords": [ "Time series data", "Unsupervised machine learning", "Visualization" ], "weblinks": [ { "href": "https://link.springer.com/article/10.1007/s12650-022-00857-4", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "Graphical Abstract", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 685, "image_height": 462, "name": "musleh-2022-mam5-Graphical Abstract.webp", "type": "image/webp", "size": 41652, "path": "Publication:musleh-2022-mam5", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/musleh-2022-mam5/musleh-2022-mam5-Graphical Abstract.webp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/musleh-2022-mam5/musleh-2022-mam5-Graphical Abstract:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "musleh-2022-mam5-paper.pdf", "type": "application/pdf", "size": 1034180, "path": "Publication:musleh-2022-mam5", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/musleh-2022-mam5/musleh-2022-mam5-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/musleh-2022-mam5/musleh-2022-mam5-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/musleh-2022-mam5/", "__class": "Publication" }, { "id": "grossmann-2022-conceptSplatters", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/152292", "title": "Concept splatters: Exploration of latent spaces based on human interpretable concepts", "date": "2022-04", "abstract": "Similarity maps show dimensionality-reduced activation vectors of a high number of data points and thereby can help to understand which features a neural network has learned from the data. However, similarity maps have severely limited expressiveness for large datasets with hundreds of thousands of data instances and thousands of labels, such as ImageNet or word2vec. In this work, we present “concept splatters” as a scalable method to interactively explore similarities between data instances as learned by the machine through the lens of human-understandable semantics. Our approach enables interactive exploration of large latent spaces on multiple levels of abstraction. We present a web-based implementation that supports interactive exploration of tens of thousands of word vectors of word2vec and CNN feature vectors of ImageNet. In a qualitative study, users could effectively discover spurious learning strategies of the network, ambiguous labels, and could characterize reasons for potential confusion.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1055, "image_height": 794, "name": "grossmann-2022-conceptSplatters-teaser.png", "type": "image/png", "size": 1013977, "path": "Publication:grossmann-2022-conceptSplatters", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/grossmann-2022-conceptSplatters-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/grossmann-2022-conceptSplatters-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,projects", "repositum_presentation_id": null, "authors": [ 1366, 166, 1110 ], "doi": "10.1016/j.cag.2022.04.013", "issn": "1873-7684", "journal": "Computers and Graphics", "open_access": "yes", "pages": "12", "pages_from": "73", "pages_to": "84", "publisher": "Elsevier", "volume": "105", "research_areas": [ "InfoVis" ], "keywords": [ "Concept spaces", "Latent spaces", "Similarity maps", "Visual exploratory analysis" ], "weblinks": [ { "href": "https://www.sciencedirect.com/science/article/pii/S0097849322000656", "caption": "paper", "description": "Link to open access paper", "main_file": 1 }, { "href": "https://kontor.cg.tuwien.ac.at/ConceptSplatters/", "caption": "online demo", "description": null, "main_file": 1 } ], "files": [ { "description": "Detailed findings", "filetitle": "supplementary document", "main_file": false, "use_in_gallery": false, "access": "public", "name": "grossmann-2022-conceptSplatters-supplementary document.pdf", "type": "application/pdf", "size": 25193252, "path": "Publication:grossmann-2022-conceptSplatters", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/grossmann-2022-conceptSplatters-supplementary document.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/grossmann-2022-conceptSplatters-supplementary document:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1055, "image_height": 794, "name": "grossmann-2022-conceptSplatters-teaser.png", "type": "image/png", "size": 1013977, "path": "Publication:grossmann-2022-conceptSplatters", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/grossmann-2022-conceptSplatters-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/grossmann-2022-conceptSplatters-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "grossmann-2022-conceptSplatters-video.mp4", "type": "video/mp4", "size": 49841833, "path": "Publication:grossmann-2022-conceptSplatters", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/grossmann-2022-conceptSplatters-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/grossmann-2022-conceptSplatters-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/grossmann-2022-conceptSplatters-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/grossmann-2022-conceptSplatters/", "__class": "Publication" }, { "id": "lippeck-2022-mna", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "3D Graph Algorithm for Multilayer Network Analytics", "date": "2022-04", "abstract": "Simple graphs are often not able to accurately represent real world entities. Therefore, more complex data structures have been introduced, one of which is the so-called “multilayer network”. Multilayer networks are used in multiple fields, such as medical\nscience, where data can represent the correlation of diseases or social science, where data\nmight represent different actors and their relationship to one another.\n\nVisualizing these complex data types is particularly challenging, as two-dimensional\nvisualizations - the gold standard for graph visualizations - are often not good enough\nto gather deeper insight into the data, as big datasets quickly fill two-dimensional\nvisualizations with visual clutter. Therefore, this thesis introduces a new visualization\ntechnique for multilayer networks by extending existing 2d state-of-the-art methods with\na third dimensions.\n\nOur solution visualizes the layers as sub graphs on a two-dimensional plane, which are\npositioned around a sphere. To optimize the layout within the layer for multilayer networks,\nour solution calculates the position of individual nodes by considering connections\nwithin the same layer, as well as connections to other layers. To minimize visual clutter,\nedge bundling was implemented, additionally to a view, which restricts the visualization\nto nodes and edges of a single layer, as well as connections to nodes of other layers. Our\nresults show that our solution with the additional space due to the third dimension,\ncombined with an optimized layout, allows users to visualize larger networks and gather\nbetter insight into the data, compared to conventional two-dimensional", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 658, "image_height": 610, "name": "lippeck-2022-mna-teaser.PNG", "type": "image/png", "size": 291615, "path": "Publication:lippeck-2022-mna", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/lippeck-2022-mna/lippeck-2022-mna-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/lippeck-2022-mna/lippeck-2022-mna-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1926 ], "date_end": "2022-04", "date_start": "2021", "matrikelnr": "11776883", "supervisor": [ 1072, 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": { "1": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 658, "image_height": 610, "name": "lippeck-2022-mna-teaser.PNG", "type": "image/png", "size": 291615, "path": "Publication:lippeck-2022-mna", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/lippeck-2022-mna/lippeck-2022-mna-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/lippeck-2022-mna/lippeck-2022-mna-teaser:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "lippeck-2022-mna-thesis.pdf", "type": "application/pdf", "size": 4906915, "path": "Publication:lippeck-2022-mna", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/lippeck-2022-mna/lippeck-2022-mna-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/lippeck-2022-mna/lippeck-2022-mna-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/lippeck-2022-mna/", "__class": "Publication" }, { "id": "sietzen-2022-vacnnr", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/20099", "title": "Visual Analytics for Convolutional Neural Network Robustness", "date": "2022-04", "abstract": "Convolutional neural networks (CNNs) are a type of machine learning model that is\nwidely used for computer vision tasks. Despite their high performance, the robustness of\nCNNs is often weak. A model trained for image classification might misclassify an image\nwhen it is slightly rotated, blurred, or after a change in color saturation. Moreover, CNNs\nare vulnerable to so-called “adversarial attacks”, methods where analytically computed\nperturbations are generated which fool the classifier despite being imperceptible by\nhumans. Various training methods have been designed to increase robustness in CNNs.\n\nIn this thesis, we investigate CNN robustness with two approaches: First, we visualize\ndifferences between standard and robust training methods. For this, we use feature\nvisualization, a method to visualize the patterns which individual units of a CNN respond\nto. Subsequently, we present an interactive visual analytics application which lets the\nuser manipulate a 3d scene while simultaneously observing a CNN’s prediction, as\nwell as intermediate neuron activations. To be able to compare standard and robustly\ntrained models, the application allows simultaneously observing two models. To test\nthe usefulness of our application, we conducted five case studies with machine learning\nexperts. During these case studies and our own experiments, several novel insights about\nrobustly trained models were made, three of which we verified quantitatively. Despite its\nability to probe two high performing CNNs in real-time, our tool fully runs client-side\nin a standard web-browser and can be served as a static website, without requiring a\npowerful backend server", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "activations", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 420, "image_height": 437, "name": "sietzen-2022-vacnnr-activations.png", "type": "image/png", "size": 219337, "path": "Publication:sietzen-2022-vacnnr", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/sietzen-2022-vacnnr/sietzen-2022-vacnnr-activations.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/sietzen-2022-vacnnr/sietzen-2022-vacnnr-activations:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1373 ], "date_end": "2022-04", "date_start": "2019", "diploma_examina": "2022-05", "matrikelnr": "0372194", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/", "caption": "Computer Graphics Forum paper", "description": "Journal paper associated with the thesis", "main_file": 0 }, { "href": "http://perturber.stefansietzen.at/", "caption": "online playground", "description": "Online playground", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "activations", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 420, "image_height": 437, "name": "sietzen-2022-vacnnr-activations.png", "type": "image/png", "size": 219337, "path": "Publication:sietzen-2022-vacnnr", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/sietzen-2022-vacnnr/sietzen-2022-vacnnr-activations.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/sietzen-2022-vacnnr/sietzen-2022-vacnnr-activations:thumb{{size}}.png" }, { "description": null, "filetitle": "Master thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sietzen-2022-vacnnr-Master thesis.pdf", "type": "application/pdf", "size": 13007795, "path": "Publication:sietzen-2022-vacnnr", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/sietzen-2022-vacnnr/sietzen-2022-vacnnr-Master thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/sietzen-2022-vacnnr/sietzen-2022-vacnnr-Master thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sietzen-2022-vacnnr-poster.pdf", "type": "application/pdf", "size": 1572744, "path": "Publication:sietzen-2022-vacnnr", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/sietzen-2022-vacnnr/sietzen-2022-vacnnr-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/sietzen-2022-vacnnr/sietzen-2022-vacnnr-poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/sietzen-2022-vacnnr/", "__class": "Publication" }, { "id": "bayat-2022-mva", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/139147", "title": "Multi-faceted Visual Analysis of Inter-Observer Variability", "date": "2022", "abstract": "Despite the advancements in auto-segmentation tools, manual delineation is still necessary in the medical field. For example, tumor segmentation is a crucial step in cancer radiotherapy and is still widely performed by hand by experienced radiologists. However, the opinions of experienced radiologists might differ, for a multitude of reasons. In this work, we visualize the variability originating from multiple experts delineating medical scans of the same patient, known as inter-observer variability.The novelty of this work consists of capturing the process of segmenting a target object. The focus lies in gaining insight into the observer’s thought processes and reasoning strategies. To investigate these aspects of segmenting we conduct a data acquisitionwith novice users and experts, capturing their thoughts in a think-aloud protocol and their areas of attention by tracking their mouse-movement during the segmentation process. This data is visualized with our Multi Observer Looking Environment (MOLE).MOLE allows to gain deep insight into the observers’ segmentation process and enables to compare different segmentation outcomes and how these occurred. With our proposed visualization techniques we emphasize regions of uncertainty that need more attention when delineating. Additionally, relevant keywords are extracted from the think-aloud protocol and aligned with the positions in the segmentation, providing information about the thought process of an observer. We link the initial image to a three-dimensional representation of the delineations and provide more details of the think-aloud protocol on demand.Our approach is universal to segmentation, attention and thought process data regardless of the domain of the data. We show how MOLE can be used with a medical dataset as well as an artificially created dataset. By validating our approach with the help of a medical expert actively working in the field, we define potential use cases in the existing pipeline of tumor delineation for cancer treatment.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 783, "image_height": 536, "name": "bayat-2022-mva-teaser.jpg", "type": "image/jpeg", "size": 91325, "path": "Publication:bayat-2022-mva", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/bayat-2022-mva/bayat-2022-mva-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/bayat-2022-mva/bayat-2022-mva-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1693 ], "co_supervisor": [ 1410 ], "date_end": "2022-12", "date_start": "2022-03", "diploma_examina": "2023-01-16", "doi": "10.34726/hss.2022.105180", "matrikelnr": "01614855", "open_access": "yes", "pages": "145", "supervisor": [ 1110 ], "research_areas": [ "InfoVis", "MedVis" ], "keywords": [ "medical visualization", "uncertainty", "inter-observer variability", "data acquisition", "segmentation", "manual delineation" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Master thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "bayat-2022-mva-Master thesis.pdf", "type": "application/pdf", "size": 4821903, "path": "Publication:bayat-2022-mva", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/bayat-2022-mva/bayat-2022-mva-Master thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/bayat-2022-mva/bayat-2022-mva-Master thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 783, "image_height": 536, "name": "bayat-2022-mva-teaser.jpg", "type": "image/jpeg", "size": 91325, "path": "Publication:bayat-2022-mva", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/bayat-2022-mva/bayat-2022-mva-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/bayat-2022-mva/bayat-2022-mva-teaser:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/bayat-2022-mva/", "__class": "Publication" }, { "id": "louis-alexandre_dit_petit-frere-2022-veo", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/80545", "title": "Visual Exploration of Indirect Biases in Natural Language Processing Transformer Models", "date": "2022", "abstract": "In recent years, the importance of Natural Language Processing has been increasing with more and more fields of application. The word representations, such as word embedding or transformer models, used to transcribe the language are trained using large text corpora that may include stereotypes. These stereotypes may be learned by Natural Language Processing algorithms and lead to biases in their results. Extensive research has been performed on the detection, repair and visualization of the biases in the field of Natural Language Processing. Nevertheless, the methods developed so far mostly focus on word embeddings, or direct and binary biases.To fill the research gap regarding multi-class indirect biases learned by transformer models, this thesis proposes new visualisation interfaces to explore indirect and multi-class biases learned by BERT and XLNet models. These visualisations are based on an indirect quantitative method to measure the potential biases encapsulated in transformer models, the Indirect Logarithmic Probability Bias Score. This metric is adapted from an existing one, to enable the investigation of indirect biases. The evaluation of our new indirect method shows that it enables to reveal known biases and to discover new insights which could not be found using the direct method. Moreover, the user study performed on our visualization interfaces demonstrates that the visualizations supports the exploration of multi-class indirect biases, even though improvements may be needed to fully assist the investigation of the sources of the biases.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 959, "image_height": 253, "name": "louis-alexandre_dit_petit-frere-2022-veo-teaser.png", "type": "image/png", "size": 23473, "path": "Publication:louis-alexandre_dit_petit-frere-2022-veo", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/louis-alexandre_dit_petit-frere-2022-veo/louis-alexandre_dit_petit-frere-2022-veo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/louis-alexandre_dit_petit-frere-2022-veo/louis-alexandre_dit_petit-frere-2022-veo-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5211 ], "date_end": "2022-11", "date_start": "2022-01", "diploma_examina": "2022-11-21", "doi": "10.34726/hss.2022.99921", "matrikelnr": "12024728", "open_access": "yes", "pages": "134", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [ "visual exploration", "visual analytics", "natural language processing", "bias", "transformer models" ], "weblinks": [ { "href": "https://judith-la.github.io/IndirectBiasTransformerModels/Visualization1/Indirect_Biases_Exploration_Vis1.html", "caption": "Table View", "description": null, "main_file": 0 }, { "href": "https://judith-la.github.io/IndirectBiasTransformerModels/Visualization2/Indirect_Biases_Exploration_Vis2.html", "caption": "Scatterplot", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "Master thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "louis-alexandre_dit_petit-frere-2022-veo-Master thesis.pdf", "type": "application/pdf", "size": 3034845, "path": "Publication:louis-alexandre_dit_petit-frere-2022-veo", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/louis-alexandre_dit_petit-frere-2022-veo/louis-alexandre_dit_petit-frere-2022-veo-Master thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/louis-alexandre_dit_petit-frere-2022-veo/louis-alexandre_dit_petit-frere-2022-veo-Master thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 959, "image_height": 253, "name": "louis-alexandre_dit_petit-frere-2022-veo-teaser.png", "type": "image/png", "size": 23473, "path": "Publication:louis-alexandre_dit_petit-frere-2022-veo", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/louis-alexandre_dit_petit-frere-2022-veo/louis-alexandre_dit_petit-frere-2022-veo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/louis-alexandre_dit_petit-frere-2022-veo/louis-alexandre_dit_petit-frere-2022-veo-teaser:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/louis-alexandre_dit_petit-frere-2022-veo/", "__class": "Publication" }, { "id": "bhore-2021-issac", "type_id": "inproceedings", "tu_id": 299975, "repositum_id": "20.500.12708/55639", "title": "Untangling Circular Drawings: Algorithms and Complexity", "date": "2021-12", "abstract": "We consider the problem of untangling a given (non-planar) straight-line circular drawing δG of an\r\nouterplanar graph G = (V,E) into a planar straight-line circular drawing by shifting a minimum\r\nnumber of vertices to a new position on the circle. For an outerplanar graph G, it is clear that such\r\na crossing-free circular drawing always exists and we define the circular shifting number shift◦(δG)\r\nas the minimum number of vertices that need to be shifted to resolve all crossings of δG. We show\r\nthat the problem Circular Untangling, asking whether shift◦(δG) ≤ K for a given integer K,\r\nis NP-complete. Based on this result we study Circular Untangling for almost-planar circular\r\ndrawings, in which a single edge is involved in all the crossings. In this case we provide a tight upper\r\nbound shift◦(δG) ≤ ⌊n2\r\n⌋ − 1, where n is the number of vertices in G, and present a polynomial-time\r\nalgorithm to compute the circular shifting number of almost-planar drawings.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "date", "repositum_presentation_id": null, "authors": [ 1878, 1698, 1579, 1879, 1464 ], "booktitle": "Proceedings of the 32nd International Symposium on Algorithms and Computation", "cfp": { "name": "ISAAC 2021.pdf", "type": "application/pdf", "error": "0", "size": "66412", "orig_name": "ISAAC 2021.pdf", "ext": "pdf" }, "doi": "10.4230/LIPIcs.ISAAC.2021.19", "event": "The 32nd International Symposium on Algorithms and Computation", "lecturer": [ 1698 ], "pages": "17", "pages_from": "1", "pages_to": "17", "publisher": "LIPICS", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "bhore-2021-issac-paper.pdf", "type": "application/pdf", "size": 1149414, "path": "Publication:bhore-2021-issac", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/bhore-2021-issac/bhore-2021-issac-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/bhore-2021-issac/bhore-2021-issac-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/bhore-2021-issac/", "__class": "Publication" }, { "id": "bugnar-esk-2021", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Exploratory Search Interface for Knowledge Databases", "date": "2021-12", "abstract": "Visualization has always been a powerful tool to effectively convey knowledge and\ninformation. It has also gained attention in the context of search, in particular for newer\nvisualization techniques like “Multifaceted Search” and “Exploratory Search”. There are\ncurrently many tools and websites that still rely on an explicit search function or an\nalphabetically ordered glossary of terms to allow users to filter and browse resources.\nThis results in many useful resources not being discovered by users because of a lack of\nproper search tools. Exploratory Search is more open-ended, allowing users to search\neven if they do not exactly know what they are looking for.\n\nThis thesis proposes an adaptable, modular, web-based prototype of an exploratory\nsearch interface. The goal of the prototype is to serve as a basis for the evaluation of\nexploratory search interfaces for a wide variety of use cases. In contrast to many existing\nExploratory Search tools, this prototype does not require rich meta-data to be present\nin a dataset. By utilizing an optional preprocessing step to extract named entities via\nNatural Language Processing, the prototype is compatible with most text-based datasets.\nThe search interface consists of a word cloud created by a force-directed layout algorithm\nthat places related entities close to each other. This interface also serves as the main\nfiltering option, which keeps the users’ focus on the word cloud. After selecting interesting\nentities, matching documents can be browsed in a list view.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 823, "image_height": 271, "name": "bugnar-esk-2021-teaser.PNG", "type": "image/png", "size": 111932, "path": "Publication:bugnar-esk-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/bugnar-esk-2021/bugnar-esk-2021-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/bugnar-esk-2021/bugnar-esk-2021-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1761 ], "date_end": "2021-12", "date_start": "2020-04", "matrikelnr": "01402617", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 823, "image_height": 271, "name": "bugnar-esk-2021-teaser.PNG", "type": "image/png", "size": 111932, "path": "Publication:bugnar-esk-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/bugnar-esk-2021/bugnar-esk-2021-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/bugnar-esk-2021/bugnar-esk-2021-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "bugnar-esk-2021-thesis.pdf", "type": "application/pdf", "size": 5892838, "path": "Publication:bugnar-esk-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/bugnar-esk-2021/bugnar-esk-2021-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/bugnar-esk-2021/bugnar-esk-2021-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/bugnar-esk-2021/", "__class": "Publication" }, { "id": "sbardellati-2021-eveos", "type_id": "masterthesis", "tu_id": 300124, "repositum_id": "20.500.12708/18678", "title": "Exploratory Visual System for Predictive Machine Learning of Event-Organisation Data", "date": "2021-11", "abstract": "In recent years, the usage of machine learning (ML) models and especially deep neural\nnetworks in many different domains has increased rapidly. One of the major challenges\nwhen working with ML models is to correctly and efficiently interpret the results given\nby a model. Additionally, understanding how the model came to its conclusions can be\na very complicated task even for domain experts in the field of machine learning. For\nlaypeople, ML models are often just black-boxes. The lack of understanding of a model\nand its reasoning often leads to users not trusting the model’s predictions.\n\nIn this thesis, we work with an ML model trained on event-organisation data. The\ngoal is to create an exploratory visual event-organisation system that enables event\norganisers to efficiently work with the model. The main user goals in this scenario are\nto maximise profits and to be able to prepare for the predicted number of visitors. To\nachieve these goals users need to be able to perform tasks like: interpreting the prediction\nof the current input and performing what-if analyses to understand the effects of\nchanging parameters. The proposed system incorporates adapted versions of multiple\nstate-of-the-art model-agnostic interpretation methods like partial dependence plots and\ncase-based reasoning. Since model-agnostic methods are independent of the ML model,\nthey provide high flexibility.\n\nMany state-of-the-art approaches to explain ML models are too complex to be understood\nby laypeople. Our target group of event organisers cannot be expected to have a sufficient\namount of technical knowledge in the field of machine learning. In this thesis, we want\nto find answers to the questions: How can we visualise ML predictions to laypeople in a\ncomprehensible way? How can predictions be compared against each other? How can\nwe support users in gaining trust in the ML model? Our event-organisation system is\ncreated using a human-centred design approach performing multiple case studies with\npotential users during the whole development circle.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 967, "image_height": 1079, "name": "sbardellati-2021-eveos-teaser.PNG", "type": "image/png", "size": 146317, "path": "Publication:sbardellati-2021-eveos", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sbardellati-2021-eveos/sbardellati-2021-eveos-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sbardellati-2021-eveos/sbardellati-2021-eveos-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1555 ], "co_supervisor": [ 166 ], "date_end": "2021-11", "date_start": "2020-11", "diploma_examina": "2021-11-15", "doi": "10.34726/hss.2021.85640", "matrikelnr": "01526262", "open_access": "yes", "pages": "110", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [ "machine learning", "interactive visualisation" ], "weblinks": [], "files": { "1": { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sbardellati-2021-eveos-poster.pdf", "type": "application/pdf", "size": 1867611, "path": "Publication:sbardellati-2021-eveos", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sbardellati-2021-eveos/sbardellati-2021-eveos-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sbardellati-2021-eveos/sbardellati-2021-eveos-poster:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 967, "image_height": 1079, "name": "sbardellati-2021-eveos-teaser.PNG", "type": "image/png", "size": 146317, "path": "Publication:sbardellati-2021-eveos", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sbardellati-2021-eveos/sbardellati-2021-eveos-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sbardellati-2021-eveos/sbardellati-2021-eveos-teaser:thumb{{size}}.png" }, "3": { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sbardellati-2021-eveos-thesis.pdf", "type": "application/pdf", "size": 9660724, "path": "Publication:sbardellati-2021-eveos", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sbardellati-2021-eveos/sbardellati-2021-eveos-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sbardellati-2021-eveos/sbardellati-2021-eveos-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sbardellati-2021-eveos/", "__class": "Publication" }, { "id": "Groeller_2021-10", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "Interactive Visual Data Analysis", "date": "2021-10-21", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 166 ], "event": "ICSTCC 2021 - 25th International Conference on System Theory, Control and Computing", "location": "Iasi, Romania", "open_access": "no", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://icstcc2021.ac.tuiasi.ro/", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Groeller_2021-10/", "__class": "Publication" }, { "id": "Priselac2021", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/18845", "title": "Visual Analytics of Spatial Time Series Data", "date": "2021-10-12", "abstract": "Regardless of what algorithms and technologies are developed, the human mind and logical reasoning remain important tools for analysing, modelling, and solving problems. Visual representation of data is considered the most e˙ective way to convey information to the human brain and promote analytical thinking. Visual analytics encompasses a set of techniques, methods, and tools that support analytical thinking through visual representations of various types of data. Due to their complexity and size, spatial time series data are suitable for implementation of such techniques, as their analysis remains challenging. Many environmental, social, and economic processes of modern civilization are represented by spatial time series, which emphasises the need for interactive visual representations for their more eÿcient analysis.\nOne clear example of such complex processes is economic recession, a decline in economic activity for which there is no single formal definition. However, it is often described in terms of recession factors such as GDP, the Gini index, or inflation, all of which are examples of spatial time series data, and whose change can be a clear indicator of the state of the economy. As recession analysis is a very complex topic and it is not entirely clear which economic factors have the greatest impact, purely automated techniques are not appropriate and there is scope for advances in analytical approaches.\nThis thesis proposes an application “Recession Explorer”: visual analytics of economic recession and its forecasting as an example of a holistic system that displays spatial time series data and explores patterns and insights in the data. Such a combination of approaches provides a unique perspective on economic recession studies by facilitating both high-level human reasoning and the use of advanced mathematical algorithms. The goal of the application is to demonstrate that the use of visual analytics is a beneficial approach to address the challenges of economic recession and, more generally, to assist users with interactive visualisations when dealing with and analysing spatial time series data.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 849, "image_height": 306, "name": "Priselac2021-image.JPG", "type": "image/jpeg", "size": 43088, "path": "Publication:Priselac2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Priselac2021/Priselac2021-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Priselac2021/Priselac2021-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1868 ], "date_end": "2021-10-12", "date_start": "2021-01-05", "diploma_examina": "2021-10-12", "doi": "10.34726/hss.2021.73924", "matrikelnr": "11735131", "open_access": "yes", "pages": "60", "supervisor": [ 235 ], "research_areas": [ "InfoVis" ], "keywords": [ "visual analytics", "interactive visual analysis", "machine learning", "linear regression", "elastic net", "K-Means", "classification", "spatial time series", "economic recession", "recession factors" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 849, "image_height": 306, "name": "Priselac2021-image.JPG", "type": "image/jpeg", "size": 43088, "path": "Publication:Priselac2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Priselac2021/Priselac2021-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Priselac2021/Priselac2021-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Priselac2021-Master Thesis.pdf", "type": "application/pdf", "size": 12953562, "path": "Publication:Priselac2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Priselac2021/Priselac2021-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Priselac2021/Priselac2021-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Priselac2021-Poster.pdf", "type": "application/pdf", "size": 1308445, "path": "Publication:Priselac2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Priselac2021/Priselac2021-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Priselac2021/Priselac2021-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Priselac2021/", "__class": "Publication" }, { "id": "Heim_2021", "type_id": "journalpaper_notalk", "tu_id": 300188, "repositum_id": "20.500.12708/138542", "title": "CoSi: Visual Comparison of Similarities in High-Dimensional Data Ensembles", "date": "2021-10-10", "abstract": "Comparative analysis of multivariate datasets, e.g. of advanced materials regarding the characteristics of internal structures (fibers, pores, etc.), is of crucial importance in various scientific disciplines. Currently domain experts in materials science mostly rely on sequential comparison of data using juxtaposition. Our work assists domain experts to perform detailed comparative analyses of large ensemble data in materials science applications. For this purpose, we developed a comparative visualization framework, that includes a tabular overview and three detailed visualization techniques to provide a holistic view on the similarities in the ensemble. We demonstrate the applicability of our framework on two specific usage scenarios and verify its techniques using a qualitative user study with 12 material experts. The insights gained from our work represent a significant advancement in the field of comparative material analysis of high-dimensional data. Our framework provides experts with a novel perspective on the data and eliminates the need for time-consuming sequential exploration of numerical data.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 765, "image_height": 399, "name": "Heim_2021-Image.JPG", "type": "image/jpeg", "size": 69697, "path": "Publication:Heim_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heim_2021/Heim_2021-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heim_2021/Heim_2021-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1354, 166, 611 ], "doi": "CoSi: Visual Comparison of Similarities in High-Dimensional Data Ensembles", "first_published": "2021-10-10", "journal": "VMV: Vision, Modeling, and Visualization", "open_access": "yes", "pages_from": "1", "pages_to": "8", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 765, "image_height": 399, "name": "Heim_2021-Image.JPG", "type": "image/jpeg", "size": 69697, "path": "Publication:Heim_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heim_2021/Heim_2021-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heim_2021/Heim_2021-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Heim_2021-Paper.pdf", "type": "application/pdf", "size": 926914, "path": "Publication:Heim_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heim_2021/Heim_2021-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heim_2021/Heim_2021-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heim_2021/", "__class": "Publication" }, { "id": "grossmann-2021-layout", "type_id": "inproceedings", "tu_id": 300287, "repositum_id": "20.500.12708/58620", "title": "Does the Layout Really Matter? A Study on Visual Model Accuracy Estimation", "date": "2021-10", "abstract": "In visual interactive labeling, users iteratively assign labels to data items until the machine model reaches an acceptable accuracy. A crucial step of this process is to inspect the model's accuracy and decide whether it is necessary to label additional elements. In scenarios with no or very little labeled data, visual inspection of the predictions is required. Similarity-preserving scatterplots created through a dimensionality reduction algorithm are a common visualization that is used in these cases. Previous studies investigated the effects of layout and image complexity on tasks like labeling. However, model evaluation has not been studied systematically. We present the results of an experiment studying the influence of image complexity and visual grouping of images on model accuracy estimation. We found that users outperform traditional automated approaches when estimating a model's accuracy. Furthermore, while the complexity of images impacts the overall performance, the layout of the items in the plot has little to no effect on estimations.", "authors_et_al": false, "substitute": null, "main_image": { "description": "In both scatterplots shown here, the percentage of images with correctly predicted class labels (visualized as border color) is over 90%. We found that users can estimate these accuracies fairly well. Image complexity impacts overall performance, but the layout has very little effect on users’ estimations. ", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 3287, "image_height": 1817, "name": "grossmann-2021-layout-teaser.png", "type": "image/png", "size": 879037, "path": "Publication:grossmann-2021-layout", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1366, 1851, 1690, 1110 ], "booktitle": "IEEE Visualization Conference (VIS)", "cfp": { "name": "Short Paper Call for Participation.pdf", "type": "application/pdf", "error": "0", "size": "180486", "orig_name": "Short Paper Call for Participation.pdf", "ext": "pdf" }, "doi": "10.1109/VIS49827.2021.9623326", "event": "IEEE Visualization Conference (VIS)", "lecturer": [ 1110 ], "open_access": "yes", "pages": "5", "pages_from": "61", "pages_to": "65", "publisher": "IEEE Computer Society Press", "research_areas": [ "InfoVis", "Perception" ], "keywords": [], "weblinks": [ { "href": "https://arxiv.org/pdf/2110.07188.pdf", "caption": "arxiv", "description": "Link to arxiv version of the paper", "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "grossmann-2021-layout-paper.pdf", "type": "application/pdf", "size": 1951149, "path": "Publication:grossmann-2021-layout", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-paper:thumb{{size}}.png" }, { "description": "Pre-recorded presentation for VIS 2021", "filetitle": "presentation", "main_file": false, "use_in_gallery": false, "access": "public", "name": "grossmann-2021-layout-presentation.mp4", "type": "video/mp4", "size": 28816734, "path": "Publication:grossmann-2021-layout", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-presentation.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-presentation:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-presentation:video.mp4" }, { "description": "Fast-forward preview video", "filetitle": "preview", "main_file": false, "use_in_gallery": false, "access": "public", "name": "grossmann-2021-layout-preview.mp4", "type": "video/mp4", "size": 5736268, "path": "Publication:grossmann-2021-layout", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-preview.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-preview:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-preview:video.mp4" }, { "description": "Supplementary document showing study conditions and interface", "filetitle": "supplement", "main_file": false, "use_in_gallery": false, "access": "public", "name": "grossmann-2021-layout-supplement.pdf", "type": "application/pdf", "size": 44940660, "path": "Publication:grossmann-2021-layout", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-supplement.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-supplement:thumb{{size}}.png" }, { "description": "In both scatterplots shown here, the percentage of images with correctly predicted class labels (visualized as border color) is over 90%. We found that users can estimate these accuracies fairly well. Image complexity impacts overall performance, but the layout has very little effect on users’ estimations. ", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 3287, "image_height": 1817, "name": "grossmann-2021-layout-teaser.png", "type": "image/png", "size": 879037, "path": "Publication:grossmann-2021-layout", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/grossmann-2021-layout-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/grossmann-2021-layout/", "__class": "Publication" }, { "id": "sietzen-2021-perturber", "type_id": "journalpaper", "tu_id": 300245, "repositum_id": "20.500.12708/55628", "title": "Interactive Analysis of CNN Robustness", "date": "2021-10", "abstract": "While convolutional neural networks (CNNs) have found wide adoption as state-of-the-art models for image-related tasks, their predictions are often highly sensitive to small input perturbations, which the human vision is robust against.\nThis paper presents Perturber, a web-based application that allows users to instantaneously explore how CNN activations and predictions evolve when a 3D input scene is interactively perturbed. Perturber offers a large variety of scene modifications, such as camera controls, lighting and shading effects, background modifications, object morphing, as well as adversarial attacks, to facilitate the discovery of potential vulnerabilities. Fine-tuned model versions can be directly compared for qualitative evaluation of their robustness. Case studies with machine learning experts have shown that Perturber helps users to quickly generate hypotheses about model vulnerabilities and to qualitatively compare model behavior. Using quantitative analyses, we could replicate users' insights with other CNN architectures and input images, yielding new insights about the vulnerability of adversarially trained models. ", "authors_et_al": false, "substitute": null, "main_image": { "description": "Activations and feature visualizations for neurons associated with complex shapes and curvatures in layer mixed4a in the standard model. Note how rotating the input model causes activation changes for oriented shape detectors. ", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1423, "image_height": 736, "name": "sietzen-2021-perturber-teaser.png", "type": "image/png", "size": 1235572, "path": "Publication:sietzen-2021-perturber", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1373, 1852, 1853, 1854, 1110 ], "cfp": { "name": "Call for Papers _ Pacific Graphics 2021.pdf", "type": "application/pdf", "error": "0", "size": "246798", "orig_name": "Call for Papers _ Pacific Graphics 2021.pdf", "ext": "pdf" }, "date_from": "2021-10-18", "date_to": "2021-10-21", "doi": "10.1111/cgf.14418", "event": "Pacific Graphics 2021", "journal": "Computer Graphics Forum", "lecturer": [ 1373 ], "open_access": "yes", "pages": "12", "pages_from": "253", "pages_to": "264", "publisher": "John Wiley and Sons", "volume": "40", "research_areas": [ "InfoVis" ], "keywords": [ "Computer Graphics and Computer-Aided Design" ], "weblinks": [ { "href": "http://perturber.stefansietzen.at/", "caption": "online tool", "description": "Perturber online tool for interactive analysis of CNN robustness", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sietzen-2021-perturber-paper.pdf", "type": "application/pdf", "size": 10858795, "path": "Publication:sietzen-2021-perturber", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-paper:thumb{{size}}.png" }, { "description": "Additional use cases and detailed reports from the case study", "filetitle": "supplementary document ", "main_file": false, "use_in_gallery": false, "access": "public", "name": "sietzen-2021-perturber-supplementary document .pdf", "type": "application/pdf", "size": 24700068, "path": "Publication:sietzen-2021-perturber", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-supplementary document .pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-supplementary document :thumb{{size}}.png" }, { "description": "Activations and feature visualizations for neurons associated with complex shapes and curvatures in layer mixed4a in the standard model. Note how rotating the input model causes activation changes for oriented shape detectors. ", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1423, "image_height": 736, "name": "sietzen-2021-perturber-teaser.png", "type": "image/png", "size": 1235572, "path": "Publication:sietzen-2021-perturber", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sietzen-2021-perturber-video.mp4", "type": "video/mp4", "size": 215752131, "path": "Publication:sietzen-2021-perturber", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/sietzen-2021-perturber-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sietzen-2021-perturber/", "__class": "Publication" }, { "id": "sorger-2021-egonet", "type_id": "journalpaper", "tu_id": 300416, "repositum_id": "20.500.12708/58630", "title": "Egocentric Network Exploration for Immersive Analytics", "date": "2021-10", "abstract": "To exploit the potential of immersive network analytics for engaging and effective exploration, we promote the metaphor of ``egocentrism'', where data depiction and interaction are adapted to the perspective of the user within a 3D network. Egocentrism has the potential to overcome some of the inherent downsides of virtual environments, e.g., visual clutter and cyber-sickness. To investigate the effect of this metaphor on immersive network exploration, we designed and evaluated interfaces of varying degrees of egocentrism. In a user study, we evaluated the effect of these interfaces on visual search tasks, efficiency of network traversal, spatial orientation, as well as cyber-sickness. Results show that a simple egocentric interface considerably improves visual search efficiency and navigation performance, yet does not decrease spatial orientation or increase cyber-sickness. A distorted occlusion-free view of the neighborhood only marginally improves the user's performance. We tie our findings together in an open online tool for egocentric network exploration, providing actionable insights on the benefits of the egocentric network exploration metaphor.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2921, "image_height": 735, "name": "sorger-2021-egonet-teaser.png", "type": "image/png", "size": 2079618, "path": "Publication:sorger-2021-egonet", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/sorger-2021-egonet-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/sorger-2021-egonet-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1072, 1705, 1720, 853, 1110 ], "cfp": { "name": "Call for Papers _ Pacific Graphics 2021.pdf", "type": "application/pdf", "error": "0", "size": "246798", "orig_name": "Call for Papers _ Pacific Graphics 2021.pdf", "ext": "pdf" }, "date_from": "2021-10-18", "date_to": "2021-10-21", "doi": "10.1111/cgf.14417", "event": "Pacific Graphics 21", "journal": "Computer Graphics Forum", "lecturer": [ 1072 ], "location": "Wellington, NZ", "open_access": "no", "pages": "12", "pages_from": "241", "pages_to": "252", "publisher": "John Wiley and Sons", "volume": "40", "research_areas": [ "InfoVis", "NetVis", "VR" ], "keywords": [ "Computer Graphics and Computer-Aided Design" ], "weblinks": [ { "href": "https://vis.csh.ac.at/egocentricvr/", "caption": "online egocentric network", "description": "Online tool for egocentric network exploration leveraging insights gathered at the user study", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2921, "image_height": 735, "name": "sorger-2021-egonet-teaser.png", "type": "image/png", "size": 2079618, "path": "Publication:sorger-2021-egonet", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/sorger-2021-egonet-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/sorger-2021-egonet-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "the paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sorger-2021-egonet-the paper.pdf", "type": "application/pdf", "size": 4211458, "path": "Publication:sorger-2021-egonet", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/sorger-2021-egonet-the paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/sorger-2021-egonet-the paper:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sorger-2021-egonet-video.mp4", "type": "video/mp4", "size": 295211748, "path": "Publication:sorger-2021-egonet", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/sorger-2021-egonet-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/sorger-2021-egonet-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/sorger-2021-egonet-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/sorger-2021-egonet/", "__class": "Publication" }, { "id": "stoff-concepMap-2021", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Concept Map Mining as Browser Extension", "date": "2021-10", "abstract": "Concept maps are a well-known method of structured representation of knowledge. They\nare represented as a node-link diagram that showcases different concepts and their\nrelations to each other, which are often extracted from unstructured text. Manual\ngeneration of such concept maps can be a tedious task, but fully automated approaches\nare often not able to satisfy qualitative expectations. Semi-automated methods have\nshown to be a satisfying compromise between these two. It is especially important that\nthe manual aspect of creating a concept map is as intuitive and easy as possible so that\nthe user’s workflow is not interrupted, and tasks can be completed efficiently. Therefore,\nit is the graphical user interface that plays a critical role in guaranteeing a satisfying\nexperience and swift completion of tasks.\n\nIt is therefore the aim of this thesis to create an environment, in which users are able\nto extract meaningful concepts from arbitrary websites and connect these concepts to\nexisting knowledge structures. In other words, it should visually convey how new, unseen\ninformation fits to the knowledge they already have. For this purpose, an extension to\nthe Google Chrome browser is presented in this thesis, that allows the user to analyze\nthe text on any website on the internet with a provided natural language processing\nsoftware. Concepts and relations can then be highlighted in the original text to visualize\ntheir connection to existing knowledge. At the user’s choice, new concepts, relations, and\ncombinations of the two can be added to existing concept maps. These concept maps\ncan be automatically visualized as a node-link diagram.\n\nWith the help of a small user evaluation, we conclude that the approach has definite\npotential but still lacks the reliability, especially with the automatic text processing and\nconcept extraction, for real-world use-cases.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 892, "image_height": 317, "name": "stoff-concepMap-2021-teaser.PNG", "type": "image/png", "size": 140973, "path": "Publication:stoff-concepMap-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/stoff-concepMap-2021/stoff-concepMap-2021-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/stoff-concepMap-2021/stoff-concepMap-2021-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1865 ], "date_end": "2021-10", "date_start": "2021-04", "matrikelnr": "11777706", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://github.com/Valcaad/bacConceptMaps", "caption": "GitHub", "description": "Code for the Browser Extension", "main_file": 0 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 892, "image_height": 317, "name": "stoff-concepMap-2021-teaser.PNG", "type": "image/png", "size": 140973, "path": "Publication:stoff-concepMap-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/stoff-concepMap-2021/stoff-concepMap-2021-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/stoff-concepMap-2021/stoff-concepMap-2021-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "stoff-concepMap-2021-thesis.pdf", "type": "application/pdf", "size": 4423850, "path": "Publication:stoff-concepMap-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/stoff-concepMap-2021/stoff-concepMap-2021-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/stoff-concepMap-2021/stoff-concepMap-2021-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/stoff-concepMap-2021/", "__class": "Publication" }, { "id": "Kolter_2021", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Creating an Interactive Web App for Computer Graphics Topics", "date": "2021-09-28", "abstract": "Computer Graphics is, as the name suggests, a subdomain of Computer Science with strong relation to visuals. Often a lot of complex math is necessary to make a computer render a visual representation of something onto the screen. However, in many cases the algorithms used can also be explained nicely in a very visual manner. The goal of this Bachelor’s Thesis was to find novel ways to introduce people interested in Computer Graphics to selected topics, mainly focusing on Bézier Curves and their generalizations (B-Spline and NURBS curves). To reach this goal, interactive web-based demos that can be viewed with any state-of-the-art browser were created.\nRelated existing work is presented (publications on approaches to teaching Computer Graphics and existing teaching material, as well as learning resources/demos that were found online). The ways in which the collected knowledge was used when implementing the demos are described as well as key decisions that had to be made for the concrete implementation of the web app. Important implementation details are discussed, too. Finally, an overview of the lessons learnt over the course of the whole project is given.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1856 ], "date_end": "2021-09-30", "date_start": "2021-03-10", "matrikelnr": "11810909", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Kolter_2021-Bachelor thesis.pdf", "type": "application/pdf", "size": 431252, "path": "Publication:Kolter_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Kolter_2021/Kolter_2021-Bachelor thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Kolter_2021/Kolter_2021-Bachelor thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Kolter_2021/", "__class": "Publication" }, { "id": "batik-2021-gd", "type_id": "poster", "tu_id": 300510, "repositum_id": "20.500.12708/55642", "title": "Mixed Metro Maps with User-Specied Motifs", "date": "2021-09", "abstract": "In this poster, we propose an approach to generalize mixed metro map layouts with user-defined shapes for route-finding and ad-vertisement purposes. In a mixed layout, specific lines are arranged in an iconic shape, and the remaining are in octilinear styles. The shape is expected to be recognizable, while the layout still fulfilling the classical octilinear design criteria for metro maps. The approach is in three steps, where we first search for the best fitting edge segment that approximates the guide shape and utilize least squares optimization to synthesize the layout automatically.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1637, "image_height": 1030, "name": "batik-2021-gd-image.png", "type": "image/png", "size": 116119, "path": "Publication:batik-2021-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/batik-2021-gd/batik-2021-gd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/batik-2021-gd/batik-2021-gd-image:thumb{{size}}.png" }, "sync_repositum_override": "date,authors", "repositum_presentation_id": null, "authors": [ 1830, 1699, 1579, 1877, 1464 ], "cfp": { "name": "cfp2-gd2021.pdf", "type": "application/pdf", "error": "0", "size": "90251", "orig_name": "cfp2-gd2021.pdf", "ext": "pdf" }, "date_from": "2021-09-14", "date_to": "2021-09-17", "event": "29th International Symposium on Graph Drawing and Network Visualization", "location": "Tübingen", "pages": "4", "pages_from": "1", "pages_to": "4", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1637, "image_height": 1030, "name": "batik-2021-gd-image.png", "type": "image/png", "size": 116119, "path": "Publication:batik-2021-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/batik-2021-gd/batik-2021-gd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/batik-2021-gd/batik-2021-gd-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "batik-2021-gd-paper.pdf", "type": "application/pdf", "size": 1561630, "path": "Publication:batik-2021-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/batik-2021-gd/batik-2021-gd-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/batik-2021-gd/batik-2021-gd-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/batik-2021-gd/", "__class": "Publication" }, { "id": "musleh_maath_2021_mam", "type_id": "poster", "tu_id": 300507, "repositum_id": "20.500.12708/58636", "title": "Agritology: A Decision Support System for Local Farmers in Malta and Palestine", "date": "2021-09", "abstract": " In this project, we are utilizing the potential of Semantic Web in organizing shareable knowledge. We constructed an ontology of the farming process that is reusable and interoperable in the domain of Agriculture. The ontology supports the decision making of farmers in Malta and Palestine. The web application uses the ontology to share knowledge based primarily on user input and other external data sources. In addition to English, information is also presented in Maltese and Arabic in aim to preserve domain-specific vocabulary in these languages.", "authors_et_al": false, "substitute": null, "main_image": { "description": "GUI of the Solution", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 847, "image_height": 784, "name": "musleh_maath_2021_mam-image.png", "type": "image/png", "size": 188463, "path": "Publication:musleh_maath_2021_mam", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath_2021_mam/musleh_maath_2021_mam-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath_2021_mam/musleh_maath_2021_mam-image:thumb{{size}}.png" }, "sync_repositum_override": "date", "repositum_presentation_id": null, "authors": [ 5215, 1867 ], "cfp": { "name": "3rd International Workshop on Semantics for Biodiversity.pdf", "type": "application/pdf", "error": "0", "size": "141009", "orig_name": "3rd International Workshop on Semantics for Biodiversity.pdf", "ext": "pdf" }, "date_from": "2021-09-11", "date_to": "2021-09-18", "event": "3rd International Workshop on Semantics for Biodiversity (S4BioDiv)", "journal": "CEUR Workshop Proceedings ", "location": "Bolzano, Italy", "open_access": "yes", "pages": "5", "pages_from": "1", "pages_to": "5", "research_areas": [ "InfoVis" ], "keywords": [ "Semantic Web", "Urban Agriculture", "Ontology" ], "weblinks": [ { "href": "http://ceur-ws.org/Vol-2969/paper3-s4biodiv.pdf", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": "GUI of the Solution", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 847, "image_height": 784, "name": "musleh_maath_2021_mam-image.png", "type": "image/png", "size": 188463, "path": "Publication:musleh_maath_2021_mam", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath_2021_mam/musleh_maath_2021_mam-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath_2021_mam/musleh_maath_2021_mam-image:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath_2021_mam/", "__class": "Publication" }, { "id": "musleh_maath-2021-mam1", "type_id": "inproceedings", "tu_id": 300419, "repositum_id": "20.500.12708/55641", "title": "Visual Analysis of Industrial Multivariate Time Series", "date": "2021-09", "abstract": "The recent development in the data analytics field provides a boost in production for modern industries. Small-sized factories intend to take full advantage of the data collected by sensors used in their machinery. The ultimate goal is to minimize cost and maximize quality, resulting in an increase in profit. In collaboration with domain experts, we implemented a data visualization tool to enable decision-makers in a plastic factory to improve their production process. We investigate three different aspects: methods for preprocessing multivariate time series data, clustering approaches for the already refined data, and visualization techniques that aid domain experts in gaining insights into the different stages of the production process. Here we present our ongoing results grounded in a human-centered development process. We adopt a formative evaluation approach to continuously upgrade our dashboard design that eventually meets partners' requirements and follows the best practices within the field.", "authors_et_al": false, "substitute": null, "main_image": { "description": "GUI of the Solution", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 916, "image_height": 621, "name": "musleh_maath-2021-mam1-image.png", "type": "image/png", "size": 369431, "path": "Publication:musleh_maath-2021-mam1", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam1/musleh_maath-2021-mam1-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam1/musleh_maath-2021-mam1-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1867, 5213, 5214 ], "address": "New York, NY, USA", "booktitle": "The 14th International Symposium on Visual Information Communication and Interaction", "cfp": { "name": "Submissions - VINCI 2021.pdf", "type": "application/pdf", "error": "0", "size": "2566211", "orig_name": "Submissions - VINCI 2021.pdf", "ext": "pdf" }, "date_from": "2021-09-06", "date_to": "2021-09-08", "doi": "10.1145/3481549.3481557", "editor": "Karsten Klein, Michael Burch, Daniel Limberger, Matthias Trapp", "event": "VINCI 2021: The 14th International Symposium on Visual Information Communication and Interaction", "first_published": "2021-09", "isbn": "9781450386470", "lecturer": [ 1867 ], "location": "Potsdam, germany", "note": "Best Short Paper Award", "open_access": "no", "pages": "5", "pages_from": "1", "pages_to": "5", "publisher": "Association for Computing Machinery", "series": "VINCI 2021", "research_areas": [ "InfoVis" ], "keywords": [ "time series data", "unsupervised machine learning", "visualization" ], "weblinks": [ { "href": "https://dl.acm.org/doi/10.1145/3481549.3481557", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": "GUI of the Solution", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 916, "image_height": 621, "name": "musleh_maath-2021-mam1-image.png", "type": "image/png", "size": 369431, "path": "Publication:musleh_maath-2021-mam1", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam1/musleh_maath-2021-mam1-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam1/musleh_maath-2021-mam1-image:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam1/", "__class": "Publication" }, { "id": "Nowak_2021", "type_id": "masterthesis", "tu_id": 300512, "repositum_id": "20.500.12708/79755", "title": "Interactive Correlation Panels for the Geological Mapping of the Martian Surface", "date": "2021-08-09", "abstract": "In recent years, digital outcrop models have become a popular tool to carry out geological investigations on the computer. These high-resolution, 3-dimensional models of outcrops are also created for the exploration of Mars. With specialized software, geologists can annotate geological attributes on digital outcrop models, such as the boundaries between di˙erent rock layers. After annotating, geologists create logs, a graphic description of the rock layers. To establish a geological model of a larger region, corresponding layers are correlated in multiple logs. The correlated layers of the logs are graphically linked in a correlation panel. Creating correlation panels is very time-consuming, and they are usually created by hand with drawing programs. Due to this restriction, the diagrams are created at the end of the interpretation process to avoid time-consuming editing afterwards. When switching to a drawing program, the connection between the original data and the encoded data in the diagram is also lost. This work is part of a design study with the aim of automating the creation of correlation panels, and turning a static illustration into an interactive application that can be integrated into the interpretation process. In this work, after a short introduction to the exploration of Mars with the help of geology, we analyse published correlation panels to explore the design space of these illustrations. In addition to that analysis we conducted workshops and a research stay at Imperial College London with our domain collaborators. Using the information gained from the analysis and our collaborators, we describe possible design choices, and extract the minimum requirements for a prototype. The prototype created in the course of this work was later extended and presented in a paper that encompasses the whole design study.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 678, "image_height": 348, "name": "Nowak_2021-image.JPG", "type": "image/jpeg", "size": 47583, "path": "Publication:Nowak_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Nowak_2021/Nowak_2021-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Nowak_2021/Nowak_2021-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1817 ], "date_end": "2021-08-09", "date_start": "2019-10-09", "diploma_examina": "2021-08-09", "matrikelnr": "00626227", "open_access": "yes", "pages": "133", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "visual analytics", "2D-3D integration" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 678, "image_height": 348, "name": "Nowak_2021-image.JPG", "type": "image/jpeg", "size": 47583, "path": "Publication:Nowak_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Nowak_2021/Nowak_2021-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Nowak_2021/Nowak_2021-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Nowak_2021-Master Thesis.pdf", "type": "application/pdf", "size": 3965095, "path": "Publication:Nowak_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Nowak_2021/Nowak_2021-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Nowak_2021/Nowak_2021-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Nowak_2021-Poster.pdf", "type": "application/pdf", "size": 1682015, "path": "Publication:Nowak_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Nowak_2021/Nowak_2021-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Nowak_2021/Nowak_2021-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Nowak_2021/", "__class": "Publication" }, { "id": "Heinzl2021", "type_id": "habilthesis", "tu_id": null, "repositum_id": null, "title": "Visualization and Analysis of X-ray Computed Tomography Data", "date": "2021-07-16", "abstract": "Visualization and analysis of primary and secondary X-ray computed tomography (XCT) data has become highly attractive for boosting research endeavors in the materials science domain. On the one hand, XCT allows to generate detailed and cumulative data of the specimens under investigation\nin a non-destructive way. On the other hand, through the conception, the development, and the implementation of novel, tailored analysis and visualization techniques, in-depth investigations of complex material systems turned into reality, e.g., in the form of interactive visualization of\nspatial and quantitative data, uncertainty quantification and visualization, comparative visualization, ensemble analysis and visualization, visual parameter space analysis, and many others.\nVisual analysis of XCT data enables a detailed understanding of the internal structures and the characteristics of materials and thus facilitates studies on a multitude of phenomena, at multiple scales, in different dimensions, or even using different modalities. This was simply impossible\nbefore. This habilitation thesis presents contributions to computer science in terms of novel methodsand techniques as well as respective algorithms and data structures, which are advancing visual analysis and visualization for enabling insights into XCT data on material systems. The introduced\nmethods and techniques focus on three distinct technical areas of visual analysis and visualization of XCT data. For each area, the problem statements, important research questions to be solved as well as the contributions of the habilitation candidate are discussed:\n1. Interactive visualization of spatial and quantitative data: Visualization and analysis techniques are introduced in this thesis for exploring, encoding, connecting, abstracting\nelaborating, reconfiguring, filtering, and finally selecting in \"rich\" XCT data. To reveal insights into complex objects, MObjects (i.e., mean objects) is discussed as a novel aggregation and exploration technique, which computes average volumetric representations from selections of individual objects of interest. To analyze various of these mean objects and to compare them with regards to their individual characteristics, visual analysis techniques as presented in FiberScout facilitate a detailed exploration of primary spatial data together with derived quantitative data (i.e., secondary data).\n2. Visual parameter space analysis (vPSA): The contributions towards vPSA focus on concepts for exploring and analyzing the space of possible parameter combinations of algorithms, models, and data processing pipelines as well as their effects on the ensemble of results. The presented methods and techniques visually guide users in finding adequate\ninput parameter sets, leading to optimal output results. In particular, the vPSA of segmentation and reconstruction algorithms is investigated. Similarity Metrics are introduced for comparing features as well as their characteristics.\n3. Comparative visualization and ensemble analysis: The comparison of larger sets of ensemble members as generated by vPSA is difficult, tedious, and error-prone, which is often\nexacerbated by subtle differences in the individual members. Here, techniques are presented to study the differences between multiple results regarding their visual representation as well as their characteristics. Dynamic Volume Lines is a novel technique for the visual analysis and comparison of large sets of 3D volumes using linearization methods combined with interactive data exploration. This technique is accompanied by a comparative visualization in the spatial domain to establish a link between the abstracted data and real world representations.\nFinally, in terms of visualization theory and modeling, this thesis abstracts the characteristics of visual parameter space analysis in a holistic conceptual framework. It also classifies and frames the novel area of visual computing in materials science, identifying research gaps within this\ndomain.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 472, "image_height": 326, "name": "Heinzl2021-image.JPG", "type": "image/jpeg", "size": 32717, "path": "Publication:Heinzl2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heinzl2021/Heinzl2021-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heinzl2021/Heinzl2021-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 611 ], "date_end": "2021-07-16", "date_start": "2010-01-01", "open_access": "yes", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "HABILITATION THESIS", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Heinzl2021-HABILITATION THESIS.pdf", "type": "application/pdf", "size": 26448758, "path": "Publication:Heinzl2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heinzl2021/Heinzl2021-HABILITATION THESIS.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heinzl2021/Heinzl2021-HABILITATION THESIS:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 472, "image_height": 326, "name": "Heinzl2021-image.JPG", "type": "image/jpeg", "size": 32717, "path": "Publication:Heinzl2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heinzl2021/Heinzl2021-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heinzl2021/Heinzl2021-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Heinzl2021/", "__class": "Publication" }, { "id": "Diehl_2021", "type_id": "journalpaper_notalk", "tu_id": 300516, "repositum_id": "20.500.12708/138614", "title": "Hornero: Thunderstorms Characterization using Visual Analytics", "date": "2021-06-29", "abstract": "Analyzing the evolution of thunderstorms is critical in determining the potential for the development of severe weather events. Existing visualization systems for short-term weather forecasting (nowcasting) allow for basic analysis and prediction of storm developments. However, they lack advanced visual features for efficient decision-making. We developed a visual analytics tool for the detection of hazardous thunderstorms and their characterization, using a visual design centered on a reformulated expert task workflow that includes visual features to overview storms and quickly identify high-impact weather events, a novel storm graph visualization to inspect and analyze the storm structure, as well as a set of interactive views for efficient identification of similar storm cells (known as analogs) in historical data and their use for nowcasting. Our tool was designed with and evaluated by meteorologists and expert forecasters working in short-term operational weather forecasting of severe weather events. Results show that our solution suits the forecasters' workflow. Our visual design is expressive, easy to use, and effective for prompt analysis and quick decision-making in the context of short-range operational weather forecasting.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 780, "image_height": 304, "name": "Diehl_2021-Image.JPG", "type": "image/jpeg", "size": 48560, "path": "Publication:Diehl_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Diehl_2021/Diehl_2021-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Diehl_2021/Diehl_2021-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1121, 5275, 1529, 1184, 166, 161 ], "doi": "10.1111/cgf.14308", "first_published": "2021-06-29", "journal": "Computer Graphics Forum", "number": "3", "open_access": "yes", "pages_from": "1", "pages_to": "12", "volume": "40", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 780, "image_height": 304, "name": "Diehl_2021-Image.JPG", "type": "image/jpeg", "size": 48560, "path": "Publication:Diehl_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Diehl_2021/Diehl_2021-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Diehl_2021/Diehl_2021-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Diehl_2021-Paper.pdf", "type": "application/pdf", "size": 54133751, "path": "Publication:Diehl_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Diehl_2021/Diehl_2021-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Diehl_2021/Diehl_2021-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Diehl_2021/", "__class": "Publication" }, { "id": "musleh_maath-2021-mam2", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Visual Analysis of Industrial Multivariate Time-Series Data: Effective Solution to Maximise Insights from Blow Moulding Machine Sensory Data", "date": "2021-06-21", "abstract": "Developments in the field of data analytics provides a boost for small-sized factories. These factories are eager to take full advantage of the potential insights in the remotely collected data to minimise cost and maximise quality and profit. This project aims to process, cluster and visualise sensory data of a blow moulding machine in a plastic production factory. In collaboration with Lean Automation, we aim to develop a data visualisation solution to enable decision-makers in a plastic factory to improve their production process. We will investigate three different aspects of the solution: methods for processing multivariate time-series data, clustering approaches for the sensory-data cultivated, and visualisation techniques that maximises production process insights. We use a formative evaluation method to develop a solution that meets partners' requirements and best practices within the field. Through building the MTSI dashboard tool, we hope to answer questions on optimal techniques to represent, cluster and visualise multivariate time series data. ", "authors_et_al": false, "substitute": null, "main_image": { "description": "GUI interaction snaps", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 861, "image_height": 597, "name": "musleh_maath-2021-mam2-image.png", "type": "image/png", "size": 243258, "path": "Publication:musleh_maath-2021-mam2", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam2/musleh_maath-2021-mam2-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam2/musleh_maath-2021-mam2-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1867 ], "date_end": "2021-06", "date_start": "2021-01", "diploma_examina": "2021-06-21", "matrikelnr": "19860127-T631", "open_access": "yes", "research_areas": [ "InfoVis" ], "keywords": [ "multivariate time-series", "visual analytics", "automated factories" ], "weblinks": [ { "href": "https://lnu.diva-portal.org/smash/get/diva2:1570718/FULLTEXT01.pdf", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": "GUI interaction snaps", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 861, "image_height": 597, "name": "musleh_maath-2021-mam2-image.png", "type": "image/png", "size": 243258, "path": "Publication:musleh_maath-2021-mam2", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam2/musleh_maath-2021-mam2-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam2/musleh_maath-2021-mam2-image:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/musleh_maath-2021-mam2/", "__class": "Publication" }, { "id": "mahler-2021-mdar", "type_id": "masterthesis", "tu_id": 300525, "repositum_id": "20.500.12708/17526", "title": "A Study of Multi-Document Active Reading in Analog and Digital Environments", "date": "2021-05", "abstract": "Despite the many improvements in the digital domain, knowledge workers still frequently switch between digital and analog materials and tools during their work. In doing so, they accept \"switching costs\" (such as time and resources) to perform active reading and related activities in their preferred (analog) environment. Previous studies show that active reading is more efficient using analog materials and tools than using digital ones. However, up to now, it is not fully understood what exactly leads to the superiority of analog active reading over digital active reading. The goal of this thesis is to directly compare the behaviors and strategies employed by users during active reading of multiple documents in analog and digital environments. This comparison serves to gain more detailed insights into which (sub-)areas of active reading (annotating, highlighting, note-taking, and spatial organization) are different in the two environments, what might be possible reasons for these differences, and most importantly, how to improve the experience of digital active reading in the future. As part of the comparison, it is also possible to determine whether analog active reading is still more efficient than digital active reading when using a large screen that provides a similar amount of space as an analog workstation. Thus, in a qualitative, controlled, partly confirmatory, partly exploratory, user study, users' behaviors and strategies during active reading of multiple documents in analog and digital environments are compared to investigate the previously mentioned aspects. The results show that analog active reading is still more efficient than digital active reading despite the use of a large screen. Additionally, the evaluation was able to identify differences in behaviors and adaptations of strategies used due to the accessibility and availability of tools. In particular, there is still considerable potential for improvement in the area of spatial organization during digital active reading.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1696 ], "date_end": "2021-05", "date_start": "2019", "diploma_examina": "2021-05-12", "doi": "10.34726/hss.2021.70704", "matrikelnr": "01325188", "open_access": "yes", "pages": "111", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [ "visual thinking", "active reading", "digital sensemaking", "information foraging theory", "knowledge workers", "user study" ], "weblinks": [], "files": [ { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mahler-2021-mdar-poster.pdf", "type": "application/pdf", "size": 283699, "path": "Publication:mahler-2021-mdar", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/mahler-2021-mdar/mahler-2021-mdar-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/mahler-2021-mdar/mahler-2021-mdar-poster:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mahler-2021-mdar-thesis.pdf", "type": "application/pdf", "size": 4721993, "path": "Publication:mahler-2021-mdar", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/mahler-2021-mdar/mahler-2021-mdar-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/mahler-2021-mdar/mahler-2021-mdar-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/mahler-2021-mdar/", "__class": "Publication" }, { "id": "koeppel-2021", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/55660", "title": "Context-Responsive Labeling in Augmented Reality", "date": "2021-04-19", "abstract": "Route planning and navigation are common tasks that often require additional information on points of interest. Augmented Reality (AR) enables mobile users to utilize text labels, in order to provide a composite view associated with additional information in a real- world environment. Nonetheless, displaying all labels for points of interest on a mobile device will lead to unwanted overlaps between information, and thus a context-responsive strategy to properly ar- range labels is expected. The technique should remove overlaps, show the right level-of-detail, and maintain label coherence. This is necessary as the viewing angle in an AR system may change rapidly due to users’ behaviors. Coherence plays an essential role in retaining user experience and knowledge, as well as avoiding motion sickness. In this paper, we develop an approach that sys- tematically manages label visibility and levels-of-detail, as well as eliminates unexpected incoherent movement. We introduce three label management strategies, including (1) occlusion management, (2) level-of-detail management, and (3) coherence management by balancing the usage of the mobile phone screen. A greedy approach is developed for fast occlusion handling in AR. A level-of-detail scheme is adopted to arrange various types of labels. A 3D scene manipulation is then built to simultaneously suppress the incoherent behaviors induced by viewing angle changes. Finally, we present the feasibility and applicability of our approach through one synthetic and two real-world scenarios, followed by a qualitative user study.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "koeppel-2021-image.png", "type": "image/png", "size": 72689, "path": "Publication:koeppel-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/koeppel-2021/koeppel-2021-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/koeppel-2021/koeppel-2021-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1367, 166, 1464 ], "booktitle": "Proceedings of the 14th IEEE Pacific Visualization Symposium ", "cfp": { "name": "PVIS 2021.pdf", "type": "application/pdf", "error": "0", "size": "1338305", "orig_name": "PVIS 2021.pdf", "ext": "pdf" }, "doi": "10.1109/pacificvis52677.2021.00020", "event": "IEEE Pacific Visualization Symposium ", "lecturer": [ 1464 ], "pages": "10", "pages_from": "1", "pages_to": "10", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "koeppel-2021-image.png", "type": "image/png", "size": 72689, "path": "Publication:koeppel-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/koeppel-2021/koeppel-2021-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/koeppel-2021/koeppel-2021-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "koeppel-2021-paper.pdf", "type": "application/pdf", "size": null, "path": "Publication:koeppel-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/koeppel-2021/koeppel-2021-paper.pdf", "thumb_image_sizes": [] }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "koeppel-2021-video.mp4", "type": "video/mp4", "size": 50783014, "path": "Publication:koeppel-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/koeppel-2021/koeppel-2021-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/koeppel-2021/koeppel-2021-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2021/koeppel-2021/koeppel-2021-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/koeppel-2021/", "__class": "Publication" }, { "id": "korpitsch-2021-lov", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "LSOVOMAN - Large-Scale Online Visualization of Austria's Media- Advertisement Networks", "date": "2021-04-07", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 3775, "image_height": 1960, "name": "korpitsch-2021-lov-screenshot.JPG", "type": "image/jpeg", "size": 265358, "path": "Publication:korpitsch-2021-lov", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/korpitsch-2021-lov/korpitsch-2021-lov-screenshot.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/korpitsch-2021-lov/korpitsch-2021-lov-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1697 ], "date_end": "2021-04", "date_start": "2020-10", "matrikelnr": "01529243", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [ "bipartite graphs", "large networks", "web-based visualization", "media transparency" ], "weblinks": [ { "href": "https://gitlab.cg.tuwien.ac.at/tkorpitsch/lsovaman", "caption": "Gitlab", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "Documentation", "main_file": false, "use_in_gallery": false, "access": "public", "name": "korpitsch-2021-lov-Documentation.pdf", "type": "application/pdf", "size": 141424, "path": "Publication:korpitsch-2021-lov", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/korpitsch-2021-lov/korpitsch-2021-lov-Documentation.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/korpitsch-2021-lov/korpitsch-2021-lov-Documentation:thumb{{size}}.png" }, { "description": null, "filetitle": "Report", "main_file": false, "use_in_gallery": false, "access": "public", "name": "korpitsch-2021-lov-Report.pdf", "type": "application/pdf", "size": 36864, "path": "Publication:korpitsch-2021-lov", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/korpitsch-2021-lov/korpitsch-2021-lov-Report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/korpitsch-2021-lov/korpitsch-2021-lov-Report:thumb{{size}}.png" }, { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 3775, "image_height": 1960, "name": "korpitsch-2021-lov-screenshot.JPG", "type": "image/jpeg", "size": 265358, "path": "Publication:korpitsch-2021-lov", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/korpitsch-2021-lov/korpitsch-2021-lov-screenshot.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/korpitsch-2021-lov/korpitsch-2021-lov-screenshot:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/korpitsch-2021-lov/", "__class": "Publication" }, { "id": "eiweck-hnv-2021", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Immersive Exploration of Hierarchical Networks in VR", "date": "2021-04", "abstract": "Our world is becoming more digital each year, new parts of our daily life become\nconnected and the amount and complexity of the produced data increases steadily.\nThe analysis of this data enables big opportunities for science and industry. A\nsubset of this data is organized in the form of hierarchical networks or can be\ntransformed by clustering algorithms into hierarchical layers. We see this in multiple\napplication domains for example medical research where connections, group and\ncluster memberships of diseases are tracked; social science where relationships\nare mapped in company organization charts; in software engineering in the form of\nbuild-, dependency- and source code version management software with hierarchical\nconnections between software modules, versions and layered software architecture.\n\nHowever, getting insight into this complex data with traditional two-dimensional\nvisualization is getting more difficult as the visual clutter increases significantly with\nthe exponentially growth of data we saw in recent years. Therefore, we need new\nmethods and techniques to facilitate and expedite the analysis process. In this thesis,\nwe investigate a new approach to visualize hierarchical network data by extending\nalready existing concepts of two-dimensional hierarchical network visualizations\nwith a third dimension and applying it to a virtual reality based visualization system.\nWe believe that the capabilities of virtual reality devices, such as improved\nspatial impression and interaction possibilities by room-scale tracked headsets and\ncontrollers allow the visualization to fully utilize the benefits of three-dimensional\ninformation visualization. Therefore, it should be possible to analyze even bigger\nand more complex hierarchical networks than currently possible with conventional\ntwo-dimensional visualizations.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 942, "image_height": 663, "name": "eiweck-hnv-2021-teaser.PNG", "type": "image/png", "size": 250349, "path": "Publication:eiweck-hnv-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/eiweck-hnv-2021/eiweck-hnv-2021-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/eiweck-hnv-2021/eiweck-hnv-2021-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1781 ], "co_supervisor": [ 1072 ], "date_end": "2021-04", "date_start": "2020-09", "matrikelnr": "01633012", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://3dmultilayer.emanum.dev/", "caption": "video & tool", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 942, "image_height": 663, "name": "eiweck-hnv-2021-teaser.PNG", "type": "image/png", "size": 250349, "path": "Publication:eiweck-hnv-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/eiweck-hnv-2021/eiweck-hnv-2021-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/eiweck-hnv-2021/eiweck-hnv-2021-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "eiweck-hnv-2021-thesis.pdf", "type": "application/pdf", "size": 10795367, "path": "Publication:eiweck-hnv-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/eiweck-hnv-2021/eiweck-hnv-2021-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/eiweck-hnv-2021/eiweck-hnv-2021-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/eiweck-hnv-2021/", "__class": "Publication" }, { "id": "pirch_2021_VRN", "type_id": "journalpaper_notalk", "tu_id": 299243, "repositum_id": "20.500.12708/138336", "title": "The VRNetzer platform enables interactive network analysis in Virtual Reality", "date": "2021-04", "abstract": "Networks provide a powerful representation of interacting components within complex\nsystems, making them ideal for visually and analytically exploring big data. However, the size\nand complexity of many networks render static visualizations on typically-sized paper or\nscreens impractical, resulting in proverbial ‘hairballs’. Here, we introduce a Virtual Reality\n(VR) platform that overcomes these limitations by facilitating the thorough visual, and\ninteractive, exploration of large networks. Our platform allows maximal customization and\nextendibility, through the import of custom code for data analysis, integration of external\ndatabases, and design of arbitrary user interface elements, among other features. As a proof\nof concept, we show how our platform can be used to interactively explore genome-scale\nmolecular networks to identify genes associated with rare diseases and understand how they\nmight contribute to disease development. Our platform represents a general purpose, VRbased\ndata exploration platform for large and diverse data types by providing an interface\nthat facilitates the interaction between human intuition and state-of-the-art analysis\nmethods.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1835, 1836, 1837, 1838, 1839, 1840, 1841, 1842, 1945, 378, 1843 ], "doi": "10.1038/s41467-021-22570-w", "first_published": "2021-04", "journal": "Nature Communications", "number": "2432", "open_access": "yes", "pages_from": "1", "pages_to": "14", "volume": "12", "research_areas": [ "InfoVis", "VR" ], "keywords": [ "virtual realitz" ], "weblinks": [ { "href": "https://www.nature.com/articles/s41467-021-22570-w", "caption": "Publication", "description": "The text of the publicatoin (open access). ", "main_file": 0 } ], "files": [], "projects_workgroups": [ "vr" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/pirch_2021_VRN/", "__class": "Publication" }, { "id": "raidou_previs2021", "type_id": "journalpaper_notalk", "tu_id": 301682, "repositum_id": "20.500.12708/138838", "title": "PREVIS: Predictive visual analytics of anatomical variability for radiotherapy decision support", "date": "2021-04", "abstract": "adiotherapy (RT) requires meticulous planning prior to treatment, where the RT plan is optimized with organ delineations on a pre-treatment Computed Tomography (CT) scan of the patient. The conventionally fractionated treatment usually lasts several weeks. Random changes (e.g., rectal and bladder filling in prostate cancer patients) and systematic changes (e.g., weight loss) occur while the patient is being treated. Therefore, the delivered dose distribution may deviate from the planned. Modern technology, in particular image guidance, allows to minimize these deviations, but risks for the patient remain.\n\nWe present PREVIS, a visual analytics tool for:\n\n(i) the exploration and prediction of changes in patient anatomy during the upcoming treatment, and\n\n(ii) the assessment of treatment strategies, with respect to the anticipated changes.\n\nRecords of during-treatment changes from a retrospective imaging cohort with complete data are employed in PREVIS, to infer expected anatomical changes of new incoming patients with incomplete data, using a generative model. Abstracted representations of the retrospective cohort partitioning provide insight into an underlying automated clustering, showing main modes of variation for past patients. Interactive similarity representations support an informed selection of matching between new incoming patients and past patients. A Principal Component Analysis (PCA)-based generative model describes the predicted spatial probability distributions of the incoming patient’s organs in the upcoming weeks of treatment, based on observations of past patients. The generative model is interactively linked to treatment plan evaluation, supporting the selection of the optimal treatment strategy.\n\nWe present a usage scenario, demonstrating the applicability of PREVIS in a clinical research setting, and we evaluate our visual analytics tool with eight clinical researchers.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1733, 1445, 1444, 1568, 1569, 1844, 1410 ], "doi": "https://doi.org/10.1016/j.cag.2021.04.010", "journal": "Computers and Graphics", "open_access": "yes", "pages_from": "126", "pages_to": "138", "volume": "97", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [ { "href": "https://renataraidou.com/previs-predictive-visual-analytics-of-anatomical-variability-for-radiotherapy-decision-support/", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": true, "access": "public", "preview_image_width": 768, "preview_image_height": 590, "name": "raidou_previs2021-paper.pdf", "type": "application/pdf", "size": null, "path": "Publication:raidou_previs2021", "preview_name": "raidou_previs2021-paper:preview.png", "preview_type": "image/png", "preview_size": 184775, "url": "https://www.cg.tuwien.ac.at/research/publications/2021/raidou_previs2021/raidou_previs2021-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/raidou_previs2021/raidou_previs2021-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/raidou_previs2021/", "__class": "Publication" }, { "id": "Batik-2021", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Embedding User-Defined Shapes into Metro Map Layouts", "date": "2021-03", "abstract": "Metro maps are essential when navigating through a public transportation network. They are schematic maps that have the aim to make orientation and navigation through a metro system easier. But creating them is quite complicated. Therefore numerous algorithms have been developed in the past trying to generate these maps automatically. The downside to using this approach is, that the designer only has limited possibilities to influence the resulting layout as well as contextual information of the city can not be taken into account. In order to overcome this limitation, this thesis presents a method where a potential user could influence the resulting layout by adding a set of guide paths. This method can be used to create artistically pleasing metro maps as well as make metro lines follow symbolic shapes in the layout. A mixed-layout – where some edges are rotated to be parallel to the closest guide path and other parts are octilinear – is proposed to integrate the guide paths better into the layout. To outline the potentials of this approach, examples of several metro networks were generated and are later also discussed.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 461, "image_height": 319, "name": "Batik-2021-image.png", "type": "image/png", "size": 56056, "path": "Publication:Batik-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Batik-2021/Batik-2021-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Batik-2021/Batik-2021-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1830 ], "date_end": "2021", "date_start": "2020", "matrikelnr": "11701221", "supervisor": [ 1464 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 461, "image_height": 319, "name": "Batik-2021-image.png", "type": "image/png", "size": 56056, "path": "Publication:Batik-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Batik-2021/Batik-2021-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Batik-2021/Batik-2021-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Batik-2021-thesis.pdf", "type": "application/pdf", "size": 4328824, "path": "Publication:Batik-2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Batik-2021/Batik-2021-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Batik-2021/Batik-2021-thesis:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Batik-2021/", "__class": "Publication" }, { "id": "waldner-2021-leo", "type_id": "journalpaper_notalk", "tu_id": 301684, "repositum_id": "20.500.12708/138840", "title": "Linking unstructured evidence to structured observations", "date": "2021-01-14", "abstract": "Many professionals, like journalists, writers, or consultants, need to acquire information from various sources, make sense of this unstructured evidence, structure their observations, and finally create and deliver their product, such as a report or a presentation. In formative interviews, we found that tools allowing structuring of observations are often disconnected from the corresponding evidence. Therefore, we designed a sensemaking environment with a flexible observation graph that visually ties together evidence in unstructured documents with the user’s structured knowledge. This is achieved through bi-directional deep links between highlighted document portions and nodes in the observation graph. In a controlled study, we compared users’ sensemaking strategies using either the observation graph or a simple text editor on a large display. Results show that the observation graph represents a holistic, compact representation of users’ observations, which can be linked to unstructured evidence on demand. In contrast, users taking textual notes required much more display space to spatially organize source documents containing unstructured evidence. This implies that spatial organization is a powerful strategy to structure observations even if the available space is limited.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "observation graph", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1920, "image_height": 700, "name": "waldner-2021-leo-observation graph.png", "type": "image/png", "size": 523772, "path": "Publication:waldner-2021-leo", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/waldner-2021-leo/waldner-2021-leo-observation graph.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/waldner-2021-leo/waldner-2021-leo-observation graph:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1110, 1477, 202, 1690 ], "doi": "https://doi.org/10.1177/1473871620986249", "journal": "Information Visualization", "research_areas": [ "InfoVis" ], "keywords": [ "mind map", "concept map", "observation graph", "visual links", "sensemaking" ], "weblinks": [], "files": [ { "description": null, "filetitle": "observation graph", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1920, "image_height": 700, "name": "waldner-2021-leo-observation graph.png", "type": "image/png", "size": 523772, "path": "Publication:waldner-2021-leo", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/waldner-2021-leo/waldner-2021-leo-observation graph.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/waldner-2021-leo/waldner-2021-leo-observation graph:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "waldner-2021-leo-Paper.pdf", "type": "application/pdf", "size": 4071473, "path": "Publication:waldner-2021-leo", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/waldner-2021-leo/waldner-2021-leo-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/waldner-2021-leo/waldner-2021-leo-Paper:thumb{{size}}.png" }, { "description": "accepted version", "filetitle": "preprint", "main_file": true, "use_in_gallery": false, "access": "public", "name": "waldner-2021-leo-preprint.pdf", "type": "application/pdf", "size": 6410358, "path": "Publication:waldner-2021-leo", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/waldner-2021-leo/waldner-2021-leo-preprint.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/waldner-2021-leo/waldner-2021-leo-preprint:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/waldner-2021-leo/", "__class": "Publication" }, { "id": "fourousan2021", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/17529", "title": "Visual Analytics for the Exploration of Cultural Models", "date": "2021", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1889 ], "date_end": "2021", "date_start": "2020", "diploma_examina": "2021-04-14", "doi": "10.34726/hss.2021.72580", "matrikelnr": "01429718", "pages": "172", "supervisor": [ 1410 ], "research_areas": [ "InfoVis" ], "keywords": [ "Visualization", "Cultural Models" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "fourousan2021-thesis.pdf", "type": "application/pdf", "size": 6602504, "path": "Publication:fourousan2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/fourousan2021/fourousan2021-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/fourousan2021/fourousan2021-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/fourousan2021/", "__class": "Publication" }, { "id": "sakr_sherif-2020-cacm", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "The Future is Big Graphs! A Community View on Graph Processing Systems", "date": "2020-12", "abstract": "Graphs are by nature ‘unifying abstractions’ that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decade for big graph processing to continue to succeed?\nWe are witnessing an unprecedented growth of interconnected data, which underscores the vital role of graph processing in our society. To name only a few remarkable examples of late, the importance of this field for practitioners is evidenced by the large number (over 50,000) of people registered2 to download the Neo4j book “​Graph Algorithms​” in just over 1.5 years, and by the enormous interest in the use of graph processing in the Artificial Intelligence and Machine Learning fields3. Furthermore, the timely Graphs4Covid-19 initiative4 provides evidence for the importance of big graph analytics in alleviating the global COVID-19 pandemic.\nThis article addresses the questions: How do the next-decade big graph processing systems look like from the perspectives of the data management and the large scale systems communities5? What can we say today about the guiding design principles of these systems in the next 10 years?", "authors_et_al": true, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "sakr_sherif-2020-cacm-image.png", "type": "image/png", "size": 43693, "path": "Publication:sakr_sherif-2020-cacm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1805, 1806, 1807, 1808, 1464 ], "journal": "Communications of the ACM ", "pages_from": "1", "pages_to": "14", "volume": "x", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "sakr_sherif-2020-cacm-image.png", "type": "image/png", "size": 43693, "path": "Publication:sakr_sherif-2020-cacm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sakr_sherif-2020-cacm-paper.pdf", "type": "application/pdf", "size": 711422, "path": "Publication:sakr_sherif-2020-cacm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/", "__class": "Publication" }, { "id": "spegel-gruenberger-2020", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Charakterisierung der Population von Pflegepatienten in zwei Pflegespitälern mithilfe interaktiver Visualisierungen elektronischer Patientendaten", "date": "2020-12", "abstract": "Results only accessible for members of the research unit. ", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1814 ], "date_end": "2020-12", "date_start": "2020-09", "matrikelnr": "08726501", "note": "194.047 Interdisciplinary Project in Data Science", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/spegel-gruenberger-2020/", "__class": "Publication" }, { "id": "Gall2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16616", "title": "Immersive Analytics of Multidimensional Volumetric Data", "date": "2020-11-24", "abstract": "Understanding and interpreting volumetric multidimensional data is a complex and cognitively demanding task. Especially in the field of material science the exploration of large spatial data is crucial. Non-destructive testing (NDT) plays an essential role in industrial production, especially in the field of material and component testing, regarding the analysis, visualization, and optimization of new, highly complex material systems such as fiber composites. In order to support the increasing demands on these materials and components of the future in industrial applications, extensive inspections and controls are essential. NDT inspection data generated by imaging techniques such as X-ray computed tomography (XCT) include 2D images, volumetric models, and derived high-dimensional data spaces. They can rarely, or only to a limited extent, be evaluated on desktop monitors using standard 2D visualization techniques. Therefore, novel immersive visualization and interaction techniques using Virtual Reality (VR) were developed in this thesis to investigate highly complex, heterogeneous material systems. We present a novel technique called \"Model in Miniature\" for an effective and interactive exploration and visual analysis of fiber characteristics. Furthermore, we combine different approaches like exploded views, histograms, and node-link diagrams to provide unique insights into the composite materials. Using embodied interaction and navigation, and enhancing the user’s abilities, previously impossible insights into the most complex material structures are possible. We use the latest findings from the field of Immersive Analytics to make the spatial data more comprehensible and test the results in a qualitative study with domain experts. The evaluation of our techniques has shown positive results, which indicate the benefits of an immersive analysis of composite materials and the exploration of overall high-dimensional volumes. The insights gained therefore represent an important step towards the further development of future immersive analysis platforms.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 502, "image_height": 298, "name": "Gall2020-Image.JPG", "type": "image/jpeg", "size": 31463, "path": "Publication:Gall2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1355 ], "co_supervisor": [ 611 ], "date_end": "2020-11-24", "date_start": "2020-01-15", "diploma_examina": "2020-11-24", "matrikelnr": "01225540", "open_access": "yes", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 502, "image_height": 298, "name": "Gall2020-Image.JPG", "type": "image/jpeg", "size": 31463, "path": "Publication:Gall2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Gall2020-Master Thesis.pdf", "type": "application/pdf", "size": 17524989, "path": "Publication:Gall2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Gall2020-Poster.pdf", "type": "application/pdf", "size": 2277755, "path": "Publication:Gall2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/", "__class": "Publication" }, { "id": "wu-2020-tvcg", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/140950", "title": "Multi-level Area Balancing of Clustered Graphs", "date": "2020-11-17", "abstract": "We present a multi-level area balancing technique for laying out clustered graphs to facilitate a comprehensive understanding of the complex relationships that exist in various fields, such as life sciences and sociology. Clustered graphs are often used to model relationships that are accompanied by attribute-based grouping information. Such information is essential for robust data analysis, such as for the study of biological taxonomies or educational backgrounds. Hence, the ability to smartly arrange textual labels and packing graphs within a certain screen space is therefore desired to successfully convey the attribute data . Here we propose to hierarchically partition the input screen space using Voronoi tessellations in multiple levels of detail. In our method, the position of textual labels is guided by the blending of constrained forces and the forces derived from centroidal Voronoi cells. The proposed algorithm considers three main factors: (1) area balancing, (2) schematized space partitioning, and (3) hairball management. We primarily focus on area balancing, which aims to allocate a uniform area for each textual label in the diagram. We achieve this by first untangling a general graph to a clustered graph through textual label duplication, and then coupling with spanning-tree-like visual integration. We illustrate the feasibility of our approach with examples and then evaluate our method by comparing it with well-known conventional approaches and collecting feedback from domain experts.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-tvcg-image.png", "type": "image/png", "size": 85239, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1579, 171 ], "doi": "https://doi.org/10.1109/TVCG.2020.3038154", "journal": "IEEE Transactions on Visualization and Computer Graphics (TVCG)", "open_access": "yes", "pages_from": "1", "pages_to": "15", "volume": "x", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [ "Graph drawing", "Voronoi tessellation", "multi-level", "spatially-efficient layout" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-tvcg-image.png", "type": "image/png", "size": 85239, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2020-tvcg-paper.pdf", "type": "application/pdf", "size": 48103600, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2020-tvcg-video.mov", "type": "video/quicktime", "size": 12802528, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-video.mov", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-video:video.mp4" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/", "__class": "Publication" }, { "id": "Groeller_V5_2020", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/87185", "title": "Interactive Visual Data Analysis", "date": "2020-11-09", "abstract": "Visualization and visual computing use computer-supported, interactive, visual representations of (abstract) data to amplify cognition. In recent years data complexity concerning volume, veracity, velocity, and variety has increased considerably. This is due to new data sources as well as the availability of uncertainty, error, and tolerance information. Instead of individual objects entire sets, collections, and ensembles are visually investigated. There is a need for visual analyses, comparative visualization, quantitative visualizations, scalable visualizations, and linked/integrated views. The concepts will be especially exemplified with a geospatial decision support system for flood management. Given the amplified data variability, interactive visual data analyses are likely to gain in importance in the future. Research challenges and directions are sketched at the end of the talk.\n", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 166 ], "date_from": "2020-11-09", "date_to": "2020-11-09", "event": "KAUST CEMSE Graduate Seminar (virtual)", "location": "KAUST, Saudi Arabia", "open_access": "yes", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://cemse.kaust.edu.sa/events/event/interactive-visual-data-analysis", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Groeller_V5_2020/", "__class": "Publication" }, { "id": "pointner_simon-2020", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Controllable Animation for Information Visualisation", "date": "2020-10-23", "abstract": "Understanding and identifying the alternations between different visualisations are cognitively demanding tasks. Distinct visualisations can lead to a different interpretation of data, thus it is important to understand how visualisations correlate with each other and how the insight to the data gained might vary. An approach to achieve the correlation understanding is to introduce animated transitions between different visualisations that allows to precisely follow changes, pursuing the research in the field of animated transitions. In particular, the focus of this research is on animated transitions between commonly used visualisations like bar, doughnut, pie and radial column charts with the addition of implementing them controllable. A controllable animation allows the user to control the animation with a seek-bar like in a video player. This work proposes and implements two new animated transitions, one animation between bar and pie charts and another one for hierarchical bar charts, both utilising other charts as intermediate steps. Expectations are to further improve the effectiveness and graphical perception of animated transitions. Though, a quantitative user study yielded no significant improvements apart from a little effectiveness gain among elder persons.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1796 ], "date_end": "2020-10-23", "date_start": "2019-02-26", "matrikelnr": "01612401", "supervisor": [ 1464 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "pointner_simon-2020-thesis.pdf", "type": "application/pdf", "size": 2063267, "path": "Publication:pointner_simon-2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/pointner_simon-2020/pointner_simon-2020-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/pointner_simon-2020/pointner_simon-2020-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/pointner_simon-2020/", "__class": "Publication" }, { "id": "furmanova_2020", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/140976", "title": "VAPOR: Visual Analytics for the Exploration of Pelvic Organ Variability in Radiotherapy", "date": "2020-10", "abstract": "In radiation therapy (RT) for prostate cancer, changes in patient anatomy during treatment might lead to inadequate tumor coverage and higher irradiation of healthy tissues in the nearby pelvic organs. Exploring and analyzing anatomical variability throughout the course of RT can support the design of more robust treatment strategies, while identifying patients that are prone to radiation-induced toxicity. We present VAPOR, a novel application for the exploration of pelvic organ variability in a cohort of patients, across the entire treatment process. Our application addresses: (i) the global exploration and analysis of anatomical variability in an abstracted tabular view, (ii) the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated, and (iii) the correlation of anatomical variability with radiation doses and potential toxicity. The workflow is based on available retrospective cohort data, which include segmentations of the bladder, the prostate, and the rectum through the entire treatment period. VAPOR is applied to four usage scenarios, which were conducted with two medical physicists. Our application provides clinical researchers with promising support in demonstrating the significance of treatment adaptation to anatomical changes.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1733, 1366, 1445, 1444, 1568, 1569, 166, 1410 ], "doi": "https://doi.org/10.1016/j.cag.2020.07.001", "journal": "Computer & Graphics", "note": "Special Section on VCBM 2019", "pages_from": "25", "pages_to": "38", "volume": "91", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1186, "preview_image_height": 641, "name": "furmanova_2020-paper.pdf", "type": "application/pdf", "size": 3355311, "path": "Publication:furmanova_2020", "preview_name": "furmanova_2020-paper:preview.PNG", "preview_type": "image/png", "preview_size": 382697, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/furmanova_2020/furmanova_2020-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/furmanova_2020/furmanova_2020-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/furmanova_2020/", "__class": "Publication" }, { "id": "cmolik-2020-tvcg", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/58318", "title": "Mixed Labeling: Integrating Internal and External Labels", "date": "2020-09-28", "abstract": "In this paper, we present an algorithm capable of mixed labeling of 2D and 3D objects. In mixed labeling, the given objects are labeled with both internal labels placed (at least partially) over the objects and external labels placed in the space around the objects and connected with the labeled objects with straight-line leaders. The proposed algorithm determines the position and type of each label based on the user-specified ambiguity threshold and eliminates overlaps between the labels, as well as between the internal labels and the straight-line leaders of external labels. The algorithm is a screen-space technique; it operates in an image where the 2D objects or projected 3D objects are encoded. In other words, we can use the algorithm whenever we can render the objects to an image, which makes the algorithm fit for use in many domains. The algorithm operates in real-time, giving the results immediately. Finally, we present results from an expert evaluation, in which a professional illustrator has evaluated the label layouts produced with the proposed algorithm.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "cmolik-2020-tvcg-image.png", "type": "image/png", "size": 47074, "path": "Publication:cmolik-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1246, 1782, 1464, 1579 ], "doi": "10.1109/TVCG.2020.3027368", "journal": "IEEE Transactions on Visualization and Computer Graphics (TVCG)", "pages_from": "1", "pages_to": "14", "volume": "x", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "cmolik-2020-tvcg-image.png", "type": "image/png", "size": 47074, "path": "Publication:cmolik-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "cmolik-2020-tvcg-paper.pdf", "type": "application/pdf", "size": 12960199, "path": "Publication:cmolik-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/", "__class": "Publication" }, { "id": "Groeller_V3_2020", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/87183", "title": " Interactive Visual Data Analysis", "date": "2020-09-19", "abstract": "Visualization and visual computing use computer-supported, interactive, visual representations of (abstract) data to amplify cognition. In recent years data complexity concerning volume, veracity, velocity, and variety has increased considerably. This is due to new data sources as well as the availability of uncertainty, error, and tolerance information. Instead of individual objects entire sets, collections, and ensembles are visually investigated. There is a need for visual analyses, comparative visualization, quantitative visualizations, scalable visualizations, and linked/integrated views. Several examples of interactively and visually analyzing data will be discussed in detail. These include: geospatial decision support, radiation therapy planning, and integrative cell biology. Given the amplified data variability, interactive visual data analyses are likely to gain in importance in the future. Research challenges and directions are sketched at the end of the talk.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 166 ], "event": "Conference on Image and Graphics Technology and Application (IGTA) 2021", "location": "Bejing ", "open_access": "yes", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://www.bsig.org.cn/detail/2420", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Groeller_V3_2020/", "__class": "Publication" }, { "id": "Iijima-2020-iV", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58172", "title": "Visualization of Semantic Differential Studies with a Large Number of Images, Participants and Attributes", "date": "2020-09-07", "abstract": "The Semantic Differential (SD) Method is a rating scale to measure the semantics. Attributes of SD are constructed by collecting the responses of participant’s impres- sions of the objects expressed through Likert scales representing multiple contrasting with some adjective pairs, for example, dark and bright, formal and casual, etc. Impression evaluation can be used as an index that reflects a human subjective feelings to some extent. Impression evaluations using the SD method consist of the responses of many participants, and therefore, the individual differences in the impressions of the participants greatly affect the content of the data. In this study, we propose a visualization system to analyze three aspects of SD, objects (images), participants, and attributes defined by adjective pairs. We visualize the impression evaluation data by applying dimension reduction so that, users can discover the trends and outliers of the data, such as images that are hard to judge or participants that act unpredictably. The system firstly visualizes the attributes or color distribution of the images by applying a dimensional reduction method to the impression or RGB values of each image. Then, our approach displays the average and median of each attribute near the images. This way, we can visualize the three aspects of objects, participants and attributes on a single screen and observe the relationships between image features and user impressions / attribute space. We introduce visualization examples of our system with the dataset inviting 21 participants who performed impression evaluations with 300 clothing images.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 479, "image_height": 339, "name": "Iijima-2020-iV-image.png", "type": "image/png", "size": 104231, "path": "Publication:Iijima-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1787, 1754, 1464, 1366 ], "booktitle": "Proceedings of the 24th International Conference on Information Visualisation (iV2020)", "cfp": { "name": "CFP-iV2020.pdf", "type": "application/pdf", "error": "0", "size": "59112", "orig_name": "CFP-iV2020.pdf", "ext": "pdf" }, "event": "The 24th International Conference on Information Visualisation (iV2020)", "lecturer": [ 1787 ], "pages_from": "1", "pages_to": "6", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 479, "image_height": 339, "name": "Iijima-2020-iV-image.png", "type": "image/png", "size": 104231, "path": "Publication:Iijima-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Iijima-2020-iV-paper.pdf", "type": "application/pdf", "size": 4114864, "path": "Publication:Iijima-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/", "__class": "Publication" }, { "id": "Kuroko-2020-iV", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58251", "title": "Visualization of Correlations between Places of Music Listening and Acoustic Features ", "date": "2020-09-07", "abstract": "Users often choose songs with respect to special situations and environments. We designed and developed a music recommendation method inspired by this fact. This method selects songs based on the distribution of acoustic features of the songs listened by a user at particular places that have higher ordinariness for the user. It is important to verify the relationship between the places where the songs are listened to and the acoustic features in this. Hence, we conducted the visualization to explore potential correlations between geographic locations and the music features of single users. In this paper, we designed an interactive visualization tool methods and results for the analysis of the relationship between the places and the acoustic features while listening to the songs.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 491, "image_height": 364, "name": "Kuroko-2020-iV-image.png", "type": "image/png", "size": 94249, "path": "Publication:Kuroko-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1785, 1786, 1754, 1366, 1464 ], "booktitle": "Proceedings of the 24th International Conference on Information Visualisation (iV2020)", "cfp": { "name": "CFP-iV2020.pdf", "type": "application/pdf", "error": "0", "size": "59112", "orig_name": "CFP-iV2020.pdf", "ext": "pdf" }, "event": "The 24th International Conference on Information Visualisation (iV2020)", "lecturer": [ 1785 ], "pages_from": "1", "pages_to": "6", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 491, "image_height": 364, "name": "Kuroko-2020-iV-image.png", "type": "image/png", "size": 94249, "path": "Publication:Kuroko-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Kuroko-2020-iV-paper.pdf", "type": "application/pdf", "size": 1282476, "path": "Publication:Kuroko-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/", "__class": "Publication" }, { "id": "Purchase-2020-gd", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58252", "title": "The Turing Test for Graph Drawing Algorithms", "date": "2020-09", "abstract": "DoalgorithmsfordrawinggraphspasstheTuringTest?That is, are their outputs indistinguishable from graphs drawn by humans? We address this question through a human-centred experiment, focusing on ‘small’ graphs, of a size for which it would be reasonable for someone to choose to draw the graph manually. Overall, we find that hand-drawn layouts can be distinguished from those generated by graph drawing al- gorithms, although this is not always the case for graphs drawn by force- directed or multi-dimensional scaling algorithms, making these good can- didates for Turing Test success. We show that, in general, hand-drawn graphs are judged to be of higher quality than automatically generated ones, although this result varies with graph size and algorithm.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "Purchase-2020-gd-image.png", "type": "image/png", "size": 29720, "path": "Publication:Purchase-2020-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1623, 1619, 1783, 1579, 1784, 1464 ], "booktitle": "Proceedings of the 28th International Symposium on Graph Drawing and Network Visualization (GD2020)", "cfp": { "name": "gd20-cfp.pdf", "type": "application/pdf", "error": "0", "size": "182950", "orig_name": "gd20-cfp.pdf", "ext": "pdf" }, "event": "28th International Symposium on Graph Drawing and Network Visualization ", "lecturer": [ 1623 ], "pages_from": "1", "pages_to": "16", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "Purchase-2020-gd-image.png", "type": "image/png", "size": 29720, "path": "Publication:Purchase-2020-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Purchase-2020-gd-paper.pdf", "type": "application/pdf", "size": 3933269, "path": "Publication:Purchase-2020-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/", "__class": "Publication" }, { "id": "Presch_2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/15583", "title": "Semi-Automatic Creation of Concept Maps", "date": "2020-08-20", "abstract": "Concept maps are a method for the visualization of knowledge and an established tool in education, knowledge organization and a variety of other fields. They are composed of concepts and interlinked relations between them and are displayed as a node-link diagram. Concept map mining is the process of extracting concept maps from unstructured text. The three approaches to mine concept maps are: manual, semi-automatic or fully automatic. A fully automatic approach cannot mirror the mental knowledge model, which a user would transfer to a manually created concept map. The manual process is often perceived as tedious and ineÿcient, limiting a wide-range application of concept maps.\nThis thesis presents a semi-automatic concept map mining approach that tries to bridge the gap between all manual construction and fully automatic approaches. The advantage of this approach is that the users still have control over how their concept map is constructed, but are not impeded by manual tasks that are often repetitive and ineÿcient. The presented approach is composed of an automatic text processing part, which extracts concepts and relations out of an unstructured text document and is powered by state-of-the-art natural language processing and neural coreference resolution. The second manual concept map creation part allows the creation of concept maps in a user interface and presents the extracted concepts and relations as suggestions to the user.\nIn a user study, an implemented prototype of the proposed semi-automatic concept map mining approach was evaluated. Manual gold standard concept maps that were created by the users and concept maps created by a fully automatic tool were compared to concept maps that were created with the prototype, proving the usefulness of the process. Results show that concept maps created with the semi-automatic prototype are significantly more similar to the gold standard than the ones created by the fully automatic tool. Additionally, considerably improved eÿciency in creation duration and user satisfaction could be observed in comparison to the manual creation of the gold standard maps.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1423, "image_height": 654, "name": "Presch_2020-teaser.png", "type": "image/png", "size": 262144, "path": "Publication:Presch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1687 ], "co_supervisor": [ 1110 ], "date_end": "2020-08-20", "date_start": "2020-01-23", "diploma_examina": "2020-08-20", "doi": "10.34726/hss.2020.70123", "matrikelnr": "0602554", "open_access": "yes", "pages": "122", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "Concept Map", "Natural language processing", "NLP" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Presch_2020-Master Thesis.pdf", "type": "application/pdf", "size": 5681227, "path": "Publication:Presch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Presch_2020-Poster.pdf", "type": "application/pdf", "size": 743440, "path": "Publication:Presch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-Poster:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1423, "image_height": 654, "name": "Presch_2020-teaser.png", "type": "image/png", "size": 262144, "path": "Publication:Presch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/", "__class": "Publication" }, { "id": "Neubauer2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/15249", "title": "Volumetric Image Segmentation on Multimodal Medical Images using Deep Learning", "date": "2020-07-25", "abstract": "The automatic segmentation of tumors on different imaging modalities supports medical experts in patient diagnosis and treatment. Magnetic resonance imaging (MRl), Computed Tomography (CT), or Positron Emission Tomography (PET) show the tumor in a different anatomical. functional, or molecular context. The fusion of this multimodal information leads to more profound knowledge and enabler more precise diagnoses. So far, the potential of multimodal data is only used by a few established segmentation methods. Moreover, much less is known about multimodal methods that provide several multimodal-specific tumor segmentations instead of single segmentations for a specific modality. \nThis thesis aims to develop a segmentation method that uses multimodal context to improve t the modality-specific segmentation results. For the implementation, an artificial neural network is used, which is based on a fully convolution neural network. The network architecture has been designed to learn complex multimodal features to predict multiple tumor segmentations on different modalities efficiently. \nThe evaluation is based on a dataset consisting of MRl aid PET /CT scans of soft soft tissue tumors. The experiment investigated how different network architectures, multimodal fusion strategies, and input modalities affect the segmentation results. Tbc investigation showed that multimodal rondels lead to significantly better results than models for single modalities. Promising results have been achieved with multimodal models that segment several modality-specific tumor contours simultaneously.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 236, "image_height": 286, "name": "Neubauer2020-image.JPG", "type": "image/jpeg", "size": 23529, "path": "Publication:Neubauer2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1777 ], "co_supervisor": [ 231 ], "date_end": "2020-07-25", "date_start": "2019-12-10", "diploma_examina": "2020-08-05", "doi": "10.34726/hss.2020.73220", "matrikelnr": "01609920", "open_access": "yes", "pages": "118", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "tumor segmentation", "deep learning" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 236, "image_height": 286, "name": "Neubauer2020-image.JPG", "type": "image/jpeg", "size": 23529, "path": "Publication:Neubauer2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Neubauer2020-Master Thesis.pdf", "type": "application/pdf", "size": 9032923, "path": "Publication:Neubauer2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Neubauer2020-Poster.pdf", "type": "application/pdf", "size": 9820244, "path": "Publication:Neubauer2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/", "__class": "Publication" }, { "id": "Pilizar_-2020-bachelor", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Artistic Metro Maps", "date": "2020-06-10", "abstract": "The creation of visually pleasing artistic metro maps usually requires a designer and a lot of effort, and while the automatic generation of regular metro maps has been done via several methods, none focus on the artistic aspect. To make the process easier for designers this thesis introduces a method that automatically creates maps that can either be used as they are, or used as baseline for the future design process. The goal of this thesis is to find a method and based on that create a prototype that generates metro maps in arbitrary shapes that simply requires the map and contour as input. Additional parameters are supposed to allow a user to make adjustments if so desired. The general approach is to first prepare the map as well as the contour for the following least squares calculations that reshape the map in a way to fit the contour and then create the look of a typical metro map. To test the algorithm and showcase its results it is applied to two different maps and seven different shapes. These results indicate that the introduced approach is capable of creating metro maps in arbitrary shapes, but need further adjustments by a designer to finalize the map.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1019, "image_height": 870, "name": "Pilizar_-2020-bachelor-image.png", "type": "image/png", "size": 48994, "path": "Publication:Pilizar_-2020-bachelor", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1764 ], "date_end": "2020-06", "date_start": "2019-06", "matrikelnr": "01525787", "supervisor": [ 1464 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1019, "image_height": 870, "name": "Pilizar_-2020-bachelor-image.png", "type": "image/png", "size": 48994, "path": "Publication:Pilizar_-2020-bachelor", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Pilizar_-2020-bachelor-thesis.pdf", "type": "application/pdf", "size": 3508257, "path": "Publication:Pilizar_-2020-bachelor", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/", "__class": "Publication" }, { "id": "raidou_pingu2020", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58256", "title": "PINGU Principles of Interactive Navigation for Geospatial Understanding", "date": "2020-06", "abstract": "Monitoring conditions in the periglacial areas of Antarctica helps geographers and geologists to understand physical processes associated with mesoscale land systems. Analyzing these unique temporal datasets poses a significant challenge for domain experts, due to the complex and often incomplete data, for which corresponding exploratory tools are not available. In this paper, we present a novel visual analysis tool for extraction and interactive exploration of temporal measurements captured at the polar station at the James Ross Island in Antarctica. The tool allows domain experts to quickly extract information about the snow level, originating from a series of photos acquired by trail cameras. Using linked views, the domain experts can interactively explore and combine this information with other spatial and non-spatial measures, such as temperature or wind speed, to reveal the interplay of periglacial and aeolian processes. An abstracted interactive map of the area indicates the position of measurement spots to facilitate navigation. The design of the tool was made in tight collaboration with geographers, which resulted in an early prototype, tested in the pilot study. The following version of the tool and its usability has been evaluated in the user study with five domain experts and their feedback was incorporated into the final version, presented in this paper. This version was again discussed with two experts in an informal interview. Within these evaluations, they confirmed the significant benefit of the tool for their research tasks.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1766, 1767, 1768, 1769, 1254, 1410, 1248 ], "booktitle": "2020 IEEE Pacific Visualization Symposium (PacificVis)", "cfp": { "name": "PacificVis 2020 call.pdf", "type": "application/pdf", "error": "0", "size": "168569", "orig_name": "PacificVis 2020 call.pdf", "ext": "pdf" }, "doi": "10.1109/PacificVis48177.2020.7567", "event": "IEEE Pacific Vis 2020", "lecturer": [ 1410 ], "pages_from": "216", "pages_to": "225", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1899, "image_height": 943, "name": "raidou_pingu2020-image.bmp", "type": "image/bmp", "size": 5375154, "path": "Publication:raidou_pingu2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/raidou_pingu2020-image.bmp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/raidou_pingu2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_pingu2020-paper.pdf", "type": "application/pdf", "size": 2925903, "path": "Publication:raidou_pingu2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/raidou_pingu2020-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/raidou_pingu2020-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/", "__class": "Publication" }, { "id": "wu-2020-eurovis-star", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/140650", "title": "A Survey on Transit Map Layout – from Design, Machine, and Human Perspectives", "date": "2020-05-25", "abstract": "Transit maps are designed to present information for using public transportation systems, such as urban railways. Creating a transit map is a time-consuming process, which requires iterative information selection, layout design, and usability validation, and thus maps cannot easily be customised or updated frequently. To improve this, scientists investigate fully- or semi-automatic techniques in order to produce high quality transit maps using computers and further examine their corresponding usability. Nonetheless, the quality gap between manually-drawn maps and machine-generated maps is still large. To elaborate the current research status, this state-of-the-art report provides an overview of the transit map generation process, primarily from Design, Machine, and Human perspectives. A systematic categorisation is introduced to describe the design pipeline, and an extensive analysis of perspectives is conducted to support the proposed taxonomy. We conclude this survey with a discussion on the current research status, open challenges, and future directions.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-eurovis-star-image.png", "type": "image/png", "size": 20954, "path": "Publication:wu-2020-eurovis-star", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1675, 1580, 1765, 1579 ], "cfp": { "name": "Eurovis – STARS – Eurographics & Eurovis 2020.pdf", "type": "application/pdf", "error": "0", "size": "468579", "orig_name": "Eurovis – STARS – Eurographics & Eurovis 2020.pdf", "ext": "pdf" }, "date_from": "2020-05-25", "date_to": "2020-05-29", "doi": "10.1111/cgf.14030", "event": "EuRoVis 2020", "issn": "1467-8659", "journal": "Computer Graphics Forum", "lecturer": [ 1464 ], "number": "3", "open_access": "yes", "pages": "28", "pages_from": "619", "pages_to": "646", "volume": "39", "research_areas": [ "InfoVis" ], "keywords": [ "Computer Graphics and Computer-Aided Design" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-eurovis-star-image.png", "type": "image/png", "size": 20954, "path": "Publication:wu-2020-eurovis-star", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2020-eurovis-star-paper.pdf", "type": "application/pdf", "size": 13228908, "path": "Publication:wu-2020-eurovis-star", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/", "__class": "Publication" }, { "id": "Groeller_V2_2020", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/87182", "title": "Visual Analytics in Radiation Therapy Planning", "date": "2020-05-15", "abstract": "Visual analytics concerns analytical reasoning supported by interactive visual interfaces. Radiation therapy is a complex treatment approach that requires careful planning. Visual analytics and visual computing are supportive in the entire radiation therapy workflow. After a brief survey on the workflow, concrete examples about radiation therapy planning for pelvic organs will be treated in detail. One example discusses visual analytics for the exploration of radio-therapy-induced bladder toxicity in a cohort study. Clinical researchers want to correlate bladder shape variations to dose deviations and toxicity risk through cohort studies, to understand which specific bladder shape characteristics are more prone to side effects. In another example the pelvic organ variability in a cohort of radiotherapy patients is visualized. The application addresses the global exploration and analysis of pelvic organ shape variability in an abstracted tabular view and the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated. Research challenges and directions are sketched at the end of the talk.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 166 ], "event": "Mohn Medical Imaging and Visualization Centre (MMIV) Virtual Seminar", "location": "Bergen, Norway", "open_access": "yes", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://mmiv.no/upcoming/mmiv-seminar-eduard-groeller/", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Groeller_V2_2020/", "__class": "Publication" }, { "id": "raidou_visgap2020", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58269", "title": "Lessons Learnt from Developing Visual Analytics Applications for Adaptive Prostate Cancer Radiotherapy", "date": "2020-05", "abstract": "In radiotherapy (RT), changes in patient anatomy throughout the treatment period might lead to deviations between planned\nand delivered dose, resulting in inadequate tumor coverage and/or overradiation of healthy tissues. Adapting the treatment to\naccount for anatomical changes is anticipated to enable higher precision and less toxicity to healthy tissues. Corresponding\ntools for the in-depth exploration and analysis of available clinical cohort data were not available before our work. In this\npaper, we discuss our on-going process of introducing visual analytics to the domain of adaptive RT for prostate cancer. This\nhas been done through the design of three visual analytics applications, built for clinical researchers working on the deployment\nof robust RT treatment strategies. We focus on describing our iterative design process, and we discuss the lessons learnt from\nour fruitful collaboration with clinical domain experts and industry, interested in integrating our prototypes into their workflow.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1733, 1366, 1444, 1568, 1569, 166, 1445 ], "booktitle": "The Gap between Visualization Research and Visualization Software (VisGap) (2020)", "cfp": { "name": "VisGap Workshop 2020.pdf", "type": "application/pdf", "error": "0", "size": "183556", "orig_name": "VisGap Workshop 2020.pdf", "ext": "pdf" }, "event": "EGEV2020 - VisGap Workshop", "lecturer": [ 1410 ], "open_access": "yes", "pages_from": "1", "pages_to": "8", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [ "Visual Analytics", "Life and Medical Sciences" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 1837, "preview_image_height": 998, "name": "raidou_visgap2020-paper.pdf", "type": "application/pdf", "size": 2068564, "path": "Publication:raidou_visgap2020", "preview_name": "raidou_visgap2020-paper:preview.PNG", "preview_type": "image/png", "preview_size": 87558, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_visgap2020/raidou_visgap2020-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_visgap2020/raidou_visgap2020-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_visgap2020/", "__class": "Publication" }, { "id": "gundacker-2020-wlm", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Wilangyman - Eine Google-Chrome Erweiterung die Wikipedia-Artikel um fremdsprachliche Inhalte ergänzt", "date": "2020-04", "abstract": "Wikipedia-Artikel unterscheiden sich in den unterschiedlichen Sprachversionen oft in\nStruktur und Inhalt. Manche Informationen sind nicht in allen Sprachen verfügbar.\nDas hat zur Folge, dass NutzerInnen wichtige Daten aus der Online Enzyklopädie\nentgehen, wenn sie sich auf eine Sprache beschränken. Ziel von Wilangyman ist es, diese\nInformationen zusammenzuführen und sie in übersichtlicher Art dem Nutzer oder der\nNutzerin zu präsentieren. Die Artikel werden mittels Natural Language Processing (NLP)\nverglichen und und anhand ihrer Ähnlichkeiten miteinander verknüpft. Korrespondierende\nPassagen mit zusätzlichem Informationsgehalt werden absatzweise dargestellt. Inhaltliche\nRedundanzen sollen dabei vermieden werden.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 377, "name": "gundacker-2020-wlm-screenshot.png", "type": "image/png", "size": 132524, "path": "Publication:gundacker-2020-wlm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1649 ], "date_end": "2020-04", "date_start": "2019-04", "matrikelnr": "08908802", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": { "1": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 377, "name": "gundacker-2020-wlm-screenshot.png", "type": "image/png", "size": 132524, "path": "Publication:gundacker-2020-wlm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "gundacker-2020-wlm-thesis.pdf", "type": "application/pdf", "size": 1436642, "path": "Publication:gundacker-2020-wlm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/", "__class": "Publication" }, { "id": "waldner-2020-tbg", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/141146", "title": "Interactive exploration of large time-dependent bipartite graphs", "date": "2020-04", "abstract": "Bipartite graphs are typically visualized using linked lists or matrices, but these visualizations neither scale well nor do they convey temporal development. We present a new interactive exploration interface for large, time-dependent bipartite graphs. We use two clustering techniques to build a hierarchical aggregation supporting different exploration strategies. Aggregated nodes and edges are visualized as linked lists with nested time series. We demonstrate two use cases: finding advertising expenses of public authorities following similar temporal patterns and comparing author-keyword co-occurrences across time. Through a user study, we show that linked lists with hierarchical aggregation lead to more insights than without.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Dynamic BicFlows with nested time series visualization per cluster per set.", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1121, "image_height": 936, "name": "waldner-2020-tbg-teaser.png", "type": "image/png", "size": 250456, "path": "Publication:waldner-2020-tbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1110, 1378, 166 ], "doi": "https://doi.org/10.1016/j.cola.2020.100959", "journal": "Journal of Computer Languages", "volume": "57", "research_areas": [ "InfoVis", "NetVis" ], "keywords": [ "Information visualization", "Bipartite graphs", "Clustering", "Time series data", "Insight-based evaluation" ], "weblinks": [ { "href": "https://www.sciencedirect.com/science/article/pii/S2590118420300198", "caption": "paper", "description": "Open Access article at ScienceDirect", "main_file": 1 } ], "files": [ { "description": "Dynamic BicFlows with nested time series visualization per cluster per set.", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1121, "image_height": 936, "name": "waldner-2020-tbg-teaser.png", "type": "image/png", "size": 250456, "path": "Publication:waldner-2020-tbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/", "__class": "Publication" }, { "id": "Cornel_2020", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/1225", "title": "Interactive Visualization of Simulation Data for GeospatialDecision Support", "date": "2020-01-19", "abstract": "Floods are catastrophic events that claim thousands of human lives every year. For theprediction of these events, interactive decision support systems with integrated floodsimulation have become a vital tool. Recent technological advances made it possibleto simulate flooding scenarios of unprecedented scale and resolution, resulting in verylarge time-dependent data. The amount of simulation data is further amplified by theuse of ensemble simulations to make predictions more robust, yielding high-dimensionaland uncertain data far too large for manual exploration. New strategies are thereforeneeded to filter these data and to display only the most important information to supportdomain experts in their daily work. This includes the communication of results to decisionmakers, emergency services, stakeholders, and the general public. A modern decisionsupport system has to be able to provide visual results that are useful for domain experts,but also comprehensible for larger audiences. Furthermore, for an efficient workflow, theentire process of simulation, analysis, and visualization has to happen in an interactivefashion, putting serious time constraints on the system.In this thesis, we present novel visualization techniques for time-dependent and uncertainflood, logistics, and pedestrian simulation data for an interactive decision support system.As the heterogeneous tasks in flood management require very diverse visualizations fordifferent target audiences, we provide solutions to key tasks in the form of task-specificand user-specific visualizations. This allows the user to show or hide detailed informationon demand to obtain comprehensible and aesthetic visualizations to support the task athand. In order to identify the impact of flooding incidents on a building of interest, onlya small subset of all available data is relevant, which is why we propose a solution toisolate this information from the massive simulation data. To communicate the inherentuncertainty of resulting predictions of damages and hazards, we introduce a consistentstyle for visualizing the uncertainty within the geospatial context. Instead of directlyshowing simulation data in a time-dependent manner, we propose the use of bidirectionalflow maps with multiple components as a simplified representation of arbitrary materialflows. For the communication of flood risks in a comprehensible way, however, thedirect visualization of simulation data over time can be desired. Apart from the obviouschallenges of the complex simulation data, the discrete nature of the data introducesadditional problems for the realistic visualization of water surfaces, for which we proposerobust solutions suitable for real-time applications. All of our findings have been acquiredthrough a continuous collaboration with domain experts from several flood-related fieldsof work. The thorough evaluation of our work by these experts confirms the relevanceand usefulness of our presented solutions. \n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 436, "image_height": 277, "name": "Cornel_2020-image.JPG", "type": "image/jpeg", "size": 53075, "path": "Publication:Cornel_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 877 ], "doi": "10.34726/hss.2020.75784", "duration": "5", "matrikelnr": "0726194", "open_access": "yes", "pages": "167", "reviewer_1": [ 1745 ], "reviewer_2": [ 823 ], "rigorosum": "2020-01", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "Interactive visualization", "uncertainty", "flood management", "decision support", "flood simulation" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 436, "image_height": 277, "name": "Cornel_2020-image.JPG", "type": "image/jpeg", "size": 53075, "path": "Publication:Cornel_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "PhD Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Cornel_2020-PhD Thesis.pdf", "type": "application/pdf", "size": 43001362, "path": "Publication:Cornel_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-PhD Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-PhD Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/", "__class": "Publication" }, { "id": "heim-gall-2020-dde", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "DDE - Dynamic Data Explorer: Dynamic data exploration in a collaborative spatial-aware environment", "date": "2020-01", "abstract": "Collaborative decision-making has become an integral part of the analysis process aiming to get insight into multivariate\ndata. To further encourage this workflow numerous co-located, multi-user systems have been developed consisting of large\nmulti-touch screens or interactive tabletops. But such frameworks are typically expensive and unavailable outside dedicated\nenvironments as for example laboratories. Therefore we developed the Dynamic Data Explorer, short DDE, a multi-user system\nthat enables users to join, in an ad-hoc manner, with their own mobile devices. Since forming groups should be possible in\nvarious locations, the tracking system, enabling spatial awareness of the devices, has to be light-weight and small. Near Field\nCommunication (NFC) is a widespread transmission technology which fulfils these properties and is used in our framework to\nenable different side-by-side arrangements of devices. This allows users to explore multivarate data visualizations on a system\nwhere the number of devices and their set-up can be modified at all times.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "setup", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2220, "image_height": 1900, "name": "heim-gall-2020-dde-setup.jpg", "type": "image/jpeg", "size": 1379498, "path": "Publication:heim-gall-2020-dde", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-setup.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-setup:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1354, 1355 ], "date_end": "2020-01", "date_start": "2019-04", "matrikelnr": "1226809, 1225540", "supervisor": [ 1110, 1643 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://github.com/nonsens949/Practicum/wiki", "caption": "GitHub", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "report", "main_file": false, "use_in_gallery": false, "access": "public", "name": "heim-gall-2020-dde-report.pdf", "type": "application/pdf", "size": 1583282, "path": "Publication:heim-gall-2020-dde", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-report:thumb{{size}}.png" }, { "description": null, "filetitle": "setup", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2220, "image_height": 1900, "name": "heim-gall-2020-dde-setup.jpg", "type": "image/jpeg", "size": 1379498, "path": "Publication:heim-gall-2020-dde", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-setup.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-setup:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/", "__class": "Publication" }, { "id": "sorger-2019-odn", "type_id": "inproceedings", "tu_id": 284199, "repositum_id": null, "title": "Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation", "date": "2019-12", "abstract": "Analysis of large dynamic networks is a thriving research field, typically relying on 2D graph representations. The advent of affordable head mounted displays sparked new interest in the potential of 3D visualization for immersive network analytics. Nevertheless, most solutions do not scale well with the number of nodes and edges and rely on conventional fly- or walk-through navigation. In this paper, we present a novel approach for the exploration of large dynamic graphs in virtual reality that interweaves two navigation metaphors: overview exploration and immersive detail analysis. We thereby use the potential of state-of-the-art VR headsets, coupled with a web-based 3D rendering engine that supports heterogeneous input modalities to enable ad-hoc immersive network analytics. We validate our approach through a performance evaluation and a case study with experts analyzing medical data.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "detail view", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1600, "image_height": 900, "name": "sorger-2019-odn-detail view.jpg", "type": "image/jpeg", "size": 203956, "path": "Publication:sorger-2019-odn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sorger-2019-odn/sorger-2019-odn-detail view.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sorger-2019-odn/sorger-2019-odn-detail view:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1072, 1110, 853, 1705 ], "booktitle": "2nd International Conference on Artificial Intelligence & Virtual Reality", "cfp": { "name": "IEEE AIVR 2019.pdf", "type": "application/pdf", "error": "0", "size": "203068", "orig_name": "IEEE AIVR 2019.pdf", "ext": "pdf" }, "event": "AIVR 2019", "lecturer": [ 1072 ], "location": "San Diego, California, USA", "open_access": "yes", "organization": "IEEE", "pages_from": "144", "pages_to": "151", "research_areas": [ "InfoVis", "NetVis" ], "keywords": [ "Immersive Network Analytics", "Web-Based Visualization", "Dynamic Graph Visualization" ], "weblinks": [ { "href": "https://arxiv.org/pdf/1910.06825.pdf", "caption": "arxiv preprint", "description": null, "main_file": 1 }, { "href": "http://aivr.science.uu.nl/", "caption": "IEEE AIVR 2019", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "detail view", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1600, "image_height": 900, "name": "sorger-2019-odn-detail view.jpg", "type": "image/jpeg", "size": 203956, "path": "Publication:sorger-2019-odn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sorger-2019-odn/sorger-2019-odn-detail view.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sorger-2019-odn/sorger-2019-odn-detail view:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sorger-2019-odn-video.mp4", "type": "video/mp4", "size": 97540271, "path": "Publication:sorger-2019-odn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sorger-2019-odn/sorger-2019-odn-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sorger-2019-odn/sorger-2019-odn-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/sorger-2019-odn/sorger-2019-odn-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sorger-2019-odn/", "__class": "Publication" }, { "id": "wu-2019-visworkshop", "type_id": "WorkshopTalk", "tu_id": null, "repositum_id": null, "title": "Graph Models for Biological Pathway Visualization: State of the Art and Future Challenges", "date": "2019-10-20", "abstract": "The concept of multilayer networks has become recently integrated into complex systems modeling since it encapsulates a very general concept of complex relationships. Biological pathways are an exam- ple of complex real-world networks, where vertices represent biolog- ical entities, and edges indicate the underlying connectivity. For this reason, using multilayer networks to model biological knowledge allows us to formally cover essential properties and theories in the field, which also raises challenges in visualization. This is because, in the early days of pathway visualization research, only restricted types of graphs, such as simple graphs, clustered graphs, and others were adopted. In this paper, we revisit a heterogeneous definition of biological networks and aim to provide an overview to see the gaps between data modeling and visual representation. The contribution will, therefore, lie in providing guidelines and challenges of using multilayer networks as a unified data structure for the biological pathway visualization.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-visworkshop-image.png", "type": "image/png", "size": 22606, "path": "Publication:wu-2019-visworkshop", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1579, 171 ], "cfp": { "name": "Multilayer_Network_Visualization_Workshop_VIS_2019.pdf", "type": "application/pdf", "error": "0", "size": "508927", "orig_name": "Multilayer_Network_Visualization_Workshop_VIS_2019.pdf", "ext": "pdf" }, "event": "Vis 2019 Workshop", "lecturer": [ 1464 ], "location": "Canada", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [ "Graph drawing", "multilayer network", "biological pathway" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-visworkshop-image.png", "type": "image/png", "size": 22606, "path": "Publication:wu-2019-visworkshop", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2019-visworkshop-paper.pdf", "type": "application/pdf", "size": 252096, "path": "Publication:wu-2019-visworkshop", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/", "__class": "Publication" }, { "id": "mazurek-2018-vac", "type_id": "masterthesis", "tu_id": 282668, "repositum_id": null, "title": "Visual Active Learning for News Stream Classification", "date": "2019-10-10", "abstract": "In many domains, the sheer quantity of text documents that have to be parsed increases\ndaily. To keep up with this continuous text stream, a considerable amount of time has to be invested. We developed a classification interface for text streams that learns user-specific topics from the user’s labeling process and partitions the incoming data into these topics.\nCurrent approaches that try to derive content categorization from a vast number of unstructured text documents use pre-trained learning models to perform text classification.\nThese models assign predefined categories to the text according to its content. Depending on the use case, a user’s interests might not coincide with the given categories. The model cannot adapt to changing terminology that was not present during training. Besides these factors, users often do not trust pre-trained models as they are a black box for them.\nTo solve this problem, our application lets users define a classification problem and\ntrain a learning model through interaction with a Star Coordinates visualization. The\napproach that makes this interaction efficient is a variant of active learning. This active learning variant states that a learning model can achieve greater accuracy with fewer labeled training instances, if a user provides data purposefully from which it learns. We adapted this strategy for text stream classification by visualizing the topic affiliation probabilities of the learning model and providing novel interaction tools to enhance the model’s performance iteratively. By simulating different selection strategies common in active learning, we found that our visual selection strategies correspond closely to the classic active learning selection\nstrategies. Further, users performed on par with the best simulated selection strategies in the results from our preliminary user study. Our evaluation concludes that there are benefits from incorporating information visualization into the active learning process.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 668, "image_height": 638, "name": "mazurek-2018-vac-image.png", "type": "image/png", "size": 56667, "path": "Publication:mazurek-2018-vac", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1364 ], "date_end": "2019-10-10", "date_start": "2018-03", "matrikelnr": "0123456", "open_access": "yes", "supervisor": [ 1110, 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 668, "image_height": 638, "name": "mazurek-2018-vac-image.png", "type": "image/png", "size": 56667, "path": "Publication:mazurek-2018-vac", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "mazurek-2018-vac-Master thesis.pdf", "type": "application/pdf", "size": 5490435, "path": "Publication:mazurek-2018-vac", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-Master thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-Master thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "mazurek-2018-vac-Poster.pdf", "type": "application/pdf", "size": 1520895, "path": "Publication:mazurek-2018-vac", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/", "__class": "Publication" }, { "id": "Arleo-2019-vis", "type_id": "inproceedings", "tu_id": 280935, "repositum_id": null, "title": "Sabrina: Modeling and Visualization of Economy Data with Incremental Domain Knowledge", "date": "2019-10", "abstract": "Investment planning requires knowledge of the financial landscape on a large scale, both in terms of geo-spatial and industry sector distribution. There is plenty of data available, but it is scattered across heterogeneous sources (newspapers, open data, etc.), which makes it difficult for financial analysts to understand the big picture. In this paper, we present Sabrina, a financial data analysis and visualization approach that incorporates a pipeline for the generation of firm-to-firm financial transaction networks. The pipeline is capable of fusing the ground truth on individual firms in a region with (incremental) domain knowledge on general macroscopic aspects of the economy. Sabrina unites these heterogeneous data sources within a uniform visual interface that enables the visual analysis process. In a user study with three domain experts, we illustrate the usefulness of Sabrina, which eases their analysis process.", "authors_et_al": false, "substitute": null, "main_image": { "description": "The different visualizations composing the Sabrina system", "filetitle": "sab_tease_nolabels", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 4770, "image_height": 2496, "name": "Arleo-2019-vis-sab_tease_nolabels.png", "type": "image/png", "size": 3157916, "path": "Publication:Arleo-2019-vis", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Arleo-2019-vis/Arleo-2019-vis-sab_tease_nolabels.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Arleo-2019-vis/Arleo-2019-vis-sab_tease_nolabels:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1705, 1706, 1558, 1707, 1708, 1598, 1709, 966, 193, 1072 ], "booktitle": "IEEE VIS 2019", "cfp": { "name": "VIS 2019-Short Papers Call for Participation.pdf", "type": "application/pdf", "error": "0", "size": "450180", "orig_name": "VIS 2019-Short Papers Call for Participation.pdf", "ext": "pdf" }, "event": " IEEE Visualization Conference (VIS)", "lecturer": [ 1705 ], "location": "Vancouver, British Columbia, Canada", "open_access": "yes", "research_areas": [ "InfoVis" ], "keywords": [ "Visualization", "Visual Analytics" ], "weblinks": [ { "href": "https://arxiv.org/abs/1908.07479", "caption": "paper", "description": null, "main_file": 0 } ], "files": [ { "description": "The different visualizations composing the Sabrina system", "filetitle": "sab_tease_nolabels", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 4770, "image_height": 2496, "name": "Arleo-2019-vis-sab_tease_nolabels.png", "type": "image/png", "size": 3157916, "path": "Publication:Arleo-2019-vis", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Arleo-2019-vis/Arleo-2019-vis-sab_tease_nolabels.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Arleo-2019-vis/Arleo-2019-vis-sab_tease_nolabels:thumb{{size}}.png" } ], "projects_workgroups": [ "3DSpatialization" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Arleo-2019-vis/", "__class": "Publication" }, { "id": "sietzen-ifv-2019", "type_id": "otherreviewed", "tu_id": null, "repositum_id": null, "title": "Interactive Feature Visualization in the Browser", "date": "2019-10", "abstract": "Excellent explanations of feature visualization already exist in the form of interactive articles, e.g. DeepDream, Feature Visualization, The Building Blocks of Interpretability, Activation Atlas, Visualizing GoogLeNet Classes. They mostly rely on curated prerendered visualizations, additionally providing colab notebooks or public repositories allowing the reader to reproduce those results. While precalculated visualizations have many advantages (directability, more processing budget), they are always discretized samples of a continuous parameter space. In the spirit of Tensorflow Playground, this project aims at providing a fully interactive interface to some basic functionality of the originally Python-based Lucid library, roughly corresponding to the concepts presented in the “Feature Visualization\" article. The user is invited to explore the effect of parameter changes in a playful way and without requiring any knowledge of programming, enabled by an implementation on top of TensorFlow.js. Live updates of the generated input image as well as feature map activations should give the user a visual intuition to the otherwise abstract optimization process. Further, this interface opens the domain of feature visualization to non-experts, as no scripting is required.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 759, "image_height": 614, "name": "sietzen-ifv-2019-screenshot.png", "type": "image/png", "size": 293509, "path": "Publication:sietzen-ifv-2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1373, 1110 ], "booktitle": "Proceedings of the Workshop on Visualization for AI explainability (VISxAI)", "cfp": { "name": "2nd VISxAI Workshop at IEEE VIS 2019.pdf", "type": "application/pdf", "error": "0", "size": "409701", "orig_name": "2nd VISxAI Workshop at IEEE VIS 2019.pdf", "ext": "pdf" }, "editor": "El-Assady, Mennatallah and Chau, Duen Horng (Polo) and Hohman, Fred and Perer, Adam and Strobelt, Hendrik and Viégas, Fernanda", "event": "Workshop on Visualization for AI explainability (VISxAI) at IEEE VIS 2019", "lecturer": [ 1373 ], "location": "Vancouver", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://visxai.stefansietzen.at/", "caption": "Explainable URL", "description": "Peer-reviewed submission for the workshop. ", "main_file": 1 }, { "href": "https://visxai.io/", "caption": "VISxAI Workshop 2019", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 759, "image_height": 614, "name": "sietzen-ifv-2019-screenshot.png", "type": "image/png", "size": 293509, "path": "Publication:sietzen-ifv-2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-screenshot:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sietzen-ifv-2019-video.mp4", "type": "video/mp4", "size": 51123687, "path": "Publication:sietzen-ifv-2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-video:video.mp4" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/", "__class": "Publication" }, { "id": "waldner-2019-rld", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "A Comparison of Radial and Linear Charts for Visualizing Daily Patterns", "date": "2019-10", "abstract": "Radial charts are generally considered less effective than linear charts. Perhaps the only exception is in visualizing periodical time-dependent data, which is believed to be naturally supported by the radial layout. It has been demonstrated that the\ndrawbacks of radial charts outweigh the benefits of this natural mapping. Visualization of daily patterns, as a special case, has not been systematically evaluated using radial charts. In contrast to yearly or weekly recurrent trends, the analysis of daily patterns on a radial chart may benefit from our trained skill on reading radial clocks that are ubiquitous in our culture. In a crowd-sourced experiment with 92 non-expert users, we evaluated the accuracy, efficiency, and subjective ratings of radial and linear charts for visualizing daily traffic accident patterns. We systematically compared juxtaposed 12-hours variants and single 24-hours variants for both layouts in four low-level tasks and one high-level interpretation task. Our results show that over all tasks, the most elementary 24-hours linear bar chart is most accurate and efficient and is also preferred by the users. This provides strong evidence for the use of linear layouts – even for visualizing periodical daily patterns.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Daily patterns visualized in a 24-hours radial chart. ", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 497, "image_height": 474, "name": "waldner-2019-rld-teaser.png", "type": "image/png", "size": 53565, "path": "Publication:waldner-2019-rld", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1110, 1121, 581, 1204, 1122, 235 ], "cfp": { "name": "IEEE VIS 2019 Call For Participation.pdf", "type": "application/pdf", "error": "0", "size": "545751", "orig_name": "IEEE VIS 2019 Call For Participation.pdf", "ext": "pdf" }, "date_from": "2019-10-20", "date_to": "2019-10-25", "doi": "10.1109/TVCG.2019.2934784", "event": "IEEE VIS InfoVis", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 1110 ], "location": "Vancouver, Canada", "pages_from": "1033", "pages_to": "1042", "volume": "26", "research_areas": [ "InfoVis", "Perception" ], "keywords": [ "radial charts", "time series data", "daily patterns", "crowd-sourced experiment" ], "weblinks": [ { "href": "https://vimeo.com/371939694", "caption": "Presentation recording from IEEE VIS 2019 (VGTC Vimeo)", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "waldner-2019-rld-paper.pdf", "type": "application/pdf", "size": 892625, "path": "Publication:waldner-2019-rld", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-paper:thumb{{size}}.png" }, { "description": "Powerpoint slides of presentation at IEEE VIS 2019 (do not contain animations and videos). ", "filetitle": "slides ", "main_file": false, "use_in_gallery": false, "access": "public", "name": "waldner-2019-rld-slides .pdf", "type": "application/pdf", "size": 12853249, "path": "Publication:waldner-2019-rld", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-slides .pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-slides :thumb{{size}}.png" }, { "description": "Supplemental information about the user study", "filetitle": "supplement", "main_file": false, "use_in_gallery": false, "access": "public", "name": "waldner-2019-rld-supplement.pdf", "type": "application/pdf", "size": 2511402, "path": "Publication:waldner-2019-rld", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-supplement.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-supplement:thumb{{size}}.png" }, { "description": "Daily patterns visualized in a 24-hours radial chart. ", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 497, "image_height": 474, "name": "waldner-2019-rld-teaser.png", "type": "image/png", "size": 53565, "path": "Publication:waldner-2019-rld", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "video preview", "main_file": false, "use_in_gallery": false, "access": "public", "name": "waldner-2019-rld-video preview.mp4", "type": "video/mp4", "size": 3082628, "path": "Publication:waldner-2019-rld", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-video preview.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-video preview:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-video preview:video.mp4" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/", "__class": "Publication" }, { "id": "li-2019-gdc", "type_id": "unknown", "tu_id": 282819, "repositum_id": null, "title": "World map of recipes", "date": "2019-09-19", "abstract": "This poster visualises the Meal Ingredients dataset with 151 international food recipes and their corresponding ingredients. The underlying graph layout in the image is automatically generated using a new multi-level force-based algorithm developed by the authors, but not yet published. The background flags were added manually to identify the countries from the data set. The algorithm aims to untangle mutually nested subgraphs by harmonizing the available space for the labels and improving edge visibility by duplicating high-frequency ingredient nodes. Ingredients occurring in multiple countries also receive at least one node per country. The idea is inspired by map diagrams, which often show the semantics enclosed by country boundaries. In our diagram, countries are represented by octolinear polygons, and are placed next to each other if they share many ingredients in their recipes. The actual placement of the countries by the algorithm is entirely data driven. As we can see, this design naturally gathers countries that are located on the same continent, due to the accessibility of the ingredients. The names of recipes are visualized using textual labels with sharp corners, and they are enclosed by the country polygon they belong to. Contrarily, ingredients are represented by textual labels with rounded corners. Moreover, ingredients are visually classified into common (pink) and special (blue) ingredients based on their frequency in the dataset. \nFor visually analyzing the data set, we can generate smoothed spanning trees along the boundaries of an (invisible) Voronoi diagram of all textual labels to connect identical nodes to visually integrate all copies of one ingredient. For example, we highlighted the ingredient \"soy sauce\", one of the most commonly used ingredients in Asia, to discover that it has spread to the UK as well. We can also perform visual queries for related recipes based on sharing rare ingredients. For example, the British dish \"steak and kidney pie\" is highlighted in green together with three blue spanning trees connecting all recipes related to that dish via at least one of its special (blue) ingredients.", "authors_et_al": false, "substitute": null, "main_image": { "description": "1st Place Award, Creative Topic-\"Meal Ingredients\", of the 28th Annual Graph Drawing Contest", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "li-2019-gdc-image.png", "type": "image/png", "size": 109353, "path": "Publication:li-2019-gdc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/li-2019-gdc-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/li-2019-gdc-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1698, 1699, 1579, 171, 1464 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": "1st Place Award, Creative Topic-\"Meal Ingredients\", of the 28th Annual Graph Drawing Contest", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "li-2019-gdc-image.png", "type": "image/png", "size": 109353, "path": "Publication:li-2019-gdc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/li-2019-gdc-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/li-2019-gdc-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "li-2019-gdc-poster.pdf", "type": "application/pdf", "size": 1508060, "path": "Publication:li-2019-gdc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/li-2019-gdc-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/li-2019-gdc-poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/", "__class": "Publication" }, { "id": "wu-2019-vcbm", "type_id": "unknown", "tu_id": null, "repositum_id": null, "title": "Map of Metabolic Harmony", "date": "2019-09-03", "abstract": "As the human body is healthy when the\nmetabolic harmony is maintained, the human metabolic pathways are\ninterpretable when its visual representation is harmonized. We\ndeveloped an automatic approach to hierarchically decompose the screen\nspace to multiple functional regions and embed sub-pathways into their\ncorresponding regions to unveil complex metabolite relationships.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-vcbm-image.png", "type": "image/png", "size": 109418, "path": "Publication:wu-2019-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1579, 171 ], "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image-full", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 8878, "image_height": 6919, "name": "wu-2019-vcbm-image-full.png", "type": "image/png", "size": 15607607, "path": "Publication:wu-2019-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image-full.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image-full:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-vcbm-image.png", "type": "image/png", "size": 109418, "path": "Publication:wu-2019-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/", "__class": "Publication" }, { "id": "raidou_2019_pelvisrunner", "type_id": "inproceedings", "tu_id": 283994, "repositum_id": null, "title": "Pelvis Runner: Visualizing Pelvic Organ Variability in a Cohort of Radiotherapy Patients", "date": "2019-09", "abstract": "In radiation therapy, anatomical changes in the patient might lead to deviations between the planned and delivered dose--including inadequate tumor coverage, and overradiation of healthy tissues. Exploring and analyzing anatomical changes throughout the entire treatment period can help clinical researchers to design appropriate treatment strategies, while identifying patients that are more prone to radiation-induced toxicity. We present the Pelvis Runner, a novel application for exploring the variability of segmented pelvic organs in multiple patients, across the entire radiation therapy treatment process. Our application addresses (i) the global exploration and analysis of pelvic organ shape variability in an abstracted tabular view and (ii) the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated. The workflow is based on available retrospective cohort data, which incorporate segmentations of the bladder, the prostate, and the rectum through the entire radiation therapy process. The Pelvis Runner is applied to four usage scenarios, which were conducted with two clinical researchers, i.e., medical physicists. Our application provides clinical researchers with promising support in demonstrating the significance of treatment plan adaptation to anatomical changes.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1366, 1444, 1445, 1568, 1569, 166, 1410 ], "booktitle": "Eurographics Workshop on Visual Computing for Biology and Medicine (2019)", "cfp": { "name": "For submitters - VCBM 2019.pdf", "type": "application/pdf", "error": "0", "size": "340448", "orig_name": "For submitters - VCBM 2019.pdf", "ext": "pdf" }, "doi": "10.2312/vcbm.20191233", "event": "Eurographics Workshop on Visual Computing for Biology and Medicine (2019)", "lecturer": [ 1366 ], "pages_from": "69", "pages_to": "78", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 9269, "preview_image_height": 4095, "name": "raidou_2019_pelvisrunner-paper.pdf", "type": "application/pdf", "size": 2868471, "path": "Publication:raidou_2019_pelvisrunner", "preview_name": "raidou_2019_pelvisrunner-paper:preview.jpg", "preview_type": "image/jpeg", "preview_size": 1955471, "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_pelvisrunner/raidou_2019_pelvisrunner-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_pelvisrunner/raidou_2019_pelvisrunner-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_2019_pelvisrunner-video.mp4", "type": "video/mp4", "size": 35722536, "path": "Publication:raidou_2019_pelvisrunner", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_pelvisrunner/raidou_2019_pelvisrunner-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_pelvisrunner/raidou_2019_pelvisrunner-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_pelvisrunner/raidou_2019_pelvisrunner-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_pelvisrunner/", "__class": "Publication" }, { "id": "raidou_2019_preha", "type_id": "inproceedings", "tu_id": 283963, "repositum_id": null, "title": "preha: Establishing Precision Rehabilitation with Visual Analytics", "date": "2019-09", "abstract": "This design study paper describes preha, a novel visual analytics application in the field of in-patient rehabilitation. We conducted extensive interviews with the intended users, i.e., engineers and clinical rehabilitation experts, to determine specific requirements of their analytical process.We identified nine tasks, for which suitable solutions have been designed and developed in the flexible environment of kibana. Our application is used to analyze existing rehabilitation data from a large cohort of 46,000 patients, and it is the first integrated solution of its kind. It incorporates functionalities for data preprocessing (profiling, wrangling and cleansing), storage, visualization, and predictive analysis on the basis of retrospective outcomes. A positive feedback from the first evaluation with domain experts indicates the usefulness of the newly proposed approach and represents a solid foundation for the introduction of visual analytics to the rehabilitation domain.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1654, 235, 166, 1410 ], "booktitle": "Eurographics Workshop on Visual Computing for Biology and Medicine (2019)", "cfp": { "name": "For submitters - VCBM 2019.pdf", "type": "application/pdf", "error": "0", "size": "340448", "orig_name": "For submitters - VCBM 2019.pdf", "ext": "pdf" }, "doi": "10.2312/vcbm.20191234", "event": "Eurographics Workshop on Visual Computing for Biology and Medicine (2019)", "lecturer": [ 1410 ], "pages_from": "79", "pages_to": "89", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1280, "preview_image_height": 720, "name": "raidou_2019_preha-paper.pdf", "type": "application/pdf", "size": 4173646, "path": "Publication:raidou_2019_preha", "preview_name": "raidou_2019_preha-paper:preview.png", "preview_type": "image/png", "preview_size": 821513, "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/raidou_2019_preha-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/raidou_2019_preha-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "slides", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_2019_preha-slides.pdf", "type": "application/pdf", "size": 1577612, "path": "Publication:raidou_2019_preha", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/raidou_2019_preha-slides.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/raidou_2019_preha-slides:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_2019_preha-video.mp4", "type": "video/mp4", "size": 19827660, "path": "Publication:raidou_2019_preha", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/raidou_2019_preha-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/raidou_2019_preha-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/raidou_2019_preha-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/", "__class": "Publication" }, { "id": "sietzen-2019-wnn", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Web-Interface for neural network feature visualization", "date": "2019-08", "abstract": "Excellent explanations of feature visualization already exist in the form of interactive articles, e.g. DeepDream, Feature Visualization, The Building Blocks of Interpretability, Activation Atlas, Visualizing GoogLeNet Classes. They mostly rely on curated prerendered visualizations, additionally providing colab notebooks or public repositories allowing the reader to reproduce those results. While precalculated visualizations have many advantages (directability, more processing budget), they are always discretized samples of a continuous parameter space. In the spirit of Tensorflow Playground, this project aims at providing a fully interactive interface to some basic functionality of the originally Python-based Lucid library, roughly corresponding to the concepts presented in the “Feature Visualization\" article. The user is invited to explore the effect of parameter changes in a playful way and without requiring any knowledge of programming, enabled by an implementation on top of TensorFlow.js. Live updates of the generated input image as well as feature map activations should give the user a visual intuition to the otherwise abstract optimization process. Further, this interface opens the domain of feature visualization to non-experts, as no scripting is required.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 759, "image_height": 614, "name": "sietzen-2019-wnn-screenshot.png", "type": "image/png", "size": 293509, "path": "Publication:sietzen-2019-wnn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/sietzen-2019-wnn-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/sietzen-2019-wnn-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1373 ], "date_end": "2019-08", "date_start": "2019-04", "matrikelnr": "0372194", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://visxai.stefansietzen.at/", "caption": "VISxAI URL", "description": "Explainable URL, accepted for the IEEE VIS 2019 Workshop on Visualization for AI Explainability. ", "main_file": 1 }, { "href": "https://visxai.io/", "caption": "VISxAI workshop", "description": "2nd workshop on Visualization for AI Explainability in Vancover, Canada, October 21, 2019. ", "main_file": 0 }, { "href": "https://github.com/stefsietz/LucidPlayground", "caption": "LucidPlayground GitHub", "description": "Source code", "main_file": 0 } ], "files": [ { "description": "JSDoc, zipped", "filetitle": "documentation LucidPlayground", "main_file": false, "use_in_gallery": false, "access": "public", "name": "sietzen-2019-wnn-documentation LucidPlayground.zip", "type": "application/x-zip-compressed", "size": 556043, "path": "Publication:sietzen-2019-wnn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/sietzen-2019-wnn-documentation LucidPlayground.zip", "thumb_image_sizes": [] }, { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 759, "image_height": 614, "name": "sietzen-2019-wnn-screenshot.png", "type": "image/png", "size": 293509, "path": "Publication:sietzen-2019-wnn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/sietzen-2019-wnn-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/sietzen-2019-wnn-screenshot:thumb{{size}}.png" }, { "description": "Submission video for VISxAI workshop. ", "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "name": "sietzen-2019-wnn-video.mp4", "type": "video/mp4", "size": 51123687, "path": "Publication:sietzen-2019-wnn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/sietzen-2019-wnn-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/sietzen-2019-wnn-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/sietzen-2019-wnn-video:video.mp4" } ], "projects_workgroups": [ "vis", "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/", "__class": "Publication" }, { "id": "raidou_2019_springer", "type_id": "inbook", "tu_id": 283965, "repositum_id": null, "title": "Visual Analytics for the Representation, Exploration and Analysis of High-Dimensional, Multi-Faceted Medical Data", "date": "2019-07-17", "abstract": "Medicine is among research fields with a significant impact on\nhumans and their health. Already for decades, medicine has established\na tight coupling with the visualization domain, proving the importance\nof developing visualization techniques, designed exclusively for this\nresearch discipline. However, medical data is steadily increasing in\ncomplexity with the appearance of heterogeneous, multi-modal, multiparametric,\ncohort or population, as well as uncertain data. To deal with\nthis kind of complex data, the field of Visual Analytics has emerged.\nIn this chapter, we discuss the many dimensions and facets of medical\ndata. Based on this classification, we provide a general overview of\nstate-of-the-art visualization systems and solutions dealing with highdimensional,\nmulti-faceted data. Our particular focus will be on multimodal,\nmulti-parametric data, on data from cohort or population studies\nand on uncertain data, especially with respect to Visual Analytics\napplications for the representation, exploration, and analysis of highdimensional,\nmulti-faceted medical data.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410 ], "booktitle": "Biomedical Visualisation", "chapter": "10", "doi": "https://doi.org/10.1007/978-3-030-14227-8_10", "editor": "Springer", "note": "https://www.springer.com/gp/book/9783030142261", "pages_from": "137", "pages_to": "162", "publisher": "Springer", "volume": "2", "research_areas": [ "BioVis", "InfoVis", "MedVis" ], "keywords": [], "weblinks": [ { "href": "https://www.springer.com/gp/book/9783030142261", "caption": "link", "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_springer/", "__class": "Publication" }, { "id": "mizuno-2019-eurovis", "type_id": "journalpaper", "tu_id": 282848, "repositum_id": null, "title": "Optimizing Stepwise Animation in Dynamic Set Diagrams", "date": "2019-07-10", "abstract": "A set diagram represents the membership relation among data elements. It is often visualized as secondary information on top of primary information, such as the spatial positions of elements on maps and charts. Visualizing the temporal evolution of such set diagrams as well as their primary features is quite important; however, conventional approaches have only focused on the temporal behavior of the primary features and do not provide an effective means to highlight notable transitions within the set relationships. This paper presents an approach for generating a stepwise animation between set diagrams by decomposing the entire transition into atomic changes associated with individual data elements. The key idea behind our approach is to optimize the ordering of the atomic changes such that the synthesized animation minimizes unwanted set occlusions by considering their depth ordering and reduces the gaze shift between two consecutive stepwise changes. Experimental results and a user study demonstrate that the proposed approach effectively facilitates the visual identification of the detailed transitions inherent in dynamic set diagrams.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "mizuno-2019-eurovis-image.png", "type": "image/png", "size": 100164, "path": "Publication:mizuno-2019-eurovis", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1674, 1464, 1580, 1040 ], "cfp": { "name": "eurovis2019.pdf", "type": "application/pdf", "error": "0", "size": "37147", "orig_name": "eurovis2019.pdf", "ext": "pdf" }, "date_from": "2019", "date_to": "2019", "doi": "https://doi.org/10.1111/cgf.13668", "event": "EuroVis 2019", "journal": "Computer Graphics Forum", "lecturer": [ 1674 ], "note": "Best Paper Honorable Mention at EuroVis 2019", "pages_from": "13", "pages_to": "24", "volume": "38", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://youtu.be/dMphkr6nAHQ", "caption": "video", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "mizuno-2019-eurovis-image.png", "type": "image/png", "size": 100164, "path": "Publication:mizuno-2019-eurovis", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mizuno-2019-eurovis-paper.pdf", "type": "application/pdf", "size": 20180512, "path": "Publication:mizuno-2019-eurovis", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/", "__class": "Publication" }, { "id": "maruyama-2019-iv", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Scale-Aware Cartographic Displacement Based on Constrained Optimization", "date": "2019-07", "abstract": "Abstract—The consistent arrangement of map features in accordance with the map scale has recently been technically important in digital cartographic generalization. This is primarily due to the recent demand for informative mapping systems, especially for use in smartphones and tablets. However, such sophisticated generalization has usually been conducted manually by expert cartographers and thus results in a time-consuming and error-prone process. In this paper, we focus on the displacement process within cartographic generalization and formulate them as a constrained optimization problem to provide an associated algorithm implementation and its effective solution. We first identify the underlying spatial relationships among map features, such as points and lines, on each map scale as constraints and optimize the cost function that penalizes excessive displacement of the map features in terms of the map scale. Several examples are also provided to demonstrate that the proposed approach allows us to maintain consistent mapping regardless of changes to the map scale.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "maruyama-2019-iv-image.png", "type": "image/png", "size": 58725, "path": "Publication:maruyama-2019-iv", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/maruyama-2019-iv/maruyama-2019-iv-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/maruyama-2019-iv/maruyama-2019-iv-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1625, 1580, 1464, 1676, 1627 ], "booktitle": "Proceedings of the 23th International Conference on Information Visualisation (iV2019)", "cfp": { "name": "iv2019.pdf", "type": "application/pdf", "error": "0", "size": "91598", "orig_name": "iv2019.pdf", "ext": "pdf" }, "doi": "https://dx.doi.org/10.1109/IV.2019.00022", "event": " The 23th International Conference on Information Visualisation ", "lecturer": [ 1580 ], "pages_from": "74", "pages_to": "80", "research_areas": [ "InfoVis" ], "keywords": [ "Cartographic generalization", "displacement", "constrained optimization", "scale-aware mapping" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "maruyama-2019-iv-image.png", "type": "image/png", "size": 58725, "path": "Publication:maruyama-2019-iv", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/maruyama-2019-iv/maruyama-2019-iv-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/maruyama-2019-iv/maruyama-2019-iv-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/maruyama-2019-iv/", "__class": "Publication" }, { "id": "byska-2019-mdfc", "type_id": "journalpaper", "tu_id": 283263, "repositum_id": null, "title": "Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization", "date": "2019-06", "abstract": "Analyzing molecular dynamics (MD) simulations is a key aspect to understand protein dynamics and function. With increasing computational power, it is now possible to generate very long and complex simulations, which are cumbersome to explore using traditional 3D animations of protein movements. Guided by requirements derived from multiple focus groups with protein engineering experts, we designed and developed a novel interactive visual analysis approach for long and crowded MD simulations. In this approach, we link a dynamic 3D focus+context visualization with a 2D chart of time series data to guide the detection and navigation towards important spatio-temporal events. The 3D visualization renders elements of interest in more detail and increases the temporal resolution dependent on the time series data or the spatial region of interest. In case studies with different MD simulation data sets and research questions, we found that the proposed visual analysis approach facilitates exploratory analysis to generate, confirm, or reject hypotheses about causalities. Finally, we derived design guidelines for interactive visual analysis of complex MD simulation data.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 783, "image_height": 717, "name": "byska-2019-mdfc-teaser.jpg", "type": "image/jpeg", "size": 95308, "path": "Publication:byska-2019-mdfc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1254, 1196, 1669, 1499, 1248, 1110 ], "cfp": { "name": "Eurovis 2019 CFP.pdf", "type": "application/pdf", "error": "0", "size": "91823", "orig_name": "Eurovis 2019 CFP.pdf", "ext": "pdf" }, "date_from": "2019-06-03", "date_to": "2019-06-07", "doi": "10.1111/cgf.13701", "event": "EuroVis 2019", "journal": "Computer Graphics Forum", "lecturer": [ 1254 ], "location": "Porto, Portugal", "number": "3", "pages_from": "441", "pages_to": "453", "volume": "38", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [ "scientific visualization", "user centered design" ], "weblinks": [ { "href": "https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13701", "caption": "Wiley Online ", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "byska-2019-mdfc-paper.pdf", "type": "application/pdf", "size": 5805942, "path": "Publication:byska-2019-mdfc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-paper:thumb{{size}}.png" }, { "description": "Domain expert report of findings", "filetitle": "supplement", "main_file": false, "use_in_gallery": false, "access": "public", "name": "byska-2019-mdfc-supplement.pdf", "type": "application/pdf", "size": 2846584, "path": "Publication:byska-2019-mdfc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-supplement.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-supplement:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 783, "image_height": 717, "name": "byska-2019-mdfc-teaser.jpg", "type": "image/jpeg", "size": 95308, "path": "Publication:byska-2019-mdfc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "byska-2019-mdfc-video.mp4", "type": "video/mp4", "size": 222623560, "path": "Publication:byska-2019-mdfc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-video:video.mp4" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/", "__class": "Publication" }, { "id": "takahashi-2019-acdt", "type_id": "journalpaper_notalk", "tu_id": 283264, "repositum_id": null, "title": "Mental Map Preservation for Progressively Labeling Railway Networks", "date": "2019-06", "abstract": "Schematizing railway networks for better readability is often achieved by aligning railway lines along the octilinear directions. However, such railway map layouts require further adjustment when placing station name labels. In this article, the authors present a novel approach to automating the placement of station names around the railway network while maximally respecting its original layout as the mental map. The key idea is to progressively annotate stations from congested central downtown areas to sparse rural areas. This is accomplished by introducing the sum of geodesic distances over the railway network to properly order the stations to be annotated first, and then elongating the line segments of the railway network while retaining their directions to spare enough labeling space around each station. Additional constraints are also introduced to restrict the aspect ratios of the region confined by the railway network for better preservation of the mental map.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "takahashi-2019-acdt-image.png", "type": "image/png", "size": 29890, "path": "Publication:takahashi-2019-acdt", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/takahashi-2019-acdt/takahashi-2019-acdt-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/takahashi-2019-acdt/takahashi-2019-acdt-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1580, 1625, 1626, 1464, 1676, 1627 ], "doi": "https://doi.org/10.4018/IJACDT.2019010103", "journal": "International Journal of Art, Culture and Design Technologies", "number": "1", "pages_from": "31", "pages_to": "50", "volume": "8", "research_areas": [ "IllVis", "InfoVis" ], "keywords": [ "Geodesic Distances", "Mental Maps", "Mixed-Integer Programming", "Progressive Annotation", "Railway Maps", "Schematic Layouts" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "takahashi-2019-acdt-image.png", "type": "image/png", "size": 29890, "path": "Publication:takahashi-2019-acdt", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/takahashi-2019-acdt/takahashi-2019-acdt-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/takahashi-2019-acdt/takahashi-2019-acdt-image:thumb{{size}}.png" }, { "description": null, "filetitle": "pdf", "main_file": true, "use_in_gallery": false, "access": "public", "name": "takahashi-2019-acdt-pdf.pdf", "type": "application/pdf", "size": 1599109, "path": "Publication:takahashi-2019-acdt", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/takahashi-2019-acdt/takahashi-2019-acdt-pdf.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/takahashi-2019-acdt/takahashi-2019-acdt-pdf:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/takahashi-2019-acdt/", "__class": "Publication" }, { "id": "Troidl_2019", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Flow Visualization on Curved Manifolds", "date": "2019-05-28", "abstract": "Climate researchers often use simulations to generate 2D vector fields of wind or ocean currents. They need visualization tools to validate and further improve their research. In this work, we present a framework that is capable of visualizing unsteady 2D flow fields on curved surfaces. An important property of our framework is that it works intrinsically in 2D, instead of in 3D ambient space. Our primary example is the visualization of 2D geophysical flow on the 2-sphere. We build on methods from differential geometry to compute line integral convolution and path lines intrinsically on curved surfaces.\nWhile line integral convolution provides an overview of one time step of an unsteady\nflow field, path lines give us a more detailed insight into an unsteady flow field. We animate the line integral convolution images and the path lines to show the direction of the flow. Furthermore, we illuminate the path lines to improve spatial perception. Our visualizations are all computed in real time and can be used interactively.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1431, "image_height": 1434, "name": "Troidl_2019-image.PNG", "type": "image/png", "size": 2199579, "path": "Publication:Troidl_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Troidl_2019/Troidl_2019-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Troidl_2019/Troidl_2019-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1659 ], "date_end": "2019-05-29", "date_start": "2018-11-02", "matrikelnr": "01525071", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://www.youtube.com/watch?v=5B0BHSpi_6g&t=1s", "caption": "Youtube: Flow Visualization on Curved Manifolds", "description": "Flow Visualization on Curved Manifolds", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "Bachelor Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Troidl_2019-Bachelor Thesis.pdf", "type": "application/pdf", "size": 15846221, "path": "Publication:Troidl_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Troidl_2019/Troidl_2019-Bachelor Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Troidl_2019/Troidl_2019-Bachelor Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1431, "image_height": 1434, "name": "Troidl_2019-image.PNG", "type": "image/png", "size": 2199579, "path": "Publication:Troidl_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Troidl_2019/Troidl_2019-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Troidl_2019/Troidl_2019-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Troidl_2019/", "__class": "Publication" }, { "id": "wu-2019-bmc", "type_id": "journalpaper_notalk", "tu_id": 280645, "repositum_id": null, "title": "Metabopolis: Scalable Network Layout for Biological Pathway Diagrams in Urban Map Style", "date": "2019-05-15", "abstract": "Background\nBiological pathways represent chains of molecular interactions in biological systems that jointly form complex dynamic networks. The network structure changes from the significance of biological experiments and layout algorithms often sacrifice low-level details to maintain high-level information, which complicates the entire image to large biochemical systems such as human metabolic pathways.\n\nResults\nOur work is inspired by concepts from urban planning since we create a visual hierarchy of biological pathways, which is analogous to city blocks and grid-like road networks in an urban area. We automatize the manual drawing process of biologists by first partitioning the map domain into multiple sub-blocks, and then building the corresponding pathways by routing edges schematically, to maintain the global and local context simultaneously. Our system incorporates constrained floor-planning and network-flow algorithms to optimize the layout of sub-blocks and to distribute the edge density along the map domain. We have developed the approach in close collaboration with domain experts and present their feedback on the pathway diagrams based on selected use cases.\n\nConclusions\nWe present a new approach for computing biological pathway maps that untangles visual clutter by decomposing large networks into semantic sub-networks and bundling long edges to create space for presenting relationships systematically.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-bmc-image.png", "type": "image/png", "size": 107492, "path": "Publication:wu-2019-bmc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1579, 1673, 171 ], "doi": "http://doi.org/10.1186/s12859-019-2779-4", "journal": "BMC Bioinformatics", "number": "187", "pages_from": "1", "pages_to": "20", "volume": "20", "research_areas": [ "BioVis", "IllVis", "InfoVis" ], "keywords": [ "Biological pathways", "Graph drawing", "Mapmetaphor", "Orthogonallayout", "Floorplanning", "Edgerouting" ], "weblinks": [ { "href": "https://www.youtube.com/watch?v=AhWCIGTxqAg", "caption": "video", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-bmc-image.png", "type": "image/png", "size": 107492, "path": "Publication:wu-2019-bmc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2019-bmc-paper.pdf", "type": "application/pdf", "size": 8528804, "path": "Publication:wu-2019-bmc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/", "__class": "Publication" }, { "id": "Rippberger_2019", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Data-Driven Anatomical Layouting of Brain Network Graphs", "date": "2019-04-18", "abstract": "The visualization of brain networks today offers a variety of different tools and approaches. Representations in 2D such as connectograms, connectivity matrices, and node-link diagrams are common but an abstract visualization of the network without any anatomical context. Visualizations tools show anatomical context in 2D but adjust it especially for\na certain species as for example the fruit fly’s brain. This project presents a tool for data-driven brain network visualization using the open-source graph library Cytoscape.js to avoid hard coded spatial constraints. The goal of the project was to find a layout algorithm that resembles the anatomical structure of the brain visualized without any hard coded constraints. After testing the layouts, they have been evaluated on different\nproperties like symmetry, node overlapping, and anatomical resemblence. Additionally,\nwe conducted an open discussion with collaborators of the Research Institute of Molecular Pathology (IMP) in Vienna and present the results.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 220, "image_height": 180, "name": "Rippberger_2019-image.JPG", "type": "image/jpeg", "size": 18446, "path": "Publication:Rippberger_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Rippberger_2019/Rippberger_2019-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Rippberger_2019/Rippberger_2019-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1648 ], "date_end": "2019-04-18", "date_start": "2018-10-10", "matrikelnr": "01307685", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Rippberger_2019-Bachelor Thesis.pdf", "type": "application/pdf", "size": 19036695, "path": "Publication:Rippberger_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Rippberger_2019/Rippberger_2019-Bachelor Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Rippberger_2019/Rippberger_2019-Bachelor Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 220, "image_height": 180, "name": "Rippberger_2019-image.JPG", "type": "image/jpeg", "size": 18446, "path": "Publication:Rippberger_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Rippberger_2019/Rippberger_2019-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Rippberger_2019/Rippberger_2019-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Rippberger_2019/", "__class": "Publication" }, { "id": "vasileva-2019-smw", "type_id": "poster", "tu_id": 283326, "repositum_id": null, "title": "OptiRoute: Interactive Maps for Wayfinding in a Complex Environment", "date": "2019-04-11", "abstract": "Visitors to amusement parks use mobile map appli- cations to decide where to go and to plan efficient routes. Such applications are especially helpful when visitors wish to avoid re-tracking their steps or visiting regions in the park several times. Visitors have limited time in the park, which typically covers a very large area, and the attractions have waiting times of varying duration. Time management is therefore important. In this paper, we propose a new visualization technique to support such route decision making, using an interactive environment. The main contribution of our system, OptiRoute, is the automatic computation of an optimal route between selected attractions as well as its effective visualization, which focuses on reducing visual clutter. This is achieved by improving the branch and bound route-finding algorithm, and introducing an intersection minimization algorithm for route representation. We demonstrate the feasibility of our approach through a case study of Tokyo Disneyland, in addition to a user study.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1068, "image_height": 726, "name": "vasileva-2019-smw-image.png", "type": "image/png", "size": 255384, "path": "Publication:vasileva-2019-smw", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/vasileva-2019-smw/vasileva-2019-smw-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/vasileva-2019-smw/vasileva-2019-smw-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1593, 1464 ], "cfp": { "name": "sm2019.pdf", "type": "application/pdf", "error": "0", "size": "78789", "orig_name": "sm2019.pdf", "ext": "pdf" }, "date_from": "2019", "date_to": "2019", "event": "schematic Mapping Workshop 2019", "note": "Best Poster Award", "research_areas": [ "InfoVis" ], "keywords": [ " Maps", "Route finding", "Wayfinding" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1068, "image_height": 726, "name": "vasileva-2019-smw-image.png", "type": "image/png", "size": 255384, "path": "Publication:vasileva-2019-smw", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/vasileva-2019-smw/vasileva-2019-smw-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/vasileva-2019-smw/vasileva-2019-smw-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "vasileva-2019-smw-paper.pdf", "type": "application/pdf", "size": 357111, "path": "Publication:vasileva-2019-smw", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/vasileva-2019-smw/vasileva-2019-smw-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/vasileva-2019-smw/vasileva-2019-smw-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/vasileva-2019-smw/", "__class": "Publication" }, { "id": "wu-2019-smw", "type_id": "WorkshopTalk", "tu_id": null, "repositum_id": null, "title": " A Survey on Computing Schematic Network Maps: The Challenge to Interactivity", "date": "2019-04-11", "abstract": "Schematic maps are in daily use to show the connec- tivity of subway systems and to facilitate travellers to plan their journeys effectively. This study surveys up-to-date algorithmic approaches in order to give an overview of the state of the art in schematic network mapping. The study investigates the hypothesis that the choice of algorithmic approach is often guided by the requirements of the mapping application. For example, an algorithm that computes globally optimal solutions for schematic maps is capable of producing results for printing, while it is not suitable for computing instant layouts due to its long running time. Our analysis and discussion, therefore, focus on the compu- tational complexity of the problem formulation and the running times of the schematic map algorithms, including algorithmic network layout techniques and station labeling techniques. The correlation between problem complexity and running time is then visually depicted using scatter plot diagrams. Moreover, since metro maps are common metaphors for data visualization, we also investigate online tools and application domains using metro map representations for analytics purposes, and finally summarize the potential future opportunities for schematic maps.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-smw-image.png", "type": "image/png", "size": 36787, "path": "Publication:wu-2019-smw", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1675, 1580, 1579 ], "cfp": { "name": "sm2019.pdf", "type": "application/pdf", "error": "0", "size": "78789", "orig_name": "sm2019.pdf", "ext": "pdf" }, "doi": "https://www.ac.tuwien.ac.at/files/pub/smw19-position-5.pdf", "event": "The 2nd Schematic Mapping Workshop 2019", "lecturer": [ 1464 ], "location": "Vienna, Austria", "research_areas": [ "InfoVis" ], "keywords": [ "Metro Maps", "Graph Drawing", "Metaphors" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-smw-image.png", "type": "image/png", "size": 36787, "path": "Publication:wu-2019-smw", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2019-smw-paper.pdf", "type": "application/pdf", "size": 2849219, "path": "Publication:wu-2019-smw", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/", "__class": "Publication" }, { "id": "wu-2019-smwp", "type_id": "poster", "tu_id": 283325, "repositum_id": null, "title": "Aspect-Ratio-Preserved Labeling on Metro Maps", "date": "2019-04-11", "abstract": "For better readability, metro lines are often aligned along the octilinear directions. Predefined layouts, however, limit the feasibility of placing station name labels. In this paper, we present a novel approach to automating the placement of station names around a schematic network while maximally respecting its original layout as the mental map. The idea behind the proposed approach is to progressively annotate stations from congested central downtown areas to sparse rural areas by intro- ducing the sum of geodesic distances over the network to identify the proper order of stations to be annotated. Our approach elongates line segments of the network without changing their directions to spare labeling space around the station. Additional constraints are introduced to restrict the aspect ratios of the region confined by the metro network for better preservation of the mental map in the original schematic layout.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 205, "name": "wu-2019-smwp-image.png", "type": "image/png", "size": 27213, "path": "Publication:wu-2019-smwp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smwp/wu-2019-smwp-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smwp/wu-2019-smwp-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1625, 1626, 1676, 1627, 1580 ], "cfp": { "name": "sm2019.pdf", "type": "application/pdf", "error": "0", "size": "78789", "orig_name": "sm2019.pdf", "ext": "pdf" }, "date_from": "2019", "date_to": "2019", "doi": "https://www.ac.tuwien.ac.at/files/pub/smw19-paper-5.pdf", "event": "Schematic Mapping Workshop 2019", "research_areas": [ "InfoVis" ], "keywords": [ "Progressive Annotation", "Geodesic Distances", "Schematic Layout", "Mental Maps", "Mixed-Integer Programming" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 205, "name": "wu-2019-smwp-image.png", "type": "image/png", "size": 27213, "path": "Publication:wu-2019-smwp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smwp/wu-2019-smwp-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smwp/wu-2019-smwp-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "wu-2019-smwp-paper.pdf", "type": "application/pdf", "size": 401145, "path": "Publication:wu-2019-smwp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smwp/wu-2019-smwp-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smwp/wu-2019-smwp-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smwp/", "__class": "Publication" }, { "id": "samoul-2019-cnp", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Visual Comparison of NLP Pipelines", "date": "2019-04", "abstract": "Natural Language Processing (NLP) is a sub-field of artificial intelligence (AI). It enables computers to understand, process\nand analyze large amounts of unstructured natural language data (raw text). Nowadays with the new techniques of machine\nlearning, we got good performance and brings us closer to unfolding the semantic meaning of the text. However, it is far\nfrom perfect. Therefore, an alternative approach to helping humans understand a text corpus is to provide a visualization of the\ncontent. To generate such a visualization, several NLP steps are necessary to convert the raw text into features, such as weighted\nkeywords or phrases, that can be visualized. The words to be visualized and their weights strongly depend on which NLP steps\nare performed, in which order, and with which parameters. However, there is currently no standard how to set up such an\nNLP pipeline and NLP pipeline configurations vary significantly across visualizations and input texts. Our project consists of\nvisualizing high dimensional data with different pre-processing steps with a different order. To compare the results, we choose\na well-known and wide-spread overview visualization technique: word clouds. Word clouds are composed of words used in a\nparticular text or subject, in which the size of each word indicates its weight computed in the course of the NLP pipeline.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1599, "image_height": 754, "name": "samoul-2019-cnp-screenshot.jpg", "type": "image/jpeg", "size": 415531, "path": "Publication:samoul-2019-cnp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-screenshot.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1644 ], "date_end": "2019-04", "date_start": "2018-11", "matrikelnr": "11833154", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Report", "main_file": false, "use_in_gallery": false, "access": "public", "name": "samoul-2019-cnp-Report.pdf", "type": "application/pdf", "size": 538545, "path": "Publication:samoul-2019-cnp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-Report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-Report:thumb{{size}}.png" }, { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1599, "image_height": 754, "name": "samoul-2019-cnp-screenshot.jpg", "type": "image/jpeg", "size": 415531, "path": "Publication:samoul-2019-cnp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-screenshot.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-screenshot:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/", "__class": "Publication" }, { "id": "wu-2019-report", "type_id": "techreport", "tu_id": 283365, "repositum_id": null, "title": "From Cells to Atoms - Biological Information Visualization (in Chinese)", "date": "2019-03-01", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1263, 171 ], "number": "TR-193-02-2019-1", "open_access": "no", "research_areas": [ "BioVis", "IllVis", "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://dl.ccf.org.cn/institude/institudeDetail?id=4320599515842560&_ack=1", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2019-report-paper.pdf", "type": "application/pdf", "size": 8399742, "path": "Publication:wu-2019-report", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/wu-2019-report-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/wu-2019-report-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/", "__class": "Publication" }, { "id": "raidou2019_prsps", "type_id": "journalpaper", "tu_id": 283349, "repositum_id": null, "title": "Relaxing Dense Scatter Plots with Pixel-Based Mappings", "date": "2019-03", "abstract": "Scatter plots are the most commonly employed technique for the visualization of bivariate data. Despite their versatility and expressiveness in showing data aspects, such as clusters, correlations, and outliers, scatter plots face a main problem. For large and dense data, the representation suffers from clutter due to overplotting. This is often partially solved with the use of density plots. Yet, data overlap may occur in certain regions of a scatter or density plot, while other regions may be partially, or even completely empty. Adequate pixel-based techniques can be employed for effectively filling the plotting space, giving an additional notion of the numerosity of data motifs or clusters. We propose the Pixel-Relaxed Scatter Plots, a new and simple variant, to improve the display of dense scatter plots, using pixel-based, space-filling mappings. Our Pixel-Relaxed Scatter Plots make better use of the plotting canvas, while avoiding data overplotting, and optimizing space coverage and insight in the presence and size of data motifs. We have employed different methods to map scatter plot points to pixels and to visually present this mapping. We demonstrate our approach on several synthetic and realistic datasets, and we discuss the suitability of our technique for different tasks. Our conducted user evaluation shows that our Pixel-Relaxed Scatter Plots can be a useful enhancement to traditional scatter plots.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 166, 1451 ], "cfp": { "name": "PacificVis 2019.pdf", "type": "application/pdf", "error": "0", "size": "380233", "orig_name": "PacificVis 2019.pdf", "ext": "pdf" }, "date_from": "2019-03-18", "date_to": "2019-03-18", "doi": "10.1109/TVCG.2019.2903956", "event": "PacificVis 2019", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 1410 ], "pages_from": "1", "pages_to": "12", "volume": "25", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 1548, "preview_image_height": 877, "name": "raidou2019_prsps-paper.pdf", "type": "application/pdf", "size": 5294590, "path": "Publication:raidou2019_prsps", "preview_name": "raidou2019_prsps-paper:preview.JPG", "preview_type": "image/jpeg", "preview_size": 274161, "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou2019_prsps/raidou2019_prsps-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou2019_prsps/raidou2019_prsps-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/raidou2019_prsps/", "__class": "Publication" }, { "id": "waldin-2019-ccm", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Cuttlefish: Color Mapping for Dynamic Multi‐Scale Visualizations", "date": "2019-03", "abstract": "Visualizations of hierarchical data can often be explored interactively. For example, in geographic visualization, there are continents, which can be subdivided into countries, states, counties and cities. Similarly, in models of viruses or bacteria at the highest level are the compartments, and below that are macromolecules, secondary structures (such as α‐helices), amino‐acids, and on the finest level atoms. Distinguishing between items can be assisted through the use of color at all levels. However, currently, there are no hierarchical and adaptive color mapping techniques for very large multi‐scale visualizations that can be explored interactively. We present a novel, multi‐scale, color‐mapping technique for adaptively adjusting the color scheme to the current view and scale. Color is treated as a resource and is smoothly redistributed. The distribution adjusts to the scale of the currently observed detail and maximizes the color range utilization given current viewing requirements. Thus, we ensure that the user is able to distinguish items on any level, even if the color is not constant for a particular feature. The coloring technique is demonstrated for a political map and a mesoscale structural model of HIV. The technique has been tested by users with expertise in structural biology and was overall well received.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Multiple color zoom levels. ", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 509, "image_height": 447, "name": "waldin-2019-ccm-teaser.png", "type": "image/png", "size": 690229, "path": "Publication:waldin-2019-ccm", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldin-2019-ccm/waldin-2019-ccm-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldin-2019-ccm/waldin-2019-ccm-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1339, 1110, 1189, 166, 1365, 1260, 1475, 171 ], "doi": "10.1111/cgf.13611", "journal": "Computer Graphics Forum", "number": "6", "pages_from": "150", "pages_to": "164", "volume": "38", "research_areas": [ "BioVis", "IllVis", "InfoVis" ], "keywords": [ "multiscale visualization", "illustrative visualization", "molecular visualization" ], "weblinks": [ { "href": "https://onlinelibrary.wiley.com/doi/10.1111/cgf.13611", "caption": "Open Access Article in Wiley Online Library", "description": null, "main_file": 1 } ], "files": [ { "description": "Multiple color zoom levels. ", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 509, "image_height": 447, "name": "waldin-2019-ccm-teaser.png", "type": "image/png", "size": 690229, "path": "Publication:waldin-2019-ccm", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldin-2019-ccm/waldin-2019-ccm-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldin-2019-ccm/waldin-2019-ccm-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis", "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldin-2019-ccm/", "__class": "Publication" }, { "id": "STEINLECHNER-2019-ICT", "type_id": "inproceedings", "tu_id": 283451, "repositum_id": null, "title": "A Novel Approach for Immediate, Interactive CT Data Visualization andEvaluation using GPU-based Segmentation and Visual Analysis", "date": "2019-02", "abstract": "CT data of industrially produced cast metal parts are often afflicted\nwith artefacts due to complex geometries ill-suited for the scanning\nprocess. Simple global threshold-based porosity detection algorithms\nusually fail to deliver meaningful results. Other adaptive methods can\nhandle image artefacts, but require long preprocessing times. This makes\nan efficient analysis workflow infeasible. We propose an alternative\napproach for analyzing and visualizing volume defects in a fully\ninteractive manner, where analyzing volumes becomes more of an\ninteractive exploration instead of time-consuming parameter guessing\ninterrupted by long processing times. Our system is based on a highly\nefficient GPU implementation of a segmentation algorithm for porosity\ndetection. The runtime is on the order of seconds for a full volume and\nparametrization is kept simple due to a single threshold parameter. A\nfully interactive user interface comprised of multiple linked views\nallows to quickly identify defects of interest, while filtering out\nartefacts even in noisy areas.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1680, "image_height": 1011, "name": "STEINLECHNER-2019-ICT-teaser.png", "type": "image/png", "size": 791896, "path": "Publication:STEINLECHNER-2019-ICT", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/STEINLECHNER-2019-ICT/STEINLECHNER-2019-ICT-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/STEINLECHNER-2019-ICT/STEINLECHNER-2019-ICT-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1387, 1640, 1641, 1642, 228, 678, 166 ], "booktitle": "International Conference on Industrial Computed Tomography (ICT) 2019", "cfp": { "name": "ICT 2019 call for papers.pdf", "type": "application/pdf", "error": "0", "size": "219852", "orig_name": "ICT 2019 call for papers.pdf", "ext": "pdf" }, "date_from": "2019-02-13", "date_to": "2019-02-15", "editor": "Simone Carmignato", "event": "International Conference on Industrial Computed Tomography (ICT) 2019", "lecturer": [ 1387 ], "location": "Padova, Italy", "pages_from": "1", "pages_to": "6", "research_areas": [ "InfoVis", "Rendering" ], "keywords": [ "CT", "GPU", "Inclusion Detection", "Interactive Visualisation", "VisualAnalysis", "Parallel Coordinates", "Volume Rendering" ], "weblinks": [], "files": [ { "description": null, "filetitle": "draft", "main_file": true, "use_in_gallery": false, "access": "public", "name": "STEINLECHNER-2019-ICT-draft.pdf", "type": "application/pdf", "size": 9584761, "path": "Publication:STEINLECHNER-2019-ICT", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/STEINLECHNER-2019-ICT/STEINLECHNER-2019-ICT-draft.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/STEINLECHNER-2019-ICT/STEINLECHNER-2019-ICT-draft:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1680, "image_height": 1011, "name": "STEINLECHNER-2019-ICT-teaser.png", "type": "image/png", "size": 791896, "path": "Publication:STEINLECHNER-2019-ICT", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/STEINLECHNER-2019-ICT/STEINLECHNER-2019-ICT-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/STEINLECHNER-2019-ICT/STEINLECHNER-2019-ICT-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis", "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/STEINLECHNER-2019-ICT/", "__class": "Publication" }, { "id": "unger-2019_vcp", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Visual Comparison of Organism-Specific Metabolic Pathways", "date": "2019-02", "abstract": "The Kyoto Encyclopaedia of Genes and Genomes\n(KEGG) resource is a combination of multiple databases,\ncontaining information about biochemical compounds, reactions,\npathways, genes and much more. This database\nis one of the main resources for bioinformaticians and biologists\nto gain an understanding of molecular functionality\ninside organisms. The Orthology (KO) database from\nKEGG assigns pathways and genes with identical functionality\nto the same ortholog groups (KO entries). Therefore\nit is possible to map genes onto the pathway maps\nand obtain organism-specific visualizations. KEGG offers\na web-based graph visualization to explore these pathways,\nhowever, the interaction possibilities are restricted\nand the rendering is inefficient. It is possible to visualize\norganism-specific pathways but a visual analysis tool to\ncompare ortholog groups of multiple organisms is missing.\nIn this work, we present an efficient interactive web application\nto compare ortholog groups of multiple organisms\nin the metabolic reference pathway. We introduce a graph\noverlay technique to mark the differences and similarities\nbetween multiple organisms and demonstrate it with two\nuse cases. Additionally, we compare it against an existing\npoint set membership visualization.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1117, "image_height": 742, "name": "unger-2019_vcp-screenshot.png", "type": "image/png", "size": 563486, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1530 ], "date_end": "2019-02", "date_start": "2018-10", "matrikelnr": "01325652", "supervisor": [ 1110 ], "research_areas": [ "BioVis", "InfoVis" ], "keywords": [ "pathways", "web-based visualization" ], "weblinks": [ { "href": "https://users.cg.tuwien.ac.at/kunger/pr-pathway-exploration/", "caption": "Online tool", "description": "Best to be used with Chrome. Enter the organisms to be compared by entering them as a string like this: \"eco+hsa+mmu\" (compares E-Coli, Homo Sapiens, and Mus Musculus). ", "main_file": 0 }, { "href": "https://www.genome.jp/kegg/catalog/org_list.html", "caption": "List of KEGG organisms", "description": "List of organisms available in KEGG. ", "main_file": 0 }, { "href": "https://cescg.org/cescg_submission/visual-comparison-of-organism-specific-metabolic-pathways/", "caption": "CESCG paper", "description": "Paper presented at the Central European Seminar on Computer Graphics 2019. ", "main_file": 0 } ], "files": [ { "description": null, "filetitle": "CESCG paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "unger-2019_vcp-CESCG paper.pdf", "type": "application/pdf", "size": 4980072, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-CESCG paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-CESCG paper:thumb{{size}}.png" }, { "description": null, "filetitle": "developer documentation", "main_file": false, "use_in_gallery": false, "access": "public", "name": "unger-2019_vcp-developer documentation.pdf", "type": "application/pdf", "size": 524187, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-developer documentation.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-developer documentation:thumb{{size}}.png" }, { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1117, "image_height": 742, "name": "unger-2019_vcp-screenshot.png", "type": "image/png", "size": 563486, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-screenshot:thumb{{size}}.png" }, { "description": null, "filetitle": "user documentation", "main_file": false, "use_in_gallery": false, "access": "public", "name": "unger-2019_vcp-user documentation.pdf", "type": "application/pdf", "size": 58613, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-user documentation.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-user documentation:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/", "__class": "Publication" }, { "id": "YOGHOURDJIAN2019", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Exploring the limits of complexity: A survey of empirical studies ongraph visualisation", "date": "2019-01-06", "abstract": "For decades, researchers in information visualisation and graph drawing\nhave focused on developing techniques for the layout and display of very\nlarge and complex networks. Experiments involving human participants\nhave also explored the readability of different styles of layout and\nrepresentations for such networks. In both bodies of literature,\nnetworks are frequently referred to as being ‘large’ or ‘complex’, yet\nthese terms are relative. From a human-centred, experiment\npoint-of-view, what constitutes ‘large’ (for example) depends on several\nfactors, such as data complexity, visual complexity, and the technology\nused. In this paper, we survey the literature on human-centred\nexperiments to understand how, in practice, different features and\ncharacteristics of node–link diagrams affect visual complexity.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "YOGHOURDJIAN2019-image.png", "type": "image/png", "size": 40040, "path": "Publication:YOGHOURDJIAN2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/YOGHOURDJIAN2019-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/YOGHOURDJIAN2019-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1618, 1619, 1620, 1621, 1622, 1623, 1464 ], "doi": "https://doi.org/10.1016/j.visinf.2018.12.006", "issn": "2468-502X", "journal": "Visual Informatics", "number": "4", "open_access": "yes", "pages_from": "264", "pages_to": "282", "volume": "2", "research_areas": [ "InfoVis" ], "keywords": [ "Graph visualisation", "Network visualisation", "node–link diagrams", "Evaluations", "Empirical studies", "Cognitive scalability" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "YOGHOURDJIAN2019-image.png", "type": "image/png", "size": 40040, "path": "Publication:YOGHOURDJIAN2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/YOGHOURDJIAN2019-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/YOGHOURDJIAN2019-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "YOGHOURDJIAN2019-paper.pdf", "type": "application/pdf", "size": 2324636, "path": "Publication:YOGHOURDJIAN2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/YOGHOURDJIAN2019-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/YOGHOURDJIAN2019-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/", "__class": "Publication" }, { "id": "hromniak-2019-vcn", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visual Comparison of Natural Language Processing Pipelines", "date": "2019-01", "abstract": "Natural Language Processing comprises a variety of operations that can be applied on\nraw text to extract features. The sequence of operations is called NLP pipeline. However,\nthe sequence and parameters of these individual operations differ between applications.\nIn each step of the ongoing sequence, a single process is performed with a specialized task.\nSuch a task can be the determination of the end of sentences or the removal of so-called\nstop words. There is no best-practice which combination is most effective and accurate\nto determine the descriptive features (key words) of a single document. The goal of this\nbachelor thesis is to compute the features of different variations of NLP pipelines and\nvisualize them as basic word clouds. It is also important to know how the resulting word\ncloud of each pipeline is affected by varying the order of certain steps, adding steps or\nremoving steps. The presented interface gives an overview of performance and similarity\nvalues of each computed pipeline.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 512, "image_height": 486, "name": "hromniak-2019-vcn-screenshot.png", "type": "image/png", "size": 37562, "path": "Publication:hromniak-2019-vcn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1556 ], "date_end": "2019-01", "date_start": "2018-04", "matrikelnr": "1425731", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": { "1": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 512, "image_height": 486, "name": "hromniak-2019-vcn-screenshot.png", "type": "image/png", "size": 37562, "path": "Publication:hromniak-2019-vcn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-screenshot:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "hromniak-2019-vcn-thesis.pdf", "type": "application/pdf", "size": 1302404, "path": "Publication:hromniak-2019-vcn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/", "__class": "Publication" }, { "id": "wu-2018-shonan", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Lost in Translation: Alignment of Mental Representations for Visual Analytics, Reimagining the Mental Map and Drawing Stability (NII Shonan Meeting Seminar 127)", "date": "2018-12", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1619, 1680, 1681, 1682, 1683, 1684, 1464 ], "number": "TR-193-02-2018-1", "open_access": "yes", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2018-shonan-paper.pdf", "type": "application/pdf", "size": 1672636, "path": "Publication:wu-2018-shonan", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-shonan/wu-2018-shonan-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-shonan/wu-2018-shonan-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-shonan/", "__class": "Publication" }, { "id": "Vasileva-2018", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Interactive Maps for Visualizing Optimal Route Planning Strategy", "date": "2018-10-26", "abstract": "There are many situations in our everyday life like events, concerts, landmarks, attraction parks, etc. that often require from visitors to line-up in front of long queues and thus spend hours in waiting. An example of that are the Disneyland amusement parks. They are all very popular and attract a significant number of people every day. For this reason, the lining-up in front of attractions may cost much time – even up to a couple of hours. Despite that, the Disneyland parks are visited by millions of people every year [sta].\nSo to avoid so much waiting they need to make a plan in advance – when and in which\norder to visit the wanted attractions. However, to make such a plan, it could be very time consuming, difficult and even unpleasant, because many prerequisites need to be considered in advance. Having the main problems and annoyances described, the goal of this thesis is to create an assisting application. Its purpose is to give the visitors the possibility to create their own plan for their visit to Tokyo Disneyland. It contains two main assisting components. Firstly, an optimization algorithm calculating an optimized\nroute of the chosen attractions as well as a route visualization for an easy attraction finding. Both will reduce the time for lining-up and pre-planning. Such a technique will make it easier for visitors to see as many attractions as possible for a single day and thus, make the most of their visit.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 192, "image_height": 337, "name": "Vasileva-2018-image.PNG", "type": "image/png", "size": 95697, "path": "Publication:Vasileva-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Vasileva-2018/Vasileva-2018-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Vasileva-2018/Vasileva-2018-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1593 ], "date_end": "2018-10-26", "date_start": "2018-05-23", "matrikelnr": "01426939", "supervisor": [ 1464 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor Thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Vasileva-2018-Bachelor Thesis.pdf", "type": "application/pdf", "size": 7087860, "path": "Publication:Vasileva-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Vasileva-2018/Vasileva-2018-Bachelor Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Vasileva-2018/Vasileva-2018-Bachelor Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 192, "image_height": 337, "name": "Vasileva-2018-image.PNG", "type": "image/png", "size": 95697, "path": "Publication:Vasileva-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Vasileva-2018/Vasileva-2018-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Vasileva-2018/Vasileva-2018-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Vasileva-2018/", "__class": "Publication" }, { "id": "Deutsch-2018", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Generating seating plan images using clustering and concave hull algorithms", "date": "2018-10-21", "abstract": "This study presents a process of generating seating plan images for the Ticket Gretchen\napp. The app offers the ability to buy tickets for theaters and similar venues by using\nan interactive seating plan. A seating plan image is a venue’s abstract visualization\ndefined by the seating layout of a performance. It should give an impression of the spatial\nstructure to see which seats are in reach of each other. The proposed automated solution\nof generating these images replaces the previously used process of creating the seating\nplan images manually. The image is made up of polygons representing seat groups that\nshow the user which seats are near each other and which are separated from each other.\nThe grouping of seats is done with the DBSCAN clustering algorithm using the seats’ 2D\nposition, sector and box information. For the computation of the polygons two concave\nhull algorithms are compared.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1000, "image_height": 953, "name": "Deutsch-2018-image.png", "type": "image/png", "size": 78508, "path": "Publication:Deutsch-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Deutsch-2018/Deutsch-2018-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Deutsch-2018/Deutsch-2018-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1592 ], "date_end": "2018-10-21", "date_start": "2018-05-23", "matrikelnr": "01327587", "supervisor": [ 1464 ], "research_areas": [ "IllVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor Thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Deutsch-2018-Bachelor Thesis.pdf", "type": "application/pdf", "size": 6601116, "path": "Publication:Deutsch-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Deutsch-2018/Deutsch-2018-Bachelor Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Deutsch-2018/Deutsch-2018-Bachelor Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1000, "image_height": 953, "name": "Deutsch-2018-image.png", "type": "image/png", "size": 78508, "path": "Publication:Deutsch-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Deutsch-2018/Deutsch-2018-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Deutsch-2018/Deutsch-2018-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Deutsch-2018/", "__class": "Publication" }, { "id": "edlinger-2018-vwr", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visually Linking web search results with bookmarked information", "date": "2018-10", "abstract": "This work presents a new approach of regaining access to stored information and for the visualization of similarities between new information and locally stored data. The fact that bookmarks are cumbersome to use and that there is no possibility to compare web search results with local information motivates the concept of this thesis. The\nimplementation was done as Google Chrome extension and based on the ’Information\nCollage’ environment. In order to improve the perceived ease of use, the visualization was integrated in the search engine results page to avoid a context switch for the user. The\nvisualization uses a word cloud to display similarities and differences between remote and\nlocal information. The word cloud layout focuses on the spatial arrangment and the text\ncolour of the words to encode their association to the remote or the local information.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 761, "image_height": 758, "name": "edlinger-2018-vwr-teaser.png", "type": "image/png", "size": 267653, "path": "Publication:edlinger-2018-vwr", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1465 ], "date_end": "2018-10", "date_start": "2017-06", "matrikelnr": "1027088", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 761, "image_height": 758, "name": "edlinger-2018-vwr-teaser.png", "type": "image/png", "size": 267653, "path": "Publication:edlinger-2018-vwr", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "edlinger-2018-vwr-thesis.pdf", "type": "application/pdf", "size": 9699891, "path": "Publication:edlinger-2018-vwr", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/", "__class": "Publication" }, { "id": "steinboeck-2018-lbg", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Casual Visual Exploration of Large Bipartite Graphs Using Hierarchical Aggregation and Filtering", "date": "2018-10", "abstract": "Bipartite graphs are typically visualized using linked\nlists or matrices. However, these classic visualization techniques\ndo not scale well with the number of nodes. Biclustering has\nbeen used to aggregate edges, but not to create linked lists\nwith thousands of nodes. In this paper, we present a new\ncasual exploration interface for large, weighted bipartite graphs,\nwhich allows for multi-scale exploration through hierarchical\naggregation of nodes and edges using biclustering in linked\nlists. We demonstrate the usefulness of the technique using two\ndata sets: a database of media advertising expenses of public\nauthorities and author-keyword co-occurrences from the IEEE\nVisualization Publication collection. Through an insight-based\nstudy with lay users, we show that the biclustering interface leads\nto longer exploration times, more insights, and more unexpected\nfindings than a baseline interface using only filtering. However,\nusers also perceive the biclustering interface as more complex.", "authors_et_al": false, "substitute": null, "main_image": { "description": "BiCFlows showing visualization authors and their key words", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 708, "image_height": 702, "name": "steinboeck-2018-lbg-teaser.png", "type": "image/png", "size": 137906, "path": "Publication:steinboeck-2018-lbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1378, 166, 1110 ], "booktitle": "International Symposium on Big Data Visual and Immersive Analytics", "event": "4th International Symposium on Big Data Visual and Immersive Analytics", "lecturer": [ 1110 ], "location": "Konstanz, Germany", "organization": "IEEE", "research_areas": [ "InfoVis", "NetVis" ], "keywords": [ "information visualization", "bipartite graphs", "biclustering", "insight-based evaluation" ], "weblinks": [ { "href": "https://users.cg.tuwien.ac.at/~waldner/bicflows/", "caption": "BiCFlows online", "description": "BiCFlows online for exploring Austria's media transparency database and the IEEE Visualization paper authors and their key words. ", "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "steinboeck-2018-lbg-paper.pdf", "type": "application/pdf", "size": 1871535, "path": "Publication:steinboeck-2018-lbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-paper:thumb{{size}}.png" }, { "description": "BiCFlows showing visualization authors and their key words", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 708, "image_height": 702, "name": "steinboeck-2018-lbg-teaser.png", "type": "image/png", "size": 137906, "path": "Publication:steinboeck-2018-lbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/", "__class": "Publication" }, { "id": "klaffenboeck-thesis", "type_id": "runphdthesis", "tu_id": null, "repositum_id": null, "title": "(untitled)", "date": "2018-09", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1598 ], "date_start": "2018-09", "duration": "2018-ongoing", "matrikelnr": "00301042", "supervisor": [ 193 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/klaffenboeck-thesis/", "__class": "Publication" }, { "id": "Muehlbacher_diss_2018", "type_id": "phdthesis", "tu_id": null, "repositum_id": null, "title": "Human-Oriented Statistical Modeling: Making Algorithms Accessible through Interactive Visualization", "date": "2018-08-30", "abstract": "Statistical modeling is a key technology for generating business value from data. While the number of available algorithms and the need for them is growing, the number of people with the skills to effectively use such methods lags behind. Many application domain experts find it hard to use and trust algorithms that come as black boxes with insufficient interfaces to adapt. The field of Visual Analytics aims to solve this problem by a human-oriented approach that puts users in control of algorithms through interactive\nvisual interfaces. However, designing accessible solutions for a broad set of users while re-using existing, proven algorithms poses significant challenges for the design of analytical infrastructures, visualizations, and interactions.\nThis thesis provides multiple contributions towards a more human-oriented modeling\nprocess: As a theoretical basis, it investigates how user involvement during the execution of algorithms can be realized from a technical perspective. Based on a characterization of needs regarding intermediate feedback and control, a set of formal strategies to realize user involvement in algorithms with different characteristics is presented. Guidelines\nfor the design of algorithmic APIs are identified, and requirements for the re-use of algorithms are discussed. From a survey of frequently used algorithms within R, the\nthesis concludes that a range of pragmatic options for enabling user involvement in new and existing algorithms exist and should be used. After these conceptual considerations, the thesis presents two methodological contributions that demonstrate how even inexperienced modelers can be effectively involved in the\nmodeling process. First, a new technique called TreePOD guides the selection of decision trees along trade-offs between accuracy and other objectives, such as interpretability.\nUsers can interactively explore a diverse set of candidate models generated by sampling the parameters of tree construction algorithms. Visualizations provide an overview of possible tree characteristics and guide model selection, while details on the underlying machine learning process are only exposed on demand. Real-world evaluation with\ndomain experts in the energy sector suggests that TreePOD enables users with and without statistical background a confident identification of suitable decision trees. As the second methodological contribution, the thesis presents a framework for interactive\nbuilding and validation of regression models. The framework addresses limitations of automated regression algorithms regarding the incorporation of domain knowledge, identifying local dependencies, and building trust in the models. Candidate variables for model refinement are ranked, and their relationship with the target variable is visualized to support an interactive workflow of building regression models. A real-world case study and feedback from domain experts in the energy sector indicate a significant effort\nreduction and increased transparency of the modeling process.\nAll methodological contributions of this work were implemented as part of a commercially distributed Visual Analytics software called Visplore. As the last contribution, this thesis reflects upon years of experience in deploying Visplore for modeling-related tasks in the energy sector. Dissemination and adoption are important aspects of making statistical\nmodels more accessible for domain experts, making this work relevant for practitioners\nand application-oriented researchers alike.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 306, "image_height": 284, "name": "Muehlbacher_diss_2018-image.PNG", "type": "image/png", "size": 34227, "path": "Publication:Muehlbacher_diss_2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Muehlbacher_diss_2018/Muehlbacher_diss_2018-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Muehlbacher_diss_2018/Muehlbacher_diss_2018-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 804 ], "co_supervisor": [ 451 ], "date_end": "2018-08", "date_start": "2012-06", "matrikelnr": "0625075", "reviewer_1": [ 176 ], "reviewer_2": [ 1144 ], "rigorosum": "2018-11-09", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 306, "image_height": 284, "name": "Muehlbacher_diss_2018-image.PNG", "type": "image/png", "size": 34227, "path": "Publication:Muehlbacher_diss_2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Muehlbacher_diss_2018/Muehlbacher_diss_2018-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Muehlbacher_diss_2018/Muehlbacher_diss_2018-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis", "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Muehlbacher_diss_2018/", "__class": "Publication" }, { "id": "Eckelt_2018_01", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Data-Driven User Guidance in Multi-Attribute Data Exploration", "date": "2018-08-18", "abstract": "Seeking relationships in multi-dimensional datasets is a common task, but can quickly\nbecome tedious due to the heterogeneity and increasing size of the data. Its visualization can be approached in a variety of ways: (i) projection techniques decrease the number of dimensions to a fraction before visualizing items, creating clusters where similarities in the high-level space may be derived; (ii) overview visualization techniques display selected\nattributes and all of their items’ values to discover patterns and find relationships; (iii) tabular techniques give an insight into the individual items and thus favor their detailed\nanalysis and exploration.\nHowever, while the interactive selection of a data subset during exploration is most easily done with tabular visualizations, finding relationships and patterns is not. Also, with overview techniques the number of attribute combinations quickly outgrows reasonable dimensions.\nIn this thesis, a data-driven touring process for Visual Analytics (VA) tools is presented that guides users in discovering relationships for a data subset of their interest. Based on the user’s selection, attributes that show some kind of similarity are presented. The selection can be done on attribute and item level. While a selected attribute is compared to all other attributes in the dataset, item sets are compared to the individual\ncategories of attributes. This comparison can be based on a number of similarity measures.\nTo cope with heterogeneity of data types, numerical attributes are discretized to achieve maximum similarity. In hierarchical attributes, the most similar subtree is sought. The touring process is also independent of the data domain and its visualization. This independence is demonstrated by the use of three different datasets and the integration of the touring process into two VA systems. These extended systems were shown to medical experts of the Kepler University Hospital, who will use them in the near future. Their feedback was incorporated to improve the guidance process.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 574, "image_height": 317, "name": "Eckelt_2018_01-image.JPG", "type": "image/jpeg", "size": 32290, "path": "Publication:Eckelt_2018_01", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Eckelt_2018_01/Eckelt_2018_01-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Eckelt_2018_01/Eckelt_2018_01-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1401 ], "date_end": "2018-08-18", "date_start": "2018-01-03", "matrikelnr": "1127705", "open_access": "yes", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 574, "image_height": 317, "name": "Eckelt_2018_01-image.JPG", "type": "image/jpeg", "size": 32290, "path": "Publication:Eckelt_2018_01", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Eckelt_2018_01/Eckelt_2018_01-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Eckelt_2018_01/Eckelt_2018_01-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Eckelt_2018_01-Master thesis.pdf", "type": "application/pdf", "size": 12430400, "path": "Publication:Eckelt_2018_01", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Eckelt_2018_01/Eckelt_2018_01-Master thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Eckelt_2018_01/Eckelt_2018_01-Master thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Eckelt_2018_01-Poster.pdf", "type": "application/pdf", "size": 343124, "path": "Publication:Eckelt_2018_01", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Eckelt_2018_01/Eckelt_2018_01-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Eckelt_2018_01/Eckelt_2018_01-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Eckelt_2018_01/", "__class": "Publication" }, { "id": "8564188", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Progressive Annotation of Schematic Railway Maps", "date": "2018-07", "abstract": "Octilinear network layouts are commonly used as the schematic\nrepresentation of railway maps due to their enhanced readability.\nHowever, it is often time-consuming to place station names on such\nrailway maps by trial and error, especially within the limited labeling\nspace around interchange stations. This paper presents a progressive\napproach to placing station names around stations in schematic railway\nmaps for better automation of map labeling processes. The idea behind\nour approach is to annotate stations in dense downtown areas around the\ninterchange stations first and then those in sparse rural areas. This is\nachieved by introducing the sum of geodesic distances over the railway\nnetwork to identify the proper order in which to annotate stations. In\nthe actual annotation process, we increase the labeling space around the\nrailway network when necessary by progressively stretching railway line\nsegments while retaining their original directions, which allows us to\nrespect the original schematic layout as much as possible. We present\nseveral experimental results to demonstrate the effectiveness of the\nproposed approach, together with a discussion on parameter tuning in our\nformulation.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "8564188-image.png", "type": "image/png", "size": 28813, "path": "Publication:8564188", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/8564188/8564188-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/8564188/8564188-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1624, 1625, 1626, 1464, 1627, 1580 ], "booktitle": "Proceedings of the 22nd International Conference Information Visualisation (IV)", "doi": "10.1109/iV.2018.00070", "event": "The 22nd International Conference Information Visualisation (IV)", "lecturer": [ 1464 ], "pages": "373-378", "research_areas": [ "InfoVis" ], "keywords": [ "Rail transportation;Layout;Labeling;Spacestations;Optimization;Programming;Visualization;Progressive annotation,geodesic distances", "schematic layouts", "railway maps", "mixed-integerprogramming" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "8564188-image.png", "type": "image/png", "size": 28813, "path": "Publication:8564188", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/8564188/8564188-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/8564188/8564188-image:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/8564188/", "__class": "Publication" }, { "id": "mazurek-2018-veq", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Visualizing Expanded Query Results", "date": "2018-06", "abstract": "When performing queries in web search engines, users often face difficulties choosing appropriate query terms. Search engines\ntherefore usually suggest a list of expanded versions of the user query to disambiguate it or to resolve potential term mismatches.\nHowever, it has been shown that users find it difficult to choose an expanded query from such a list. In this paper, we describe\nthe adoption of set-based text visualization techniques to visualize how query expansions enrich the result space of a given\nuser query and how the result sets relate to each other. Our system uses a linguistic approach to expand queries and topic\nmodeling to extract the most informative terms from the results of these queries. In a user study, we compare a common text list\nof query expansion suggestions to three set-based text visualization techniques adopted for visualizing expanded query results\n– namely, Compact Euler Diagrams, Parallel Tag Clouds, and a List View – to resolve ambiguous queries using interactive\nquery expansion. Our results show that text visualization techniques do not increase retrieval efficiency, precision, or recall.\nOverall, users rate Parallel Tag Clouds visualizing key terms of the expanded query space lowest. Based on the results, we derive\nrecommendations for visualizations of query expansion results, text visualization techniques in general, and discuss alternative\nuse cases of set-based text visualization techniques in the context of web search.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Density-based compact Euler Diagram", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 919, "image_height": 656, "name": "mazurek-2018-veq-teaser.png", "type": "image/png", "size": 34882, "path": "Publication:mazurek-2018-veq", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1364, 1110 ], "cfp": { "name": "EuroVis 2018 CfP.pdf", "type": "application/pdf", "error": "0", "size": "55844", "orig_name": "EuroVis 2018 CfP.pdf", "ext": "pdf" }, "date_from": "2018-06-04", "date_to": "2018-06-08", "event": "EG / VGTC Conference on Visualization (EuroVis)", "journal": "Computer Graphics Forum", "lecturer": [ 1364 ], "location": "Brno, Czech Republic", "pages_from": "87", "pages_to": "98", "research_areas": [ "InfoVis", "NetVis" ], "keywords": [ "Information visualization", "search interfaces", "empirical studies in visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mazurek-2018-veq-paper.pdf", "type": "application/pdf", "size": 1891501, "path": "Publication:mazurek-2018-veq", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-paper:thumb{{size}}.png" }, { "description": "Density-based compact Euler Diagram", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 919, "image_height": 656, "name": "mazurek-2018-veq-teaser.png", "type": "image/png", "size": 34882, "path": "Publication:mazurek-2018-veq", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mazurek-2018-veq-video.mp4", "type": "video/mp4", "size": 30231176, "path": "Publication:mazurek-2018-veq", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-video:video.mp4" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/", "__class": "Publication" }, { "id": "miao2018Dimsum", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "DimSUM: Dimension and Scale Unifying Maps for Visual Abstraction of DNA Origami Structures", "date": "2018-06", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 3302, "image_height": 1884, "name": "miao2018Dimsum-Image.png", "type": "image/png", "size": 2858278, "path": "Publication:miao2018Dimsum", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1263, 1474, 960, 166, 1473, 171 ], "date_from": "2017-06", "date_to": "2018-06", "event": "EuroVis Conference 2018", "journal": "Computer Graphics Forum", "lecturer": [ 1263 ], "location": "Brno, Czech Republic", "number": "3", "volume": "37", "research_areas": [ "BioVis", "IllVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 3302, "image_height": 1884, "name": "miao2018Dimsum-Image.png", "type": "image/png", "size": 2858278, "path": "Publication:miao2018Dimsum", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "preview_image_width": 3302, "preview_image_height": 1884, "name": "miao2018Dimsum-Paper.pdf", "type": "application/pdf", "size": 50814642, "path": "Publication:miao2018Dimsum", "preview_name": "miao2018Dimsum-Paper:preview.png", "preview_type": "image/png", "preview_size": 2858278, "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Paper:thumb{{size}}.png" }, { "description": null, "filetitle": "Recording", "main_file": false, "use_in_gallery": false, "access": "public", "name": "miao2018Dimsum-Recording.mp4", "type": "video/mp4", "size": 236260449, "path": "Publication:miao2018Dimsum", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Recording.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Recording:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Recording:video.mp4" }, { "description": null, "filetitle": "Video", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 3302, "preview_image_height": 1884, "name": "miao2018Dimsum-Video.mp4", "type": "video/mp4", "size": 97832153, "path": "Publication:miao2018Dimsum", "preview_name": "miao2018Dimsum-Video:preview.png", "preview_type": "image/png", "preview_size": 2858278, "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Video:video.mp4" } ], "projects_workgroups": [ "Illustrare" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/", "__class": "Publication" }, { "id": "wu-2018-metabo", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "A Visual Comparison of Hand-Drawn and Machine-Generated Human Metabolic Pathways", "date": "2018-06", "abstract": "This poster abstract presents a visual comparison between three hand-drawn and one machine-generated human metabolic pathway diagrams. The human metabolic pathways, which describe significant biochemical reactions in the human body, have been increasingly investigated due to the development of analysis processes and are compiled into pathway diagrams to provide an overview of reaction in the human body. This complex network includes about 5,000 metabolites and 7,500 reactions, which are hierarchically nested and difficult to visualize. We collect and analyze well-known human metabolic pathway diagrams, and summarize the design choices of these diagrams, respectively. Together with a machine-generated diagram, we can understand the visual complexity of three hand-drawn and one machine-generated diagrams.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 566, "image_height": 800, "name": "wu-2018-metabo-image.png", "type": "image/png", "size": 677575, "path": "Publication:wu-2018-metabo", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1579, 171 ], "cfp": { "name": "eurovis2018-poster.pdf", "type": "application/pdf", "error": "0", "size": "35735", "orig_name": "eurovis2018-poster.pdf", "ext": "pdf" }, "date_from": "2018-06-04", "date_to": "2018-06-08", "event": "EuroVis", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 566, "image_height": 800, "name": "wu-2018-metabo-image.png", "type": "image/png", "size": 677575, "path": "Publication:wu-2018-metabo", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2018-metabo-poster.pdf", "type": "application/pdf", "size": 85587001, "path": "Publication:wu-2018-metabo", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-poster:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/", "__class": "Publication" }, { "id": "steinboeck-2017-vbn", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Interactive Visual Exploration Interface for Large Bipartite Networks", "date": "2018-05-30", "abstract": "In this thesis we introduce BiCFlows, a novel interactive visualization approach to explore large bipartite graphs. We were motivated by the Media Transparency Database, a public database established by the Austrian government to provide information about governmental advertising and subsidies expenses, which holds the characteristics of a large, weighted bipartite graph.\nCurrent approaches that deal with the visualization of the Media Transparency Database are limited by the fact that they do not offer a sufficient overview of the whole dataset. Other existing approaches that are not particularly designed for the Media Transparency Database, but deal with the visualization of bipartite graphs are in addition limited by their lack of scalability for large datasets.\nAggregation is an often used concept in reducing the amount of data by grouping together similar data objects. This only works if the appropriate object properties are present in the data to use them for the aggregation. If this additional information is missing, like in the Media Transparency Database, other aggregation techniques have to be used. Since we are dealing with bipartite graphs in our approach, we use the concept of biclustering to establish a hierarchical structure within the data that can be interactively explored by the user.\nWe showed that BiCFlows cannot only be used for the Media Transparency Database, but also for other datasets that share the characteristics of a weighted bipartite graph. Furthermore, we conducted an insight-based user study to compare BiCFlows with existing concepts and discussed advantages and drawbacks. We showed that BiCFlows supported users in their exploration process and let them gain more insight than with existing approaches.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "sketch", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 649, "image_height": 462, "name": "steinboeck-2017-vbn-sketch.PNG", "type": "image/png", "size": 30764, "path": "Publication:steinboeck-2017-vbn", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-sketch.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-sketch:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1378 ], "date_end": "2018-05-30", "date_start": "2017-07", "matrikelnr": "0826088", "open_access": "yes", "supervisor": [ 166, 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "steinboeck-2017-vbn-Master Thesis.pdf", "type": "application/pdf", "size": 14008127, "path": "Publication:steinboeck-2017-vbn", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "steinboeck-2017-vbn-Poster.pdf", "type": "application/pdf", "size": 1309833, "path": "Publication:steinboeck-2017-vbn", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-Poster:thumb{{size}}.png" }, { "description": null, "filetitle": "sketch", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 649, "image_height": 462, "name": "steinboeck-2017-vbn-sketch.PNG", "type": "image/png", "size": 30764, "path": "Publication:steinboeck-2017-vbn", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-sketch.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-sketch:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/", "__class": "Publication" }, { "id": "gusenbauer-2018", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Bitstream - A bottom-up/top-down hybrid approach for web-based visual analysis of big data", "date": "2018-05-14", "abstract": "Analyzing large amounts of data is becoming an ever increasing problem. Bitcoin as an\nexample has produced more data than is possible to analyze. In order to compensate for these difficulties, creative ideas that employ data aggregation or minimization have been proposed. Other work also focuses on introducing novel visualization types that are geared towards the visualization of blockchain data. However, visualization of graphs through node-link diagrams remains a difficult challenge. Analysis of the Bitcoin transaction graph to follow bitcoin (BTC) transactions (TXs) poses a difficult problem due to the Bitcoin\nprotocol and the amount of data. This thesis combines two data processing strategies to visualize big network data on commodity hardware. The idea is to use visualization as a technique to analyze a data-set containing Bitcoin transaction information. Criminals use Bitcoin as a means of payment because of its guaranteed pseudonymity. Through visualization we aim to identify patterns that will allow us to deanonymize transactions. To do so we use a proxy server that does data preprocessing before they are visualized on a web client. The proxy leverages parallel computing to be able to do top-down and bottom-up data processing fast enough for interactive visualization. This is done through incremental loading (bottom-up), which enables to visualize data immediately\nwithout a (pre-)processing delay. The database containing the public Bitcoin ledger is over 163 gigabytes in size. The resulting graph has more than 800 million nodes. As this information is too much to be visualized, we also employ a top-down approach of data aggregation and graph minimization of the transactional graph. Through this methodology we intend to solve performance problems of long processing delays and the problem of fractured data where the data is shown only partially in the visualization.\nWe collaborate with security experts who share insights into their expertise through a continuously ongoing dialog. Exploratory analysis on a big data-set such as the Bitcoin ledger, enabled through the methodology presented in this thesis, will help security experts to analyze the money flow in a financial network that is used by criminals for its anonymity. We evaluate the result through the performance and feedback of these security experts as well as benchmark the performance against current best practice approaches.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 237, "image_height": 113, "name": "gusenbauer-2018-image.JPG", "type": "image/jpeg", "size": 11712, "path": "Publication:gusenbauer-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/gusenbauer-2018-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/gusenbauer-2018-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1257 ], "date_end": "2018-05-14", "date_start": "2016-11", "matrikelnr": "1125577", "supervisor": [ 1110, 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 237, "image_height": 113, "name": "gusenbauer-2018-image.JPG", "type": "image/jpeg", "size": 11712, "path": "Publication:gusenbauer-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/gusenbauer-2018-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/gusenbauer-2018-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "gusenbauer-2018-Master thesis.pdf", "type": "application/pdf", "size": 12125980, "path": "Publication:gusenbauer-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/gusenbauer-2018-Master thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/gusenbauer-2018-Master thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis", "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/", "__class": "Publication" }, { "id": "gusenbauer-2018-P", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "Bitstream - Top-Down/Bottom-Up Data Processing for Interactive Bitcoin Visualization.", "date": "2018-05-14", "abstract": "Analyzing large amounts of data is becoming an ever increasing problem. Bitcoin as an\nexample has produced more data than is possible to analyze. In order to compensate for these difficulties, creative ideas that employ data aggregation or minimization have been proposed. Other work also focuses on introducing novel visualization types that are geared towards the visualization of blockchain data. However, visualization of graphs through node-link diagrams remains a difficult challenge. Analysis of the Bitcoin transaction graph to follow bitcoin (BTC) transactions (TXs) poses a difficult problem due to the Bitcoin\nprotocol and the amount of data. This thesis combines two data processing strategies to visualize big network data on commodity hardware. The idea is to use visualization as a technique to analyze a data-set containing Bitcoin transaction information. Criminals use Bitcoin as a means of payment because of its guaranteed pseudonymity. Through visualization we aim to identify patterns that will allow us to deanonymize transactions.\nTo do so we use a proxy server that does data preprocessing before they are visualized on a web client. The proxy leverages parallel computing to be able to do top-down and bottom-up data processing fast enough for interactive visualization. This is done through incremental loading (bottom-up), which enables to visualize data immediately without a (pre-)processing delay. The database containing the public Bitcoin ledger is over 163 gigabytes in size. The resulting graph has more than 800 million nodes. As this information is too much to be visualized, we also employ a top-down approach of data aggregation and graph minimization of the transactional graph. Through this methodology we intend to solve performance problems of long processing delays and the problem of fractured data where the data is shown only partially in the visualization.\nWe collaborate with security experts who share insights into their expertise through a continuously ongoing dialog. Exploratory analysis on a big data-set such as the Bitcoin ledger, enabled through the methodology presented in this thesis, will help security experts to analyze the money flow in a financial network that is used by criminals for its anonymity. We evaluate the result through the performance and feedback of these security experts as well as benchmark the performance against current best practice approaches.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 279, "image_height": 149, "name": "gusenbauer-2018-P-image.JPG", "type": "image/jpeg", "size": 18488, "path": "Publication:gusenbauer-2018-P", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018-P/gusenbauer-2018-P-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018-P/gusenbauer-2018-P-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1257 ], "date_from": "2018-06-18", "date_to": "2018-06-18", "event": "EPILOG", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 279, "image_height": 149, "name": "gusenbauer-2018-P-image.JPG", "type": "image/jpeg", "size": 18488, "path": "Publication:gusenbauer-2018-P", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018-P/gusenbauer-2018-P-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018-P/gusenbauer-2018-P-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": false, "use_in_gallery": true, "access": "public", "name": "gusenbauer-2018-P-Poster.pdf", "type": "application/pdf", "size": 707107, "path": "Publication:gusenbauer-2018-P", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018-P/gusenbauer-2018-P-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018-P/gusenbauer-2018-P-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018-P/", "__class": "Publication" }, { "id": "birsak-2017-dpe", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Dynamic Path Exploration on Mobile Devices", "date": "2018-05", "abstract": "We present a novel framework for visualizing routes on mobile devices. Our framework is suitable for helping users explore their environment.\nFirst, given a starting point and a maximum route length, the system retrieves nearby points of interest (POIs). Second, we automatically compute an attractive walking path through the environment trying to pass by as many highly ranked POIs as possible. Third, we automatically compute a route visualization that shows the current user position, POI locations via pins, and detail lenses for more information about the POIs. The visualization is an animation of an orthographic map view that follows the current user position. We propose an optimization based on a binary integer program (BIP) that models multiple requirements for an effective placement of detail lenses. We show that our path computation method outperforms recently proposed methods and we evaluate the overall impact of our framework in two user studies.", "authors_et_al": false, "substitute": null, "main_image": { "description": "thumbnail", "filetitle": "thumbnail", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2002, "image_height": 1246, "name": "birsak-2017-dpe-thumbnail.png", "type": "image/png", "size": 1540567, "path": "Publication:birsak-2017-dpe", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-thumbnail.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-thumbnail:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 836, 844, 194, 193 ], "doi": "10.1109/TVCG.2017.2690294", "issn": "1077-2626", "journal": "IEEE Transactions on Visualization and Computer Graphics", "number": "5", "pages_from": "1784", "pages_to": "1798", "protocol": "null", "volume": "24", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": "overview image", "filetitle": "overview", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2229, "image_height": 2762, "name": "birsak-2017-dpe-overview.png", "type": "image/png", "size": 3708886, "path": "Publication:birsak-2017-dpe", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-overview.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-overview:thumb{{size}}.png" }, { "description": null, "filetitle": "preprint", "main_file": true, "use_in_gallery": false, "access": "public", "name": "birsak-2017-dpe-preprint.pdf", "type": "application/pdf", "size": 39449554, "path": "Publication:birsak-2017-dpe", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-preprint.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-preprint:thumb{{size}}.png" }, { "description": null, "filetitle": "supplementary", "main_file": false, "use_in_gallery": false, "access": "public", "name": "birsak-2017-dpe-supplementary.pdf", "type": "application/pdf", "size": 26746193, "path": "Publication:birsak-2017-dpe", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-supplementary.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-supplementary:thumb{{size}}.png" }, { "description": "thumbnail", "filetitle": "thumbnail", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2002, "image_height": 1246, "name": "birsak-2017-dpe-thumbnail.png", "type": "image/png", "size": 1540567, "path": "Publication:birsak-2017-dpe", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-thumbnail.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-thumbnail:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "name": "birsak-2017-dpe-video.mp4", "type": "video/mp4", "size": 45077025, "path": "Publication:birsak-2017-dpe", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/birsak-2017-dpe-video:video.mp4" } ], "projects_workgroups": [ "Photo-Guide", "MAKE-IT-FAB" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/", "__class": "Publication" }, { "id": "Cai_2018", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Research on Graphical Interfaces to Perform Anatomical Queries on Large Collections of Gene Expression Images", "date": "2018-04-06", "abstract": "As image information is increasing sharply, searching and presenting interesting images\nin large databases have become more and more important in image management. In this\npaper, an optimizing graphical query interface was designed for anatomical search to present more valuable information from the large neuro-anatomical image collections of Drosophila (fruit fly) brains. In order to achieve the goal, the relevant websites of “Fly Circuit”, “Fly Light” and “Allen Mouse Brain Atlas”, and the image management software of PivotViewer and Zegami were investigated firstly. Then, analysis and comparison for\nthe mentioned tools using different perspectives were conducted to define the guidelines for best practices out of them. Based on the findings, several redesigns are proposed for neuro-anatomical query interfaces and part of them were implemented. ", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 506, "image_height": 278, "name": "Cai_2018-image.JPG", "type": "image/jpeg", "size": 38696, "path": "Publication:Cai_2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Cai_2018/Cai_2018-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Cai_2018/Cai_2018-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1553 ], "date_end": "2018-04-06", "date_start": "2017-10-06", "matrikelnr": "1425123", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Cai_2018-Bachelor Thesis.pdf", "type": "application/pdf", "size": 28622827, "path": "Publication:Cai_2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Cai_2018/Cai_2018-Bachelor Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Cai_2018/Cai_2018-Bachelor Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 506, "image_height": 278, "name": "Cai_2018-image.JPG", "type": "image/jpeg", "size": 38696, "path": "Publication:Cai_2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Cai_2018/Cai_2018-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Cai_2018/Cai_2018-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis", "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Cai_2018/", "__class": "Publication" }, { "id": "cizmic-2018-evd", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Exploratory Data Visualization Dashboard for Technical Analysis of Commodity Market Indicators", "date": "2018-04", "abstract": "Companies and traders working in the commodity market encounter a variety of different\ndata sets, including numerous economic indicators. The analysis of those indicators and\ntheir connection to certain markets can lead to important insights. The understanding of\nthe market can be improved and predictions of the future market development can be\ncreated. However, dozens of economic indicators exist and one of the main challenges is\nto show a clear overview of the indicators and identify those, which show a correlation\nto a certain market. Software tools are often utilised in order to perform the analysis\nof financial markets. However, according to domain experts, they often hit the limit of\nhuman perception capabilities. This thesis focuses on the development of a prototypical\nweb application dashboard, which enables the user to analyse the relation between\na defined commodity market and different economic indicators. Besides the relation\nbetween one indicator and a given market, the possibility to interactively create one’s own\ncomposite indicator, for comparison with the given market, is implemented. The process\nof creating a composite indicator is another challenge as it requires numerous decisions to\nbe made. The dashboard therefore offers a platform for exploring the different composite\nindicator configurations. Moreover, the web-application provides also some visualization\nand interaction techniques, like highlighting, brushing and details-on-demand to enhance\nthe comparison process and amplify human cognition.", "authors_et_al": false, "substitute": null, "main_image": { "description": "composite indicator view", "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 909, "image_height": 378, "name": "cizmic-2018-evd-screenshot.PNG", "type": "image/png", "size": 63662, "path": "Publication:cizmic-2018-evd", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-screenshot.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1462 ], "date_end": "2018-04", "date_start": "2017-05", "matrikelnr": "1425788", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": "composite indicator view", "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 909, "image_height": 378, "name": "cizmic-2018-evd-screenshot.PNG", "type": "image/png", "size": 63662, "path": "Publication:cizmic-2018-evd", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-screenshot.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-screenshot:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "cizmic-2018-evd-thesis.pdf", "type": "application/pdf", "size": 2131622, "path": "Publication:cizmic-2018-evd", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/", "__class": "Publication" }, { "id": "smiech-2018-tei", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Configurable Text Exploration Interface with NLP for Decision Support", "date": "2018-04", "abstract": "Having to read and understand lots of text documents and reports on a daily basis can\nbe quite challenging. The intended audience for these reports has limited resources and\nwants to reduce time spent on reading such reports. Therefore a need for a tool emerges\nthat assists the process of gaining relevant information out of reports/documents more\nquickly. These text documents are often unstructured and of varying length. They are\nwritten in the English language and are available from different sources (such as RSS\nfeeds and text files). The aim of this project is to offer a tool that supports the process of\nanalysing and understanding given texts. This is made possible by using natural language\nprocessing (NLP) and text visualization (TextVis). TextVis is already a well known and\nfrequently used solution. The herein described project uses an NLP pipeline which serves\nas preprocessing for TextVis. To provide quick insight into the data, topic extraction\nmechanisms like Latent Dirichlet Allocation (LDA) or Non-negative Matrix Factorization\n(NMF) are available for the user to be chosen within the aforementioned pipeline. A major\nchallenge for TextVis is the configuration of the NLP pipeline, because there are many\ndifferent ways of doing so and a wide range of parameters to chose from. To overcome this\nissue, this project provides a solution that enables users to easily configure and customize\ntheir own NLP pipeline. It is designed to encourage these users to experiment with\ndifferent sequences of NLP operations and parameter configurations to find a solution\nthat suites them best. In order to keep it easy to use the software, it is implemented\nentirely using web technologies to be accessible in a common web browser. The resulting\nvisualization will emphasize particular parts of the text based on a set of different factors,\nif selected so. These factors can be topics, sentiments and part-of-speech-tagged words.\nThe focus of this work lies on a visual interface that enables and encourages users to\nadjust/optimize the underlying NLP pipeline (by selecting steps and setting parameters)\nand comparing their results. Evaluation with help of user feedback showed that certain\npipeline configurations work better for certain types of texts than others. Using the\nsolution created within this work, users can adapt the tool to their needs and also tweak\nit according to requirements. There is no universal configuration that works for all\ndocuments, however.", "authors_et_al": false, "substitute": null, "main_image": { "description": "detail text view", "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 985, "image_height": 585, "name": "smiech-2018-tei-screenshot.PNG", "type": "image/png", "size": 125879, "path": "Publication:smiech-2018-tei", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-screenshot.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1463 ], "date_end": "2018-04", "date_start": "2017-05", "matrikelnr": "01426853", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": "detail text view", "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 985, "image_height": 585, "name": "smiech-2018-tei-screenshot.PNG", "type": "image/png", "size": 125879, "path": "Publication:smiech-2018-tei", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-screenshot.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-screenshot:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "smiech-2018-tei-thesis.pdf", "type": "application/pdf", "size": 1305969, "path": "Publication:smiech-2018-tei", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/", "__class": "Publication" }, { "id": "wu-2018-story", "type_id": "misc", "tu_id": null, "repositum_id": null, "title": "The Travel of a Metabolite", "date": "2018-04", "abstract": "Biological pathways are chains of molecule interactions and reactions in biological systems that jointly form complex, hierarchical networks. Although several pathway layout algorithms have been investigated, biologists still prefer to use hand-drawn ones, due to their high visual quality relied on domain knowledge. In this project, we propose a visualization for computing metabolic pathway maps that restrict the grouping structure defined by biologists to rectangles and apply orthogonal-style edge routing to simplify edge orientation. This idea is inspired by concepts from urban planning, where we consider reactions as city blocks and built up roads to connect identical metabolites occurred in multiple categories. We provide a story to present how glucose is broken down to phosphoenolpyruvate to release energy, which is often stored in adenosine triphosphate (ATP) in a human body. Finally, we demonstrate ATP is also utilized to synthesize urea to eliminate the toxic ammonia in our body.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2018-story-image.png", "type": "image/png", "size": 91891, "path": "Publication:wu-2018-story", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1579, 171 ], "note": "submitted to PacificVis 2018 Data Story Telling Contest", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://vimeo.com/258174044", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2018-story-image.png", "type": "image/png", "size": 91891, "path": "Publication:wu-2018-story", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2018-story-paper.pdf", "type": "application/pdf", "size": 601059, "path": "Publication:wu-2018-story", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2018-story-video.mov", "type": "video/quicktime", "size": 15567398, "path": "Publication:wu-2018-story", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-video.mov", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-video:video.mp4" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/", "__class": "Publication" }, { "id": "polatsek-2018-stv", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Exploring visual attention and saliency modeling for task-based visual analysis", "date": "2018-02", "abstract": "Memory, visual attention and perception play a critical role in the design of visualizations. The way users observe a visualization is affected by salient stimuli in a scene as well as by domain knowledge, interest, and the task. While recent saliency models manage to predict the users’ visual attention in visualizations during exploratory analysis, there is little evidence how much influence bottom-up saliency has on task-based visual analysis. Therefore, we performed an eye-tracking study with 47 users to determine the users’ path of attention when solving three low-level analytical tasks using 30 different charts from the MASSVIS database [1]. We also compared our task-based eye tracking data to the data from the original memorability experiment by Borkin et al. [2]. We found that solving a task leads to more consistent viewing patterns compared to exploratory visual analysis. However, bottom-up saliency of a visualization has negligible influence on users’ fixations and task efficiency when performing a low-level analytical task. Also, the efficiency of visual search for an extreme target data point is barely influenced by the target’s bottom-up saliency. Therefore, we conclude that bottom-up saliency models tailored towards information visualization are not suitable for predicting visual attention when performing task-based visual analysis. We discuss potential reasons and suggest extensions to visual attention models to better account for task-based visual analysis.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "graphical abstract", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 591, "image_height": 584, "name": "polatsek-2018-stv-graphical abstract.png", "type": "image/png", "size": 193042, "path": "Publication:polatsek-2018-stv", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1545, 1110, 171, 1546, 1547 ], "doi": "https://doi.org/10.1016/j.cag.2018.01.010", "journal": "Computers & Graphics", "number": "2", "open_access": "no", "research_areas": [ "InfoVis", "Perception" ], "keywords": [ "Information visualization", "Eye-tracking experiment", "Saliency", "Visual attention", "Low-level analytical tasks" ], "weblinks": [ { "href": "https://www.sciencedirect.com/science/article/pii/S0097849318300104", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "graphical abstract", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 591, "image_height": 584, "name": "polatsek-2018-stv-graphical abstract.png", "type": "image/png", "size": 193042, "path": "Publication:polatsek-2018-stv", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "polatsek-2018-stv-paper.pdf", "type": "application/pdf", "size": 3228380, "path": "Publication:polatsek-2018-stv", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis", "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/", "__class": "Publication" }, { "id": "wu-2018-JVLC", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Overlap-Free Labeling of Clustered Networks Based on Voronoi Tessellation", "date": "2018-02", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2018-JVLC-teaser.png", "type": "image/png", "size": 23010, "path": "Publication:wu-2018-JVLC", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-JVLC/wu-2018-JVLC-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-JVLC/wu-2018-JVLC-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1580, 1581 ], "journal": "Journal of Visual Languages & Computing", "number": "44", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2018-JVLC-paper.pdf", "type": "application/pdf", "size": 6440310, "path": "Publication:wu-2018-JVLC", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-JVLC/wu-2018-JVLC-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-JVLC/wu-2018-JVLC-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2018-JVLC-teaser.png", "type": "image/png", "size": 23010, "path": "Publication:wu-2018-JVLC", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-JVLC/wu-2018-JVLC-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-JVLC/wu-2018-JVLC-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-JVLC/", "__class": "Publication" }, { "id": "Strohmayer-2018-BT", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "A Visual Analytics Approach to Hypocotyl/Root Transition Detection in Arabidopsis Thaliana", "date": "2018-01", "abstract": "Plant root phenotyping can be a tedious process if done manually, since it typically requires large data sets to be processed. The solution to this problem are automatic phenotyping pipelines, which allow significantly higher throughput than manual methods, by eliminating the need for human intervention. These pipelines rely on the robustness of automatic segmentation and detection methods for various plant characteristics. Due to numerous confounding factors, the detection of the hypocotyl/root transition point is still an unsolved task. In this thesis a novel approach to this problem, utilizing Statistical Break Point Analysis based on custom plant features, is presented. The approach has been developed using a visual analytics framework called PlateViewer, which was especially built for this task. The framework is able to analyze individual Arabidopsis Thaliana seedlings, taken from agar plate scan images, produced by an automatic phenotyping pipeline.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 920, "image_height": 1182, "name": "Strohmayer-2018-BT-image.png", "type": "image/png", "size": 560681, "path": "Publication:Strohmayer-2018-BT", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Strohmayer-2018-BT/Strohmayer-2018-BT-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Strohmayer-2018-BT/Strohmayer-2018-BT-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1540 ], "date_end": "2018-01", "date_start": "2017-08", "matrikelnr": "01426125", "supervisor": [ 1195 ], "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 920, "image_height": 1182, "name": "Strohmayer-2018-BT-image.png", "type": "image/png", "size": 560681, "path": "Publication:Strohmayer-2018-BT", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Strohmayer-2018-BT/Strohmayer-2018-BT-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Strohmayer-2018-BT/Strohmayer-2018-BT-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 920, "preview_image_height": 1182, "name": "Strohmayer-2018-BT-Thesis.pdf", "type": "application/pdf", "size": 6376986, "path": "Publication:Strohmayer-2018-BT", "preview_name": "Strohmayer-2018-BT-Thesis:preview.png", "preview_type": "image/png", "preview_size": 560681, "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Strohmayer-2018-BT/Strohmayer-2018-BT-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Strohmayer-2018-BT/Strohmayer-2018-BT-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Strohmayer-2018-BT/", "__class": "Publication" }, { "id": "raidou_bestphd", "type_id": "misc", "tu_id": null, "repositum_id": null, "title": "EuroVis Best PhD Award 2018—Visual Analytics for Digital Radiotherapy: Towards a Comprehensible Pipeline", "date": "2018", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 719, "image_height": 997, "name": "raidou_bestphd-.jpg", "type": "image/jpeg", "size": 182727, "path": "Publication:raidou_bestphd", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/raidou_bestphd/raidou_bestphd-.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/raidou_bestphd/raidou_bestphd-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410 ], "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 719, "image_height": 997, "name": "raidou_bestphd-.jpg", "type": "image/jpeg", "size": 182727, "path": "Publication:raidou_bestphd", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/raidou_bestphd/raidou_bestphd-.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/raidou_bestphd/raidou_bestphd-:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/raidou_bestphd/", "__class": "Publication" }, { "id": "wu-2017-dagstuhl", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Mapifying the Genome, Scalable Set Visualizations (Dagstuhl Seminar 17332)", "date": "2018", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1677, 1678, 1679, 1464 ], "number": "TR-193-02-2018-2", "open_access": "yes", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://doi.org/10.4230/DagRep.7.8.1", "caption": "Dagstuhl Seminar 17332", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2017-dagstuhl-paper.pdf", "type": "application/pdf", "size": 3647552, "path": "Publication:wu-2017-dagstuhl", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2017-dagstuhl/wu-2017-dagstuhl-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2017-dagstuhl/wu-2017-dagstuhl-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2017-dagstuhl/", "__class": "Publication" }, { "id": "Purgathofer-2017-China2", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "From Visualization to Decision Support", "date": "2017-09-29", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 190 ], "date_to": "2017-09-29", "event": "2nd International Forum on VR Visual Computing Technologies", "location": "Hangzhou, China", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Purgathofer-2017-China2/", "__class": "Publication" }, { "id": "Purgathofer-2017-China1", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "From Visualization to Decision Support", "date": "2017-09-28", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 190 ], "date_from": "2017-09-28", "event": "Virtual Reality and Visual Computing International Forum", "location": "Nanjing, China", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Purgathofer-2017-China1/", "__class": "Publication" }, { "id": "sorger-2017-thesis", "type_id": "phdthesis", "tu_id": null, "repositum_id": null, "title": "Integration Strategies in the Visualization of Multifaceted Spatial Data", "date": "2017-09-26", "abstract": "Visualization designers have several visual channels at their disposal for encoding data into visual representations, e.g., position, size, shape, orientation, color, texture, brightness, as well as motion. The mapping of attributes to visual channels can be chosen by the designer. In theory, any data attribute can be represented by any of these visual channels or by a combination of multiple of these channels. In practice, the optimal mapping and the most suitable type of visualization strongly depend on the data as well as on the user's task. In the visualization of spatial data, the mapping of spatial attributes to visual channels is inherently given by the data. Multifaceted spatial data possesses a wide range of additional (non-spatial) attributes without a given mapping. The data's given spatial context is often important for successfully fulfilling a task. The design space in spatial data visualization can therefore be heavily constrained when trying to choose an optimal mapping for other attributes within the spatial context. To solve an exploration or presentation task in the domain of multifaceted spatial data, special strategies have to be employed in order to integrate the essential information from the various data facets in an appropriate representation form with the spatial context.\nThis thesis explores visualization integration strategies for multifaceted spatial data. The first part of this thesis describes the design space of integration in terms of two aspects: visual and functional integration. Visual integration describes how representations of the different data facets can be visually composed within a spatial context. Functional integration, describes how events that have been triggered, for instance, through user interaction, can be coordinated across the various visually integrated representations.\nThe second part of this thesis describes contributions to the field of visualization in the context of concrete integration applications for exploration and presentation scenarios. The first scenario addresses a set of challenges in the exploratory analysis of multifaceted spatial data in the scope of a decision making scenario in lighting design. The user's task is to find an optimal lighting solution among dozens or even hundreds of potential candidates. In the scope of a design study, the challenges in lighting design are addressed with LiteVis, a system that integrates representations of the simulation parameter space with representations of all relevant aspects of the simulation output. The integration of these heterogeneous aspects together with a novel ranking visualization are thereby the key to enabling an efficient exploration and comparison of lighting parametrizations.\nIn presentation scenarios, the generation of insights often cannot rely on user interaction and therefore needs a different approach. The challenge is to generate visually appealing, yet information-rich representations for mainly passive observation. In this context, this thesis addresses two different challenges in the domain of molecular visualization. The first challenge concerns the conveying of relations between two different representations of a molecular data set, such as a virus. The relation is established via animated transitions - a temporal form of integration between two representations. The proposed solution features a novel technique for creating such transitions that are re-usable for different data sets, and can be combined in a modular fashion. \nAnother challenge in presentation scenarios of multifaceted spatial data concerns the presentation of the transition between development states of molecular models, where the actual biochemical process of the transition is not exactly known or it is too complex to represent. A novel technique applies a continuous abstraction of both model representations to a level of detail at which the relationship between them can be accurately conveyed, in order to overcome a potential indication of false relationship information. Integration thereby brings the different abstraction levels and the different model states into relation with each other. The results of this thesis clearly demonstrate that integration is a versatile tool in overcoming key challenges in the visualization of multifaceted spatial data.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "overview", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1768, "image_height": 1186, "name": "sorger-2017-thesis-overview.png", "type": "image/png", "size": 836988, "path": "Publication:sorger-2017-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/sorger-2017-thesis/sorger-2017-thesis-overview.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/sorger-2017-thesis/sorger-2017-thesis-overview:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1072 ], "co_supervisor": [ 166 ], "date_end": "2017", "date_start": "2013", "reviewer_1": [ 196 ], "reviewer_2": [ 1248 ], "rigorosum": "2017-11-22", "supervisor": [ 171 ], "research_areas": [ "BioVis", "IllVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "overview", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1768, "image_height": 1186, "name": "sorger-2017-thesis-overview.png", "type": "image/png", "size": 836988, "path": "Publication:sorger-2017-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/sorger-2017-thesis/sorger-2017-thesis-overview.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/sorger-2017-thesis/sorger-2017-thesis-overview:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sorger-2017-thesis-thesis.pdf", "type": "application/pdf", "size": 48970349, "path": "Publication:sorger-2017-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/sorger-2017-thesis/sorger-2017-thesis-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/sorger-2017-thesis/sorger-2017-thesis-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis", "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/sorger-2017-thesis/", "__class": "Publication" }, { "id": "Purgathofer-2017-VC-Interface", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "Visual Computing als Interface zur Entscheidungsunterstützung", "date": "2017-07-04", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 190 ], "date_from": "2017-07-04", "event": "RailTec 4.0 Workshop", "location": "Wien", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Purgathofer-2017-VC-Interface/", "__class": "Publication" }, { "id": "Escribano_2017", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visual Evaluation of Computational Models of the Biological Mesoscale", "date": "2017-06", "abstract": "Currently available techniques for capturing macromolecules on atomic level are not appropriate for large structures on the biological mesoscale. Therefore, those structures, such as viruses or cell organelles, have to be assembled from molecular building blocks using software tools. The goal of recent projects like cellPACK is to create models with these tools, allowing the scientific community to iteratively give feedback and edit the models, in order to eventually generate the most suitable illustration consistent with the current state of knowledge. For that purpose, we need to discern the values for properties like distribution, density or opacity that make a model preferable to others. \nThis thesis aims to create a software program for visual evaluation of the quality of the assembled structures. The program will extract the information about the quality of spatial distribution of molecules in the scenes produced by packing tools and plot it into a set of 2D representations. These will convey the statistical information about the distribution and enable the visual comparison of generated models, which vary not only due to the stochastic nature of the packing algorithms but also because of the use of different parameter settings.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 813, "image_height": 441, "name": "Escribano_2017-image.jpg", "type": "image/jpeg", "size": 76644, "path": "Publication:Escribano_2017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Escribano_2017/Escribano_2017-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Escribano_2017/Escribano_2017-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1417 ], "date_end": "2017-06", "date_start": "2017-11", "matrikelnr": "01635324", "supervisor": [ 1285, 935 ], "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 813, "image_height": 441, "name": "Escribano_2017-image.jpg", "type": "image/jpeg", "size": 76644, "path": "Publication:Escribano_2017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Escribano_2017/Escribano_2017-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Escribano_2017/Escribano_2017-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Escribano_2017-thesis.pdf", "type": "application/pdf", "size": 2872837, "path": "Publication:Escribano_2017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Escribano_2017/Escribano_2017-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Escribano_2017/Escribano_2017-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Escribano_2017/", "__class": "Publication" }, { "id": "geymayer-2017-std", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "How Sensemaking Tools Influence Display Space Usage", "date": "2017-06", "abstract": "We explore how the availability of a sensemaking tool influences users’ knowledge externalization strategies. On a large display,\nusers were asked to solve an intelligence analysis task with or without a bidirectionally linked concept-graph (BLC) to organize\ninsights into concepts (nodes) and relations (edges). In BLC, both nodes and edges maintain “deep links” to the exact source\nphrases and sections in associated documents. In our control condition, we were able to reproduce previously described spatial\norganization behaviors using document windows on the large display. When using BLC, however, we found that analysts apply\nspatial organization to BLC nodes instead, use significantly less display space and have significantly fewer open windows.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 805, "image_height": 344, "name": "geymayer-2017-std-image.PNG", "type": "image/png", "size": 604999, "path": "Publication:geymayer-2017-std", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/geymayer-2017-std-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/geymayer-2017-std-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1477, 1110, 1476, 202 ], "booktitle": "EuroVis Workshop on Visual Analytics", "event": "EuroVis 2017", "lecturer": [ 1477 ], "research_areas": [ "InfoVis" ], "keywords": [ "sensemaking", "large displays", "evaluation" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 805, "image_height": 344, "name": "geymayer-2017-std-image.PNG", "type": "image/png", "size": 604999, "path": "Publication:geymayer-2017-std", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/geymayer-2017-std-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/geymayer-2017-std-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "geymayer-2017-std-paper.pdf", "type": "application/pdf", "size": 1117995, "path": "Publication:geymayer-2017-std", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/geymayer-2017-std-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/geymayer-2017-std-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/", "__class": "Publication" }, { "id": "waldner-2017-vph", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Exploring Visual Prominence of Multi-Channel Highlighting in Visualizations", "date": "2017-05", "abstract": "Visualizations make rich use of multiple visual channels so that there are few resources left to make selected focus elements visually\ndistinct from their surrounding context. A large variety of highlighting techniques for visualizations has been presented in the past,\nbut there has been little systematic evaluation of the design space of highlighting. We explore highlighting from the perspective\nof visual marks and channels – the basic building blocks of visualizations that are directly controlled by visualization designers.\nWe present the results from two experiments, exploring the visual prominence of highlighted marks in scatterplots: First, using\nluminance as a single highlight channel, we found that visual prominence is mainly determined by the luminance difference between\nthe focus mark and the brightest context mark. The brightness differences between context marks and the overall brightness level\nhave negligible influence. Second, multi-channel highlighting using luminance and blur leads to a good trade-off between highlight\neffectiveness and aesthetics. From the results, we derive a simple highlight model to balance highlighting across multiple visual\nchannels and focus and context marks, respectively.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 160, "image_height": 124, "name": "waldner-2017-vph-.png", "type": "image/png", "size": 20447, "path": "Publication:waldner-2017-vph", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1110, 925, 166 ], "booktitle": "Spring Conference on Computer Graphics 2017", "lecturer": [ 1110 ], "research_areas": [ "InfoVis", "Perception" ], "keywords": [ "information visualization", "highlighting", "focus+context", "visual prominence" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 160, "image_height": 124, "name": "waldner-2017-vph-.png", "type": "image/png", "size": 20447, "path": "Publication:waldner-2017-vph", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "waldner-2017-vph-paper.pdf", "type": "application/pdf", "size": 1851221, "path": "Publication:waldner-2017-vph", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-paper:thumb{{size}}.png" }, { "description": "Details about experiment design and results. ", "filetitle": "supplemental material", "main_file": false, "use_in_gallery": false, "access": "public", "name": "waldner-2017-vph-supplemental material.pdf", "type": "application/pdf", "size": 1396255, "path": "Publication:waldner-2017-vph", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-supplemental material.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-supplemental material:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/", "__class": "Publication" }, { "id": "Wagner_032017", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "3D-Printing of Fetal Ultrasound", "date": "2017-03", "abstract": "3D printing has been used industrially for decades. It enables rapid prototyping while\nmaintaining low costs. Personal 3D printing became popular approximately since 2011.\nSince the massive arise of public interest, 3D printers are getting more and more affordable.\nIn this thesis, we show how fetal 3D ultrasound data can be processed to enable 3D printing. Major steps are classification of the tissues, extraction of the isosurface and mesh-smoothing. Our approach uses thresholding, in combination with Connected Component Analysis, to separate the mother tissues from the fetal tissues. From the labeled data, we extract the fetal surface using Marching Tetrahedra. The mesh is then smoothed and converted into a data format suitable for 3D printing. Depending on the quality of the given ultrasound data, we can generate a model with recognizable facial features and peripheral structures.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 220, "image_height": 290, "name": "Wagner_032017-image.JPG", "type": "image/jpeg", "size": 16866, "path": "Publication:Wagner_032017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Wagner_032017/Wagner_032017-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Wagner_032017/Wagner_032017-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1350 ], "date_end": "2017-03-17", "date_start": "2016-10-01", "matrikelnr": "1326108", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Wagner_032017-Bachelor Thesis.pdf", "type": "application/pdf", "size": 5193004, "path": "Publication:Wagner_032017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Wagner_032017/Wagner_032017-Bachelor Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Wagner_032017/Wagner_032017-Bachelor Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 220, "image_height": 290, "name": "Wagner_032017-image.JPG", "type": "image/jpeg", "size": 16866, "path": "Publication:Wagner_032017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Wagner_032017/Wagner_032017-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Wagner_032017/Wagner_032017-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Wagner_032017/", "__class": "Publication" }, { "id": "mazurek-2017-sio", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Stream I/O - An Interactive Visualization of Publication Data", "date": "2017", "abstract": "The publication database of the Institute of Computer Graphics and Algorithms can\ncurrently be queried by a simple UI which returns a list. Stream I/O, the application\nof this thesis, extends the interface to improve it in terms of overview, exploration and\nanalysis support. To cope with these shortcommings a visualization is added to the user\ninterface. As the publication database includes a lot of additional data attributes, a\nselection of attributes is used for the visualization to give further insight. By using the\nStreamgraph [BW08] visualization, the variations over time within attributes like authors,\npublication type and research areas are made visible. The focus of this visualization lies\nin showing individual attribute values while also conveying the sum. This relationship\nis depicted in a timeline, which allows a user to explore the past and current work of\nthe institute as well as to find relationships and trends in the publications. As the\nvisualization uses a timeline encoding, the directed flow from left to right is interpreted\nas the movement through time. It shows the evolution of different attributes, while the\noccurrence of a topic at a specific time is coded with the width of the layer at a specific\npoint. Searching the database is enriched through multiple viewpoints which give the user\ninsight how attributes relate in the underlying data and how the data is changing through\nhis/her manipulation. Selections of colored layers within the graph can represent bigger\ntrends and give insight into the data as a whole. The Stream I/O application invites\nusers to interactively explore the publication database, while simultaneously gaining new\ninsight through the visualization.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1293, "image_height": 562, "name": "mazurek-2017-sio-.png", "type": "image/png", "size": 403642, "path": "Publication:mazurek-2017-sio", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1364 ], "date_end": "2017-03", "date_start": "2016-05", "duration": "4 months", "matrikelnr": "0123456", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1293, "image_height": 562, "name": "mazurek-2017-sio-.png", "type": "image/png", "size": 403642, "path": "Publication:mazurek-2017-sio", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "mazurek-2017-sio-thesis.pdf", "type": "application/pdf", "size": 4004622, "path": "Publication:mazurek-2017-sio", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/", "__class": "Publication" }, { "id": "mazurek-2017-vows", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Visualization of Thesaurus-Based Web Search", "date": "2017", "abstract": "The general functions of current web search engines are well established. A box is\nprovided in which to type the queries and the engine returns a result list which users can\nevaluate. The autocomplete suggestions assist users in defining their problems, however\nthere is a lack of support for an iterative manual refinement of the query. This additional\naid can be beneficial when users not know the exact terms to describe the concept they\nare looking for. Therefore, the goal of this project is to show searchers how a slight\nvariation of the query changes the results. With this information, they then can perform\na targeted refinement of the query to access useful information sources. To achieve this\ngoal, each part of the searcher’s query is varied with a thesaurus that provides synonyms\nfor the individual query terms. While performing the user’s original query in a normal\nfashion, variations of this query are conducted in the background. To provide a concise\nvisual summary of the query results, text mining techniques are performed on all gathered\nresults to retrieve the most important key terms for each query variation. This procedure\nresults in a visual overview of what the searcher’s query finds together with what could\nbe found with a slight variation of the query. Additional queries should make users aware\nthat alternative queries may be more appropriate when their original query is poorly\nformulated. In conjunction with some interaction tools, the goal is to reduce the burden\nof refining search queries and therefore making searching the web less complex.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 539, "name": "mazurek-2017-vows-teaser.PNG", "type": "image/png", "size": 405860, "path": "Publication:mazurek-2017-vows", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1364 ], "date_end": "2017-10", "date_start": "2017-08", "matrikelnr": "1126483", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "report", "main_file": false, "use_in_gallery": false, "access": "public", "name": "mazurek-2017-vows-report.pdf", "type": "application/pdf", "size": 540973, "path": "Publication:mazurek-2017-vows", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-report:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 539, "name": "mazurek-2017-vows-teaser.PNG", "type": "image/png", "size": 405860, "path": "Publication:mazurek-2017-vows", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/", "__class": "Publication" }, { "id": "steinboeck-2017-vefp", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Visualization of EU Funding Programmes", "date": "2017", "abstract": "To fund research and technological development, not only in Europe but all over the world, the European Union created so-called Framework Programmes. The data\nof these programmes, containing information about projects, corresponding topics,\nfunding sums, funding periods and recipient countries, is publicly available, but hard\nto analyze without visual support. Therefore, a multiple coordinated view approach is developed in course of this project. The different visualization techniques used, like bar charts, treemap, choropleth map and line graph, make it possible to filter, analyze and further explore the available data through brushing and linking. The project was developed in close collaboration with the end users of the Centre for Social Innovation and received an overall positive feedback from them.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screen shot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1920, "image_height": 945, "name": "steinboeck-2017-vefp-screen shot.png", "type": "image/png", "size": 208713, "path": "Publication:steinboeck-2017-vefp", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/steinboeck-2017-vefp/steinboeck-2017-vefp-screen shot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/steinboeck-2017-vefp/steinboeck-2017-vefp-screen shot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1378 ], "date_end": "2017-02", "date_start": "2016-09", "matrikelnr": "0826088", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "screen shot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1920, "image_height": 945, "name": "steinboeck-2017-vefp-screen shot.png", "type": "image/png", "size": 208713, "path": "Publication:steinboeck-2017-vefp", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/steinboeck-2017-vefp/steinboeck-2017-vefp-screen shot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/steinboeck-2017-vefp/steinboeck-2017-vefp-screen shot:thumb{{size}}.png" }, { "description": null, "filetitle": "technical report", "main_file": false, "use_in_gallery": false, "access": "public", "name": "steinboeck-2017-vefp-technical report.pdf", "type": "application/pdf", "size": 518813, "path": "Publication:steinboeck-2017-vefp", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/steinboeck-2017-vefp/steinboeck-2017-vefp-technical report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/steinboeck-2017-vefp/steinboeck-2017-vefp-technical report:thumb{{size}}.png" } ], "projects_workgroups": [ "vis", "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/steinboeck-2017-vefp/", "__class": "Publication" }, { "id": "vad_viktor-2017-WVE", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Watergate: Visual Exploration of Water Trajectories in Protein Dynamics", "date": "2017", "abstract": "The function of proteins is tightly related to their interactions with other molecules. The study of such interactions often requires to track the molecules that enter or exit specific regions of the proteins. This is investigated with molecular dynamics simulations, producing the trajectories of thousands of water molecules during hundreds of thousands of time steps. To ease the exploration of such rich spatio-temporal data, we propose a novel workflow for the analysis and visualization of large sets of water-molecule trajectories. Our solution consists of a set of visualization techniques, which help biochemists to classify, cluster, and filter the trajectories and to explore the properties and behavior of selected subsets in detail. Initially, we use an interactive histogram and a time-line visualization to give an overview of all water trajectories and select the interesting ones for further investigation. Further, we depict clusters of trajectories in a novel 2D representation illustrating the flows of water molecules. These views are interactively linked with a 3D representation where we show individual paths, including their simplification, as well as extracted statistical information displayed by isosurfaces. The proposed solution has been designed in tight collaboration with experts to support specific tasks in their scientific workflows. They also conducted several case studies to evaluate the usability and effectiveness of our new solution with respect to their research scenarios. These confirmed that our proposed solution helps in analyzing water trajectories and in extracting the essential information out of the large amount of input data.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 1474, "preview_image_height": 588, "name": "vad_viktor-2017-WVE-.pdf", "type": "application/pdf", "size": 6012581, "path": "Publication:vad_viktor-2017-WVE", "preview_name": "vad_viktor-2017-WVE-:preview.png", "preview_type": "image/png", "preview_size": 244889, "url": "https://www.cg.tuwien.ac.at/research/publications/2017/vad_viktor-2017-WVE/vad_viktor-2017-WVE-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/vad_viktor-2017-WVE/vad_viktor-2017-WVE-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1195, 1254, 1255, 171, 166, 176, 1498, 1499, 1248 ], "booktitle": "Eurographics Workshop on Visual Computing for Biology and Medicine 2017", "date_from": "2017", "lecturer": [ 1195 ], "location": "September, 2017 Bremen, Germany", "pages_from": "33", "pages_to": "42", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://diglib.eg.org/handle/10.2312/vcbm20171235", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 1474, "preview_image_height": 588, "name": "vad_viktor-2017-WVE-.pdf", "type": "application/pdf", "size": 6012581, "path": "Publication:vad_viktor-2017-WVE", "preview_name": "vad_viktor-2017-WVE-:preview.png", "preview_type": "image/png", "preview_size": 244889, "url": "https://www.cg.tuwien.ac.at/research/publications/2017/vad_viktor-2017-WVE/vad_viktor-2017-WVE-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/vad_viktor-2017-WVE/vad_viktor-2017-WVE-:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/vad_viktor-2017-WVE/", "__class": "Publication" }, { "id": "Groeller_2016_P6", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "PorosityAnalyzer: Visual Analysis and Evaluation of Segmentation Pipelines to Determine the Porosity in Fiber-Reinforced Polymers", "date": "2016-10", "abstract": "In this paper we present PorosityAnalyzer, a novel tool for detailed evaluation and visual analysis of pore segmentation pipelines to determine the porosity in fiber-reinforced polymers (FRPs). The presented tool consists of two modules: the computation module and the analysis module. The computation module enables a convenient setup and execution of distributed off-line-computations on industrial 3D X-ray computed tomography datasets. It allows the user to assemble individual segmentation pipelines in the form of single pipeline steps, and to specify the parameter ranges as well as the sampling of the parameter-space of each pipeline segment. The result of a single segmentation run consists of the input parameters, the calculated 3D binary-segmentation mask, the resulting porosity value, and other derived results (e.g., segmentation pipeline runtime). The analysis module presents the data at different levels of detail by drill-down filtering in order to determine accurate and robust segmentation pipelines. Overview visualizations allow to initially compare and evaluate the segmentation pipelines. With a scatter plot matrix (SPLOM), the segmentation pipelines are examined in more detail based on their input and output parameters. Individual segmentation-pipeline runs are selected in the SPLOM and visually examined and compared in 2D slice views and 3D renderings by using aggregated segmentation masks and statistical contour renderings. PorosityAnalyzer has been thoroughly evaluated with the help of twelve domain experts. Two case studies demonstrate the applicability of our proposed concepts and visualization techniques, and show that our tool helps domain experts to gain new insights and improve their workflow efficiency.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 570, "image_height": 436, "name": "Groeller_2016_P6-image.PNG", "type": "image/png", "size": 307225, "path": "Publication:Groeller_2016_P6", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P6/Groeller_2016_P6-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P6/Groeller_2016_P6-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1169, 817, 166, 571, 611 ], "booktitle": "IEEE Conference on Visual Analytics Science and Technology, 2016 (VAST 2016)", "lecturer": [ 651 ], "pages_from": "101", "pages_to": "110", "publisher": "IEEE Computer Society", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://vimeo.com/182984586", "caption": "Video", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 570, "image_height": 436, "name": "Groeller_2016_P6-image.PNG", "type": "image/png", "size": 307225, "path": "Publication:Groeller_2016_P6", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P6/Groeller_2016_P6-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P6/Groeller_2016_P6-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P6/", "__class": "Publication" }, { "id": "Groeller_2016_P4", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Visual Analytics for the Exploration and Assessment of Segmentation Errors", "date": "2016-09-07", "abstract": "Several diagnostic and treatment procedures require the segmentation of anatomical structures from medical images. However, the automatic model-based methods that are often employed, may produce inaccurate segmentations. These, if used as input for diagnosis or treatment, can have detrimental effects for the patients. Currently, an analysis to predict which anatomic regions are more prone to inaccuracies, and to determine how to improve segmentation algorithms, cannot be performed. We propose a visual tool to enable experts, working on model-based segmentation algorithms, to explore and analyze the outcomes and errors of their methods. Our approach supports the exploration of errors in a cohort of pelvic organ segmentations, where the\nperformance of an algorithm can be assessed. Also, it enables the detailed exploration and assessment of segmentation errors, in individual subjects. To the best of our knowledge, there is no other tool with comparable functionality. A usage scenario is employed to explore and illustrate the capabilities of our visual tool. To further assess the value of the proposed tool, we performed an evaluation with five segmentation experts. The evaluation participants confirmed the potential of the tool in providing new insight into their data and employed algorithms. They also gave feedback for future improvements.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 360, "image_height": 335, "name": "Groeller_2016_P4-image.PNG", "type": "image/png", "size": 191339, "path": "Publication:Groeller_2016_P4", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P4/Groeller_2016_P4-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P4/Groeller_2016_P4-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1411, 679, 166, 459, 1412 ], "journal": "Eurographics Workshop on Visual Computing for Biology and Medicine", "lecturer": [ 161, 563, 459 ], "pages_from": "193", "pages_to": "202", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 360, "image_height": 335, "name": "Groeller_2016_P4-image.PNG", "type": "image/png", "size": 191339, "path": "Publication:Groeller_2016_P4", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P4/Groeller_2016_P4-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P4/Groeller_2016_P4-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Groeller_2016_P4-Paper.pdf", "type": "application/pdf", "size": 8104018, "path": "Publication:Groeller_2016_P4", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P4/Groeller_2016_P4-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P4/Groeller_2016_P4-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P4/", "__class": "Publication" }, { "id": "dworschak-2016-szcm", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Semantically Zoomable Choropleth Map", "date": "2016-09", "abstract": "Geographic visualizations, like choropleth maps, are used to visualize data on geographic\nregions. In this thesis a choropleth map was implemented to display quantities of\npublications of scientific texts and papers. With the use of a choropleth map the viewer\nis able to interpret how quantitative data changes on different geographic regions. The\nmain feature that distinguishes the implemented choropleth map from conventional ones\nis the use of map navigation. The choropleth map can be zoomed and panned to different\nmap regions. What makes this map navigation so special is the use of semantic zooming\nto allow the level of detail of the map to change on discrete zoom steps. The change\nof the level of detail means that administrative regions are being divided into smaller\nadministrative regions which are than again colorized individually to create a new, more\ndetailed, choropleth map. Other interactions with the choropleth map are introduced\nadditionally. The other interactions with the map range from the manipulation of the\nmap appearance to filtering the displayed data set.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 637, "image_height": 185, "name": "dworschak-2016-szcm-teaser.png", "type": "image/png", "size": 73351, "path": "Publication:dworschak-2016-szcm", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/dworschak-2016-szcm/dworschak-2016-szcm-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/dworschak-2016-szcm/dworschak-2016-szcm-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1353 ], "date_end": "2016-09", "date_start": "2016-05", "duration": "5 months", "matrikelnr": "1225883", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 637, "image_height": 185, "name": "dworschak-2016-szcm-teaser.png", "type": "image/png", "size": 73351, "path": "Publication:dworschak-2016-szcm", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/dworschak-2016-szcm/dworschak-2016-szcm-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/dworschak-2016-szcm/dworschak-2016-szcm-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "dworschak-2016-szcm-thesis.pdf", "type": "application/pdf", "size": 6720884, "path": "Publication:dworschak-2016-szcm", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/dworschak-2016-szcm/dworschak-2016-szcm-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/dworschak-2016-szcm/dworschak-2016-szcm-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "illvisation", "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/dworschak-2016-szcm/", "__class": "Publication" }, { "id": "schmidt-phd", "type_id": "phdthesis", "tu_id": null, "repositum_id": null, "title": "Scalable Comparative Visualization", "date": "2016-06-28", "abstract": "The comparison of two or more objects is getting an increasingly important task in data analysis. Visualization systems successively have to move from representing one phenomenon to allowing users to analyze several datasets at once. Visualization systems can support the users in several ways. Firstly, comparison tasks can be supported in a very intuitive way by allowing users to place objects that should be compared in an appropriate context. Secondly, visualization systems can explicitly compute differences among the datasets and present the results to the user. In comparative visualization, researchers are working on new approaches for computer-supported techniques that provide data comparison functionality. Techniques from this research field can be used to compare two objects with each other, but often reach their limits if a multitude of objects (i.e., 100 or more) have to be compared. Large data collections that contain a lot of individual, but related, datasets with slightly different characteristics can be called ensembles. The individual datasets being part of an ensemble are called the ensemble members. Ensembles have been created in the simulation domain, especially for weather and climate research, for already quite some time. These domains were greatly driving the development of ensemble visualization techniques. Due to the availability of affordable computing resources and the multitude of different analysis algorithms (e.g., for segmentation), other domains nowadays also face similar problems. All together, this shows a great need for ensemble visualization techniques in various domains. Ensembles can either be analyzed in a feature-based or in a location-based way. In the case of a location-based analysis, the ensemble members are compared based on certain spatial data positions of interest. For such an analysis, local selection and analysis techniques for ensembles are needed.\n\nIn the course of this thesis different visual analytics techniques for the comparative visualization of datasets have been researched. A special focus has been set on providing scalable techniques, which makes them also suitable for ensemble datasets. The proposed techniques operate on different dataset types in 2D and 3D. In the first part of the thesis, a visual analytics approach for the analysis of 2D image datasets is introduced. The technique analyzes localized differences in 2D images. The approach not only identifies differences in the data, but also provides a technique to quickly find out what the differences are, and judge upon the underlying data. This way patterns can be found in the data, and outliers can be identified very quickly. As a second part of the thesis, a scalable application for the comparison of several similar 3D mesh datasets is described. Such meshes may be, for example, created by point-cloud reconstruction algorithms, using different parameter settings. Similar to the proposed technique for the comparison of 2D images, this application is also scalable to a large number of individual datasets. The application enables the automatic comparison of the meshes, searches interesting regions in the data, and allows users to also concentrate on local regions of interest. The analysis of the local regions is in this case done in 3D. The application provides the possibility to arrange local regions in a parallel coordinates plot. The regions are represented by the axes in the plot, and the input meshes are depicted as polylines. This way it can be very quickly spotted whether meshes produce good/bad results in a certain local region. In the third and last part of the thesis, a technique for the interactive analysis of local regions in a volume ensemble dataset is introduced. Users can pick regions of interest, and these regions can be arranged in a graph according to their similarity. The graph can then be used to detect similar regions with a similar data distribution within the ensemble, and to compare individual ensemble members against the rest of the ensemble. All proposed techniques and applications have been tested with real-world datasets from different domains. The results clearly show the usefulness of the techniques for the comparative analysis of ensembles.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 603, "image_height": 446, "name": "schmidt-phd-teaser.png", "type": "image/png", "size": 11954, "path": "Publication:schmidt-phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/schmidt-phd/schmidt-phd-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/schmidt-phd/schmidt-phd-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 950 ], "date_end": "2016", "date_start": "2011", "reviewer_1": [ 166 ], "reviewer_2": [ 161 ], "rigorosum": "2016-06-28", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 603, "image_height": 446, "name": "schmidt-phd-teaser.png", "type": "image/png", "size": 11954, "path": "Publication:schmidt-phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/schmidt-phd/schmidt-phd-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/schmidt-phd/schmidt-phd-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 589, "preview_image_height": 460, "name": "schmidt-phd-thesis.pdf", "type": "application/pdf", "size": 42185190, "path": "Publication:schmidt-phd", "preview_name": "schmidt-phd-thesis:preview.png", "preview_type": "image/png", "preview_size": 814656, "url": "https://www.cg.tuwien.ac.at/research/publications/2016/schmidt-phd/schmidt-phd-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/schmidt-phd/schmidt-phd-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "ViMaL", "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/schmidt-phd/", "__class": "Publication" }, { "id": "Gadllah_Hani_2016", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Comparative Visualization of the Circle of Willis", "date": "2016-06", "abstract": "The human brain is supplied with blood by arteries that form a collateral circulation, the so-called Circle of Willis (CoW). The anatomy of the CoW varies considerably among the population. In fact, depending on the study, just 13% to 72% of the population does have the typical textbook illustration of the CoW. Although divergent configurations are usually not pathological, some incomplete configurations increase the risk of stroke.\nFurthermore, studies suggest an association between certain neurological diseases and abnormal configurations of the CoW. Thus, for the diagnosis and treatment of diverse neurological diseases the assessment of the patient’s CoW is an important issue. This thesis addresses the development of a software for a comparative visualization of the CoWs\nof a population with the CoWs of a second population. For this purpose, an average CoW is calculated for each of the populations. The two resulting CoWs are then visualized side-by-side, so that the viewer is able to distinguish differences between the CoWs of the two populations with relatively little effort. The aim of this visualization is the support\nof studies that consider the clinical significance of the different CoW configurations as well as the support of diagnosis and treatment of diseases that are caused by an abnormal configuration of the CoW. The latter can be achieved by comparing the patient’s CoW with datasets of risk groups or with a dataset of a healthy population. ", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 909, "image_height": 804, "name": "Gadllah_Hani_2016-image.png", "type": "image/png", "size": 120201, "path": "Publication:Gadllah_Hani_2016", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Gadllah_Hani_2016/Gadllah_Hani_2016-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Gadllah_Hani_2016/Gadllah_Hani_2016-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1356 ], "date_end": "2016-06", "date_start": "2016-02", "matrikelnr": "1128636", "supervisor": [ 166 ], "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor Thesis", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 909, "preview_image_height": 804, "name": "Gadllah_Hani_2016-Bachelor Thesis.pdf", "type": "application/pdf", "size": 1537208, "path": "Publication:Gadllah_Hani_2016", "preview_name": "Gadllah_Hani_2016-Bachelor Thesis:preview.png", "preview_type": "image/png", "preview_size": 120201, "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Gadllah_Hani_2016/Gadllah_Hani_2016-Bachelor Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Gadllah_Hani_2016/Gadllah_Hani_2016-Bachelor Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 909, "image_height": 804, "name": "Gadllah_Hani_2016-image.png", "type": "image/png", "size": 120201, "path": "Publication:Gadllah_Hani_2016", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Gadllah_Hani_2016/Gadllah_Hani_2016-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Gadllah_Hani_2016/Gadllah_Hani_2016-image:thumb{{size}}.png" } ], "projects_workgroups": [ "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Gadllah_Hani_2016/", "__class": "Publication" }, { "id": "ortner-2016-tunnel", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Visual analytics and rendering for tunnel crack analysis", "date": "2016-05-11", "abstract": "The visual analysis of surface cracks plays an essential role in tunnel maintenance when assessing the condition of a tunnel. To identify patterns of cracks, which endanger the structural integrity of its concrete surface, analysts need an integrated solution for visual analysis of geometric and multivariate data to decide if issuing a repair project is necessary. The primary contribution of this work is a design study, supporting tunnel crack analysis by tightly integrating geometric and attribute views to allow users a holistic visual analysis of geometric representations and multivariate attributes. Our secondary contribution is Visual Analytics and Rendering, a methodological approach which addresses challenges and recurring design questions in integrated systems. We evaluated the tunnel crack analysis solution in informal feedback sessions with experts from tunnel maintenance and surveying. We substantiated the derived methodology by providing guidelines and linking it to examples from the literature.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 750, "image_height": 340, "name": "ortner-2016-tunnel-teaser.gif", "type": "image/gif", "size": 97212, "path": "Publication:ortner-2016-tunnel", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-tunnel/ortner-2016-tunnel-teaser.gif", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-tunnel/ortner-2016-tunnel-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1277, 1072, 451, 205, 166 ], "event": "Computer Graphics International (CGI)", "journal": "The Visual Computer", "number": "6", "pages_from": "859", "pages_to": "869", "volume": "32", "research_areas": [ "InfoVis" ], "keywords": [ "Integration of spatial and non-spatial data", "Methodology", "Visual analytics" ], "weblinks": [ { "href": "http://link.springer.com/article/10.1007/s00371-016-1257-5", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 750, "image_height": 340, "name": "ortner-2016-tunnel-teaser.gif", "type": "image/gif", "size": 97212, "path": "Publication:ortner-2016-tunnel", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-tunnel/ortner-2016-tunnel-teaser.gif", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-tunnel/ortner-2016-tunnel-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-tunnel/", "__class": "Publication" }, { "id": "TR1862162", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Visual Analysis of Volume Ensembles Based on Local Features", "date": "2016-05", "abstract": "Ensemble datasets describe a specific phenomenon (e.g., a simulation scenario or a measurements series) through a large set of individual ensemble members. These individual members typically do not differ too much from each other but rather feature slightly changing characteristics. In many cases, the ensemble members are defined in 3D space, which implies severe challenges when exploring the complete ensembles such as handling occlusions, focus and context or its sheer datasize. In this paper we address these challenges and put our focus on the exploration of local features in 3D volumetric ensemble datasets, not only by visualizing local characteristics, but also by identifying connections to other local features with similar characteristics in the data. We evaluate the variance in the dataset and use the the spatial median (medoid) of the ensemble to visualize the differences in the dataset. This medoid is subsequently used as a representative of the ensemble in 3D. The variance information is used to guide users during the exploration, as regions of high variance also indicate larger changes within the ensemble members. The local characteristics of the regions can be explored by using our proposed 3D probing widgets. These widgets consist of a 3D sphere, which can be positioned at any point in 3D space. While moving a widget, the local data characteristics at the corresponding position are shown in a separate detail view, which depicts the local outliers and their surfaces in comparison to the medoid surface. The 3D probing widgets can also be fixed at a user-defined position of interest. The fixed probing widgets are arranged in a similarity graph to indicate similar local data characteristics. The similarity graph thus allows to explore whether high variances in a certain region are caused by the same dataset members or not. Finally, it is also possible to compare a single member against the rest of the ensemble. We evaluate our technique through two demonstration cases using volumetric multi-label segmentation mask datasets, two from the\nindustrial domain and two from the medical domain.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 599, "image_height": 277, "name": "TR1862162-teaser.png", "type": "image/png", "size": 498904, "path": "Publication:TR1862162", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 950, 1191, 799, 983, 166, 161, 611 ], "number": "TR-186-2-16-2", "research_areas": [ "InfoVis" ], "keywords": [ "ensemble visualization", "guided local exploration", "variance analysis" ], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 599, "image_height": 277, "name": "TR1862162-teaser.png", "type": "image/png", "size": 498904, "path": "Publication:TR1862162", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "tech-report", "main_file": false, "use_in_gallery": false, "access": "public", "name": "TR1862162-tech-report.pdf", "type": "application/pdf", "size": 5108648, "path": "Publication:TR1862162", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-tech-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-tech-report:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/", "__class": "Publication" }, { "id": "klein-2016-WCL", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "Towards Interactive Visual Exploration of Parallel Programs using a Domain-Specific Language", "date": "2016-04", "abstract": "The use of GPUs and the massively parallel computing paradigm have become wide-spread. We describe a framework for the interactive visualization and visual analysis of the run-time behavior of massively parallel programs, especially OpenCL kernels. This facilitates understanding a program's function and structure, finding the causes of possible slowdowns, locating program bugs, and interactively exploring and visually comparing different code variants in order to improve performance and correctness. Our approach enables very specific, user-centered analysis, both in terms of the recording of the run-time behavior and the visualization itself. Instead of having to manually write instrumented code to record data, simple code annotations tell the source-to-source compiler which code instrumentation to generate automatically. The visualization part of our framework then enables the interactive analysis of kernel run-time behavior in a way that can be very specific to a particular problem or optimization goal, such as analyzing the causes of memory bank conflicts or understanding an entire parallel algorithm.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1285, "image_height": 369, "name": "klein-2016-WCL-image.png", "type": "image/png", "size": 297574, "path": "Publication:klein-2016-WCL", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/klein-2016-WCL-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/klein-2016-WCL-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1285, 161, 166, 226, 488 ], "event": "4th International Workshop on OpenCL (IWOCL '16)", "location": "Vienna, Austria", "publisher": "ACM", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "extended_abstract", "main_file": false, "use_in_gallery": false, "access": "public", "name": "klein-2016-WCL-extended_abstract.pdf", "type": "application/pdf", "size": 866287, "path": "Publication:klein-2016-WCL", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/klein-2016-WCL-extended_abstract.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/klein-2016-WCL-extended_abstract:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1285, "image_height": 369, "name": "klein-2016-WCL-image.png", "type": "image/png", "size": 297574, "path": "Publication:klein-2016-WCL", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/klein-2016-WCL-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/klein-2016-WCL-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": false, "use_in_gallery": false, "access": "public", "name": "klein-2016-WCL-poster.pdf", "type": "application/pdf", "size": 3606134, "path": "Publication:klein-2016-WCL", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/klein-2016-WCL-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/klein-2016-WCL-poster:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/", "__class": "Publication" }, { "id": "ortner-2016-visaware", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Vis-a-ware: Integrating spatial and non-spatial visualization for visibility-aware urban planning", "date": "2016-01-22", "abstract": "3D visibility analysis plays a key role in urban planning for assessing the visual impact of proposed buildings on the cityscape. A call for proposals typically yields around 30 candidate buildings that need to be evaluated with respect to selected viewpoints. Current visibility analysis methods are very time-consuming and limited to a small number of viewpoints. Further, analysts neither have measures to evaluate candidates quantitatively, nor to compare them efficiently. The primary contribution of this work is the design study of Vis-A-Ware, a visualization system to qualitatively and quantitatively evaluate, rank, and compare visibility data of candidate buildings with respect to a large number of viewpoints. Vis-A-Ware features a 3D spatial view of an urban scene and non-spatial views of data derived from visibility evaluations, which are tightly integrated by linked interaction. To enable a quantitative evaluation we developed four metrics in accordance with experts from urban planning. We illustrate the applicability of Vis-A-Ware on the basis of a use case scenario and present results from informal feedback sessions with domain experts from urban planning and development. This feedback suggests that Vis-A-Ware is a valuable tool for visibility analysis allowing analysts to answer complex questions more efficiently and objectively.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1552, "image_height": 900, "name": "ortner-2016-visaware-teaser.png", "type": "image/png", "size": 348718, "path": "Publication:ortner-2016-visaware", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-visaware/ortner-2016-visaware-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-visaware/ortner-2016-visaware-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1277, 1072, 1387, 205, 451, 166 ], "issn": "1077-2626 ", "journal": "Visualization and Computer Graphics, IEEE Transactions on", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://ieeexplore.ieee.org/document/7390069/?arnumber=7390069", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1552, "image_height": 900, "name": "ortner-2016-visaware-teaser.png", "type": "image/png", "size": 348718, "path": "Publication:ortner-2016-visaware", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-visaware/ortner-2016-visaware-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-visaware/ortner-2016-visaware-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-visaware/", "__class": "Publication" }, { "id": "sorger-2015-litevis", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "LiteVis: Integrated Visualization for Simulation-Based Decision Support in Lighting Design", "date": "2016-01", "abstract": "State-of-the-art lighting design is based on physically accurate lighting simulations of scenes such as offices. The simulation results support lighting designers in the creation of lighting configurations, which must meet contradicting customer objectives regarding quality and price while conforming to industry standards. However, current tools for lighting design impede rapid feedback cycles. On the one side, they decouple analysis and simulation specification. On the other side, they lack capabilities for a detailed comparison of multiple configurations. The primary contribution of this paper is a design study of LiteVis, a system for efficient decision support in lighting design. LiteVis tightly integrates global illumination-based lighting simulation, a spatial representation of the scene, and non-spatial visualizations of parameters and result indicators. This enables an efficient iterative cycle of simulation parametrization and analysis. Specifically, a novel visualization supports decision making by ranking simulated lighting configurations with regard to a weight-based prioritization of objectives that considers both spatial and non-spatial characteristics. In the spatial domain, novel concepts support a detailed comparison of illumination scenarios. We demonstrate LiteVis using a real-world use case and report qualitative feedback of lighting designers. This feedback indicates that LiteVis successfully supports lighting designers to achieve key tasks more efficiently and with greater certainty.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "thumb", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1860, "image_height": 1516, "name": "sorger-2015-litevis-thumb.png", "type": "image/png", "size": 253297, "path": "Publication:sorger-2015-litevis", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-thumb.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-thumb:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1072, 1277, 659, 678, 166, 451 ], "event": "IEEE Vis", "issn": "1077-2626 ", "journal": "Visualization and Computer Graphics, IEEE Transactions on", "lecturer": [ 1072 ], "location": "Chicago", "number": "1", "pages_from": "290", "pages_to": "299", "volume": "22", "research_areas": [ "InfoVis", "Rendering" ], "keywords": [ "Integrating Spatial and Non-Spatial Data" ], "weblinks": [ { "href": "http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7192703&tag=1", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "30sec preview", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 1280, "preview_image_height": 720, "name": "sorger-2015-litevis-30sec preview.mp4", "type": "video/mp4", "size": 20482898, "path": "Publication:sorger-2015-litevis", "preview_name": "sorger-2015-litevis-30sec preview:preview.png", "preview_type": "image/jpeg", "preview_size": 77105, "url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-30sec preview.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-30sec preview:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-30sec preview:video.mp4" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "sorger-2015-litevis-paper.pdf", "type": "application/pdf", "size": 14633562, "path": "Publication:sorger-2015-litevis", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-paper:thumb{{size}}.png" }, { "description": "two components of the LiteVis interface, left: the Simulation View, right: ranking of lighting solutions in the Analysis View", "filetitle": "teaser", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 2934, "image_height": 1048, "name": "sorger-2015-litevis-teaser.png", "type": "image/png", "size": 367321, "path": "Publication:sorger-2015-litevis", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thumb", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1860, "image_height": 1516, "name": "sorger-2015-litevis-thumb.png", "type": "image/png", "size": 253297, "path": "Publication:sorger-2015-litevis", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-thumb.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-thumb:thumb{{size}}.png" }, { "description": null, "filetitle": "video demonstration", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1120, "preview_image_height": 630, "name": "sorger-2015-litevis-video demonstration.mp4", "type": "video/mp4", "size": 58980955, "path": "Publication:sorger-2015-litevis", "preview_name": "sorger-2015-litevis-video demonstration:preview.png", "preview_type": "image/jpeg", "preview_size": 52277, "url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-video demonstration.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-video demonstration:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/sorger-2015-litevis-video demonstration:video.mp4" } ], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/", "__class": "Publication" }, { "id": "Chen-Information-2016", "type_id": "book", "tu_id": null, "repositum_id": null, "title": "Information Theory Tools for Visualization", "date": "2016", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1083, 608, 171, 1512, 207, 1513 ], "isbn": "9781498740937", "pages": "194", "publisher": "CRC Press", "research_areas": [ "IllVis", "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Chen-Information-2016/", "__class": "Publication" }, { "id": "Groeller_2016_P1", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": " Visual Analysis of Defects in Glass Fiber Reinforced Polymers for 4DCT Interrupted In situ Tests", "date": "2016", "abstract": "Material engineers use interrupted in situ tensile testing to investigate the damage mechanisms in composite materials. For\neach subsequent scan, the load is incrementally increased until the specimen is completely fractured. During the interrupted in situ testing of glass fiber reinforced polymers (GFRPs) defects of four types are expected to appear: matrix fracture, fiber/matrix debonding, fiber pull-out, and fiber fracture. There is a growing demand for the detection and analysis of these defects among the material engineers. In this paper, we present a novel workflow for the detection, classification, and visual analysis of defects in GFRPs using interrupted in situ tensile tests in combination with X-ray Computed Tomography. The workflow is based on the\nautomatic extraction of defects and fibers. We introduce the automatic Defect Classifier assigning the most suitable type to each defect based on its geometrical features. We present a visual analysis system that integrates four visualization methods: 1) the Defect Viewer highlights defects with visually encoded type in the context of the original CT image, 2) the Defect Density Maps provide an overview of the defect distributions according to type in 2D and 3D, 3) the Final Fracture Surface estimates the material fracture’s location and displays it as a 3D surface, 4) the 3D Magic Lens enables interactive exploration by combining detailed visualizations in the region of interest with overview visualizations as context. In collaboration with material engineers,\nwe evaluate our solution and demonstrate its practical applicability.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 427, "image_height": 107, "name": "Groeller_2016_P1-image.jpg", "type": "image/jpeg", "size": 10634, "path": "Publication:Groeller_2016_P1", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P1/Groeller_2016_P1-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P1/Groeller_2016_P1-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1170, 817, 790, 571, 166, 611 ], "issn": "doi: 10.1111/cgf.12896", "journal": "Computer Graphics Forum (2016)", "number": "3", "pages_from": "201", "pages_to": "210", "volume": " 35", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 427, "image_height": 107, "name": "Groeller_2016_P1-image.jpg", "type": "image/jpeg", "size": 10634, "path": "Publication:Groeller_2016_P1", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P1/Groeller_2016_P1-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P1/Groeller_2016_P1-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Groeller_2016_P1-Paper.pdf", "type": "application/pdf", "size": 3432744, "path": "Publication:Groeller_2016_P1", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P1/Groeller_2016_P1-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P1/Groeller_2016_P1-Paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P1/", "__class": "Publication" }, { "id": "Groeller_2016_P2", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Towards Quantitative Visual Analytics with Structured Brushing and Linked Statistics", "date": "2016", "abstract": "Until now a lot of visual analytics predominantly delivers qualitative results—based, for example, on a continuous color map or a detailed spatial encoding. Important target applications, however, such as medical diagnosis and decision making, clearly benefit from quantitative analysis results. In this paper we propose several specific extensions to the well-established concept of\nlinking&brushing in order to make the analysis results more quantitative. We structure the brushing space in order to improve the reproducibility of the brushing operation, e.g., by introducing the percentile grid. We also enhance the linked visualization with overlaid descriptive statistics to enable a more quantitative reading of the resulting focus+context visualization. Addition-\nally, we introduce two novel brushing techniques: the percentile brush and the Mahalanobis brush. Both use the underlying\ndata to support statistically meaningful interactions with the data. We illustrate the use of the new techniques in the context of two case studies, one based on meteorological data and the other one focused on data from the automotive industry where we evaluate a shaft design in the context of mechanical power transmission in cars.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 340, "image_height": 287, "name": "Groeller_2016_P2-image.jpg", "type": "image/jpeg", "size": 25399, "path": "Publication:Groeller_2016_P2", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P2/Groeller_2016_P2-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P2/Groeller_2016_P2-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1359, 1204, 235, 710, 166, 176 ], "journal": "Computer Graphics Forum (2016)", "location": "EUROVIS 2016", "number": "3", "pages_from": "251", "pages_to": "260", "volume": "35", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 340, "image_height": 287, "name": "Groeller_2016_P2-image.jpg", "type": "image/jpeg", "size": 25399, "path": "Publication:Groeller_2016_P2", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P2/Groeller_2016_P2-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P2/Groeller_2016_P2-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Groeller_2016_P2-paper.pdf", "type": "application/pdf", "size": 12830428, "path": "Publication:Groeller_2016_P2", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P2/Groeller_2016_P2-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P2/Groeller_2016_P2-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P2/", "__class": "Publication" }, { "id": "miao_2016_cgf", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Visual Quantification of the Circle of Willis: An Automated Identification and Standardized Representation", "date": "2016", "abstract": "This paper presents a method for the visual quantification of cerebral arteries, known as the Circle of Willis (CoW). It is an arterial structure with the responsibility of supplying the brain with blood, however, dysfunctions can lead to strokes. The diagnosis of such a time-critical/urgent event depends on the expertise of radiologists and the applied software tools. They use basic display methods of the volumetric data without any support of advanced image processing and visualization techniques. The goal of this paper is to present an automated method for the standardized description of cerebral arteries in stroke patients in order to provide an overview of the CoW's configuration. This novel representation provides visual indications of problematic areas as well as straightforward comparisons between multiple patients. Additionally, we offer a pipeline for extracting the CoW from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) data sets together with an enumeration technique for labelling the arterial segments by detecting the main supplying arteries of the CoW. We evaluated the feasibility of our visual quantification approach in a study of 63 TOF-MRA data sets and compared our findings to those of three radiologists. The obtained results demonstrate that our proposed techniques are effective in detecting the arteries and visually capturing the overall configuration of the CoW.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1900, "image_height": 1842, "name": "miao_2016_cgf-image.png", "type": "image/png", "size": 271848, "path": "Publication:miao_2016_cgf", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1263, 869, 1264, 166 ], "issn": "1467-8659", "journal": "Computer Graphics Forum", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [ "Circle of Willis", "medical visualization", "information visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1900, "image_height": 1842, "name": "miao_2016_cgf-image.png", "type": "image/png", "size": 271848, "path": "Publication:miao_2016_cgf", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "miao_2016_cgf-paper.pdf", "type": "application/pdf", "size": 5537482, "path": "Publication:miao_2016_cgf", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/", "__class": "Publication" }, { "id": "raidou_eurovis16", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Visual Analysis of Tumor Control Models for Prediction of Radiotherapy Response.", "date": "2016", "abstract": "In radiotherapy, tumors are irradiated with a high dose, while surrounding healthy tissues are spared. To quantify the prob-ability that a tumor is effectively treated with a given dose, statistical models were built and employed in clinical research.These are called tumor control probability (TCP) models. Recently, TCP models started incorporating additional informationfrom imaging modalities. In this way, patient-specific properties of tumor tissues are included, improving the radiobiologicalaccuracy of models. Yet, the employed imaging modalities are subject to uncertainties with significant impact on the modelingoutcome, while the models are sensitive to a number of parameter assumptions. Currently, uncertainty and parameter sensitivityare not incorporated in the analysis, due to time and resource constraints. To this end, we propose a visual tool that enablesclinical researchers working on TCP modeling, to explore the information provided by their models, to discover new knowledgeand to confirm or generate hypotheses within their data. Our approach incorporates the following four main components: (1)It supports the exploration of uncertainty and its effect on TCP models; (2) It facilitates parameter sensitivity analysis to com-mon assumptions; (3) It enables the identification of inter-patient response variability; (4) It allows starting the analysis fromthe desired treatment outcome, to identify treatment strategies that achieve it. We conducted an evaluation with nine clinicalresearchers. All participants agreed that the proposed visual tool provides better understanding and new opportunities for theexploration and analysis of TCP modeling.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_eurovis16-.pdf", "type": "application/pdf", "size": 2982085, "path": "Publication:raidou_eurovis16", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_eurovis16/raidou_eurovis16-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_eurovis16/raidou_eurovis16-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1444, 1445, 1446, 1447, 679, 459 ], "journal": "EuroVis - Eurographics/IEEE-VGTC Symposium on Visualization 2016", "lecturer": [ 1448, 1449, 652 ], "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_eurovis16-.pdf", "type": "application/pdf", "size": 2982085, "path": "Publication:raidou_eurovis16", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_eurovis16/raidou_eurovis16-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_eurovis16/raidou_eurovis16-:thumb{{size}}.png" }, { "description": null, "filetitle": "demo", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_eurovis16-demo.mp4", "type": "video/mp4", "size": 43216314, "path": "Publication:raidou_eurovis16", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_eurovis16/raidou_eurovis16-demo.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_eurovis16/raidou_eurovis16-demo:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_eurovis16/raidou_eurovis16-demo:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_eurovis16/", "__class": "Publication" }, { "id": "raidou_miccai16", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Employing Visual Analytics to Aid the Design of White Matter Hyperintensity Classifiers.", "date": "2016", "abstract": "Accurate segmentation of brain white matter hyperintensi-ties (WMHs) is important for prognosis and disease monitoring. To thisend, classi\fers are often trained { usually, using T1 and FLAIR weightedMR images. Incorporating additional features, derived from di\u000busionweighted MRI, could improve classi\fcation. However, the multitude ofdi\u000busion-derived features requires selecting the most adequate. For this,automated feature selection is commonly employed, which can often besub-optimal. In this work, we propose a di\u000berent approach, introducing asemi-automated pipeline to select interactively features for WMH classi\f-cation. The advantage of this solution is the integration of the knowledgeand skills of experts in the process. In our pipeline, a Visual Analytics(VA) system is employed, to enable user-driven feature selection. Theresulting features are T1, FLAIR, Mean Di\u000busivity (MD), and RadialDi\u000busivity (RD) { and secondarily,CSand Fractional Anisotropy (FA).The next step in the pipeline is to train a classi\fer with these features,and compare its results to a similar classi\fer, used in previous work withautomated feature selection. Finally, VA is employed again, to analyzeand understand the classi\fer performance and results.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1433, 1434, 1435, 1436, 679, 459 ], "journal": "Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "demo", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_miccai16-demo.mp4", "type": "video/mp4", "size": 40385545, "path": "Publication:raidou_miccai16", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_miccai16/raidou_miccai16-demo.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_miccai16/raidou_miccai16-demo:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_miccai16/raidou_miccai16-demo:video.mp4" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_miccai16-paper.pdf", "type": "application/pdf", "size": 927133, "path": "Publication:raidou_miccai16", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_miccai16/raidou_miccai16-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_miccai16/raidou_miccai16-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_miccai16/", "__class": "Publication" }, { "id": "Diehl_2015", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "Albero: A Visual Analytics Tool for Probabilistic Weather Forecasting.", "date": "2015-11", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1121, 1396, 235, 1122, 741, 166, 161 ], "date_from": "2015-11", "date_to": "2015-11", "event": "Poster at Workshop Big Data & Environment", "location": "University of Buenos Aires", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Diehl_2015/", "__class": "Publication" }, { "id": "Klein_Tobias_2015TIV", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language", "date": "2015-11", "abstract": "The utilization of GPUs and the massively parallel computing paradigm have become increasingly prominent in many research domains. Recent developments of platforms, such as\nOpenCL and CUDA, enable the usage of heterogeneous parallel computing in a wide-spread field. However, the efficient utilization of parallel hardware requires profound knowledge of\nparallel programming and the hardware itself.\n\nOur approach presents a domain-specific language that facilitates fast prototyping of parallel programs, and a visual explorer which reveals their execution behavior. With the aid\nof our visualizations, interactions with the hardware become visible, supporting the comprehensibility\nof the program and its utilization of the hardware components. Furthermore, we\naggregate behavior that leads to common issues in parallel programming and present it in a clearly structured view to the user.\n\nWe augment the standard methods for debugging and profiling by a visual approach that enables a more problem-specific, fine-grained way of analyzing parallel code. Our framework parses all program code and user-specified annotations in order to enable automatic, yet configurable code instrumentation. The resulting recordings are directly linked to interactive visualizations created with the well-known D3 (data-driven documents) framework.\n\nTo demonstrate our approach, we present two case studies about the visual analysis of memory bank conflicts and branch divergence. They investigate different parallel reduction\nimplementations and a common image processing example (all from the NVIDIA OpenCL SDK). We show that our visualizations provide immediate visual insight in the execution behavior of the program and that the performance influence of the implementations is directly reflected visually.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1114, "image_height": 443, "name": "Klein_Tobias_2015TIV-Image.jpg", "type": "image/jpeg", "size": 40401, "path": "Publication:Klein_Tobias_2015TIV", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Klein_Tobias_2015TIV/Klein_Tobias_2015TIV-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Klein_Tobias_2015TIV/Klein_Tobias_2015TIV-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1285 ], "matrikelnr": "1129861", "supervisor": [ 166, 488 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1114, "image_height": 443, "name": "Klein_Tobias_2015TIV-Image.jpg", "type": "image/jpeg", "size": 40401, "path": "Publication:Klein_Tobias_2015TIV", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Klein_Tobias_2015TIV/Klein_Tobias_2015TIV-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Klein_Tobias_2015TIV/Klein_Tobias_2015TIV-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Klein_Tobias_2015TIV-Poster.pdf", "type": "application/pdf", "size": 520222, "path": "Publication:Klein_Tobias_2015TIV", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Klein_Tobias_2015TIV/Klein_Tobias_2015TIV-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Klein_Tobias_2015TIV/Klein_Tobias_2015TIV-Poster:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Klein_Tobias_2015TIV-Thesis.pdf", "type": "application/pdf", "size": 4404334, "path": "Publication:Klein_Tobias_2015TIV", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Klein_Tobias_2015TIV/Klein_Tobias_2015TIV-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Klein_Tobias_2015TIV/Klein_Tobias_2015TIV-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Klein_Tobias_2015TIV/", "__class": "Publication" }, { "id": "Ganuza_ML_2015_ISA", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "Interactive Semi-Automatic Categorization for Spinel Group Minerals", "date": "2015-10", "abstract": "Spinel group minerals are excellent indicators of geological environments (tectonic settings). In 2001, Barnes and Roeder defined a set of contours corresponding to compositional fields for spinel group minerals. Geologists typically use this contours to estimate the tectonic environment where a particular spinel composition could have been formed. This task is prone to errors and requires tedious manual comparison of overlapping diagrams. We introduce a semi-automatic, interactive detection of tectonic settings for an arbitrary dataset based on the Barnes and Roeder contours. The new approach integrates the mentioned contours and includes a novel interaction called contour brush. The new methodology is integrated in the Spinel Explorer system and it improves the scientist's workflow significantly.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1228, 1233, 1229, 408, 1232, 166, 235 ], "date_from": "2015-10-25", "date_to": "2015-10-30", "event": "2015 IEEE Conference on Visual Analytics Science and Technology (VAST) (2015)", "isbn": " 978-1-4673-9783-4", "location": "Chicago, IL, USA ", "pages_from": "197", "pages_to": "198", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Ganuza_ML_2015_ISA/", "__class": "Publication" }, { "id": "sorger-2015-taxintec", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "A Taxonomy of Integration Techniques for Spatial and Non-Spatial Visualizations", "date": "2015-10", "abstract": "Research on visual data representations is traditionally classified into methods assuming an inherent mapping from data values to spatial coordinates (scientific visualization and real-time rendering) and methods for abstract data lacking explicit spatial references (information visualization). In practice, however, many applications need to analyze data comprising abstract and spatial information, thereby spanning both visualization domains. Traditional classification schemes do not support a formal description of these integrated systems. The contribution of this paper is a taxonomy that describes a holistic design space for integrating components of spatial and abstract visualizations. We structure a visualization into three components: Data, Visual, and Navigation. These components can be linked to build integrated visualizations. Our taxonomy provides an alternative view on the field of visualization in a time where the border between scientific and information visualization becomes blurred.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 541, "image_height": 393, "name": "sorger-2015-taxintec-teaser.png", "type": "image/png", "size": 23806, "path": "Publication:sorger-2015-taxintec", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/sorger-2015-taxintec/sorger-2015-taxintec-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/sorger-2015-taxintec/sorger-2015-taxintec-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1072, 1277, 451, 205, 166 ], "booktitle": "20th International Symposium on Vision, Modeling and Visualization (VMV 2015)", "date_from": "2015-10-07", "date_to": "2015-10-10", "editor": "David Bommes and Tobias Ritschel and Thomas Schultz", "issn": "0302-9743", "lecturer": [ 1072 ], "location": "Aachen, Germany", "publisher": "The Eurographics Association", "series": "Springer Lecture Notes in Computer Science (LNCS) series", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "sorger-2015-taxintec-paper.pdf", "type": "application/pdf", "size": 456732, "path": "Publication:sorger-2015-taxintec", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/sorger-2015-taxintec/sorger-2015-taxintec-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/sorger-2015-taxintec/sorger-2015-taxintec-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 541, "image_height": 393, "name": "sorger-2015-taxintec-teaser.png", "type": "image/png", "size": 23806, "path": "Publication:sorger-2015-taxintec", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/sorger-2015-taxintec/sorger-2015-taxintec-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/sorger-2015-taxintec/sorger-2015-taxintec-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/sorger-2015-taxintec/", "__class": "Publication" }, { "id": "Miao_2015_VCBM", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "CoWRadar: Visual Quantification of the Circle of Willis in Stroke Patients", "date": "2015-09", "abstract": "This paper presents a method for the visual quantification of cerebral arteries, known as the Circle of Willis (CoW).\nThe CoW is an arterial structure that is responsible for the brain’s blood supply. Dysfunctions of this arterial circle\ncan lead to strokes. The diagnosis relies on the radiologist’s expertise and the software tools used. These tools\nconsist of very basic display methods of the volumetric data without support of advanced technologies in medical\nimage processing and visualization. The goal of this paper is to create an automated method for the standardized\ndescription of cerebral arteries in stroke patients in order to provide an overview of the CoW’s configuration. This novel display provides visual indications of problematic areas as well as straightforward comparisons between\nmultiple patients. Additionally, we offer a pipeline for extracting the CoW from Time-of-Flight Magnetic Resonance\nAngiography (TOF-MRA) data sets. An enumeration technique for the labeling of the arterial segments is therefore\nsuggested. We also propose a method for detecting the CoW’s main supplying arteries by analyzing the coronal,\nsagittal and transverse image planes of the data sets. We evaluated the feasibility of our visual quantification\napproach in a study of 63 TOF-MRA data sets and compared our findings to those of three radiologists. The obtained results demonstrate that our proposed techniques are effective in detecting the arteries of the CoW.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 552, "image_height": 470, "name": "Miao_2015_VCBM-image.png", "type": "image/png", "size": 310337, "path": "Publication:Miao_2015_VCBM", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/Miao_2015_VCBM-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/Miao_2015_VCBM-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1263, 869, 1264, 166 ], "booktitle": "EG Workshop on Visual Computing for Biology and Medicine", "date_from": "2015-09-14", "date_to": "2015-09-15", "editor": "Katja Bühler and Lars Linsen and Nigel W. John", "isbn": "978-3-905674-82-8", "issn": "2070-5786", "lecturer": [ 1263 ], "location": "Chester, United Kingdom", "organization": "EG Digital Library", "pages_from": "1", "pages_to": "10", "publisher": "The Eurographics Association", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": "A short demonstration", "filetitle": "demo", "main_file": true, "use_in_gallery": false, "access": "public", "preview_image_width": 1280, "preview_image_height": 720, "name": "Miao_2015_VCBM-demo.mp4", "type": "video/mp4", "size": 28569430, "path": "Publication:Miao_2015_VCBM", "preview_name": "Miao_2015_VCBM-demo:preview.png", "preview_type": "image/jpeg", "preview_size": 50335, "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/Miao_2015_VCBM-demo.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/Miao_2015_VCBM-demo:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/Miao_2015_VCBM-demo:video.mp4" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 552, "image_height": 470, "name": "Miao_2015_VCBM-image.png", "type": "image/png", "size": 310337, "path": "Publication:Miao_2015_VCBM", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/Miao_2015_VCBM-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/Miao_2015_VCBM-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Miao_2015_VCBM-paper.pdf", "type": "application/pdf", "size": 6127015, "path": "Publication:Miao_2015_VCBM", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/Miao_2015_VCBM-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/Miao_2015_VCBM-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/", "__class": "Publication" }, { "id": "Bruckner_Stefan_2015_VAS", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting", "date": "2015-05", "abstract": "Weather conditions affect multiple aspects of human life such as economy, safety, security, and social activities. For\nthis reason, weather forecast plays a major role in society. Currently weather forecasts are based on Numerical\nWeather Prediction (NWP) models that generate a representation of the atmospheric flow. Interactive visualization\nof geo-spatial data has been widely used in order to facilitate the analysis of NWP models. This paper presents a\nvisualization system for the analysis of spatio-temporal patterns in short-term weather forecasts. For this purpose,\nwe provide an interactive visualization interface that guides users from simple visual overviews to more advanced\nvisualization techniques. Our solution presents multiple views that include a timeline with geo-referenced maps, an\nintegrated webmap view, a forecast operation tool, a curve-pattern selector, spatial filters, and a linked meteogram.\nTwo key contributions of this work are the timeline with geo-referenced maps and the curve-pattern selector. The\nlatter provides novel functionality that allows users to specify and search for meaningful patterns in the data.\nThe visual interface of our solution allows users to detect both possible weather trends and errors in the weather\nforecast model.We illustrate the usage of our solution with a series of case studies that were designed and validated\nin collaboration with domain experts.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1121, 166, 161 ], "booktitle": "Computer Graphic Forum", "date_from": "2015-05-25", "date_to": "2015-05-29", "lecturer": [ 161 ], "location": "Cagliari, Sardinia, Italy", "pages_from": "381", "pages_to": "390", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Bruckner_Stefan_2015_VAS-Paper.pdf", "type": "application/pdf", "size": 2391385, "path": "Publication:Bruckner_Stefan_2015_VAS", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Bruckner_Stefan_2015_VAS/Bruckner_Stefan_2015_VAS-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Bruckner_Stefan_2015_VAS/Bruckner_Stefan_2015_VAS-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Bruckner_Stefan_2015_VAS/", "__class": "Publication" }, { "id": "Matkovic_Kresimir_2015_", "type_id": "habilthesis", "tu_id": null, "repositum_id": "20.500.12708/8001", "title": "Interactive Visual Analysis of Multi-Parameter Scientific Data", "date": "2015-05", "abstract": "Increasing complexity and a large number of control parameters make the design and understanding of modern engineering systems impossible without simulation. Advances in simulation technology and the ability to run multiple simulations with different sets of parameters pose new challenges for analysis techniques. The resulting\ndata is often heterogeneous. A single data point does not contain scalars or\nvectors only, as usual. Instead, a single data point contains scalars, time series, and other types of mappings. Such a data model is common in many domains. Interactive visual analysis utilizes a tight feedback loop of computation/visualization and user interaction to facilitate knowledge discovery in complex datasets.\n\nOur research extends the visual analysis technology to challenging heterogeneous data, in particular to a combination of multivariate data and more complex data types, such as functions, for example. Furthermore, we focus on developing a structured model for interactive visual analysis which supports a synergetic combination\nof user interaction and computational analysis.\n\nThe concept of height surfaces and function graphs is a proven and well developed mechanism for the analysis of a single mapping. The state of the art when a set of such mappings is analyzed suggested a use of different descriptors or aggregates in the analysis. Our research makes it possible to analyze a whole set of mappings (function graphs, or height surfaces, for example) while keeping the original data. We advance the interactive visual analysis to cope with complex scientific data. Most of the analysis techniques consider the data as a static source. Such an\napproach often hinders the analysis. We introduce a concept of interactive visual steering for simulation ensembles. We link the data generation and data exploration and analysis tasks in a single workflow. This makes it possible to tune and optimize complex systems having high dimensional parameter space and complex outputs.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 235 ], "date_end": "2014", "date_start": "2005", "doi": "10.34726/hss.2016.40602", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Habilitation Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Matkovic_Kresimir_2015_-Habilitation Thesis.pdf", "type": "application/pdf", "size": 24142604, "path": "Publication:Matkovic_Kresimir_2015_", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Matkovic_Kresimir_2015_/Matkovic_Kresimir_2015_-Habilitation Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Matkovic_Kresimir_2015_/Matkovic_Kresimir_2015_-Habilitation Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Matkovic_Kresimir_2015_/", "__class": "Publication" }, { "id": "Miao_Haichao_2015_VQC", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Visual Quantification of the Circle of Willis in Stroke Patients", "date": "2015-04", "abstract": "This thesis presents a novel method for the visual quantification of cerebral arteries. The Circle of Willis (CoW) is an arterial structure that is responsible for the brain’s blood supply. Dysfunctions of this arterial circle can lead to strokes. The diagnosis of stroke patients is complex\nand relies on the radiologist’s expertise and the software tools used. These tools consist of very basic display methods of the volumetric data without support of state-of-the-art technologies in medical image processing and visualization. The goal of this thesis is to create an automated\nmethod for the standardized visualization of cerebral arteries in stroke patients in order to allow visual indications of problematic areas as well as straightforward inter-patient comparisons.\n\nPrior to the visualization, this work offers a solution for the extraction of the CoW from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) images. An enumeration technique for the labeling of the segments is therefore suggested. Furthermore, it proposes a method for the detection of the CoW’s main supplying arteries by analyzing the coronal, sagittal and transverse image planes of the volume. This work gives a comprehensive account of the entire pipeline that is required to extract the arteries in the CoW and to build a model for the standardized\nvisualization. The final goal of this thesis is to create an effective display of the arteries based on a radial tree layout.\n\nThe feasibility of the visual quantification method is tested in a study of 63 TOF-MRAs. With the proposed methodology applied to the subjects, the results were compared to the findings from radiologists. The obtained results demonstrate that the proposed techniques are effective\nin detecting the arteries of the CoW. Finally, we focused our methods on the identification of the main arteries.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 552, "image_height": 470, "name": "Miao_Haichao_2015_VQC-.png", "type": "image/png", "size": 310337, "path": "Publication:Miao_Haichao_2015_VQC", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1263 ], "matrikelnr": "0726810", "supervisor": [ 166 ], "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 552, "image_height": 470, "name": "Miao_Haichao_2015_VQC-.png", "type": "image/png", "size": 310337, "path": "Publication:Miao_Haichao_2015_VQC", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Miao_Haichao_2015_VQC-poster.pdf", "type": "application/pdf", "size": 9515940, "path": "Publication:Miao_Haichao_2015_VQC", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-poster:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Miao_Haichao_2015_VQC-Thesis.pdf", "type": "application/pdf", "size": 18465647, "path": "Publication:Miao_Haichao_2015_VQC", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/", "__class": "Publication" }, { "id": "raidou_EuroVis15", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Visual analytics for the exploration of tumor tissue characterization", "date": "2015", "abstract": "Tumors are heterogeneous tissues consisting of multiple regions with distinct characteristics. Characterization ofthese intra-tumor regions can improve patient diagnosis and enable a better targeted treatment. Ideally, tissuecharacterization could be performed non-invasively, using medical imaging data, to derive per voxel a number offeatures, indicative of tissue properties. However, the high dimensionality and complexity of this imaging-derivedfeature space is prohibiting for easy exploration and analysis - especially when clinical researchers require toassociate observations from the feature space to other reference data, e.g., features derived from histopathologicaldata. Currently, the exploratory approach used in clinical research consists of juxtaposing these data, visuallycomparing them and mentally reconstructing their relationships. This is a time consuming and tedious process,from which it is difficult to obtain the required insight. We propose a visual tool for: (1) easy exploration and visualanalysis of the feature space of imaging-derived tissue characteristics and (2) knowledge discovery and hypothesisgeneration and confirmation, with respect to reference data used in clinical research. We employ, as central view,a 2D embedding of the imaging-derived features. Multiple linked interactive views provide functionality for theexploration and analysis of the local structure of the feature space, enabling linking to patient anatomy andclinical reference data. We performed an initial evaluation with ten clinical researchers. All participants agreedthat, unlike current practice, the proposed visual tool enables them to identify, explore and analyze heterogeneousintra-tumor regions and particularly, to generate and confirm hypotheses, with respect to clinical reference data.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1446, 1454, 1455, 1456, 679, 459 ], "journal": "In Computer Graphics Forum", "lecturer": [ 1460, 1448, 1449 ], "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_EuroVis15-paper.pdf", "type": "application/pdf", "size": 2846498, "path": "Publication:raidou_EuroVis15", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_EuroVis15/raidou_EuroVis15-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_EuroVis15/raidou_EuroVis15-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_EuroVis15-video.mp4", "type": "video/mp4", "size": 30229493, "path": "Publication:raidou_EuroVis15", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_EuroVis15/raidou_EuroVis15-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_EuroVis15/raidou_EuroVis15-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_EuroVis15/raidou_EuroVis15-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_EuroVis15/", "__class": "Publication" }, { "id": "raidou_vis15", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Orientation-Enhanced Parallel Coordinate Plots", "date": "2015", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1451, 679, 823, 459 ], "journal": "IEEE transactions on visualization and computer graphics", "lecturer": [ 1452, 1453, 1448 ], "number": "1", "pages_from": "589", "pages_to": "598", "volume": "22", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_vis15-paper.pdf", "type": "application/pdf", "size": 3927905, "path": "Publication:raidou_vis15", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_vis15/raidou_vis15-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_vis15/raidou_vis15-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_vis15/", "__class": "Publication" }, { "id": "beham-2014-cupid", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Cupid: Cluster-based Exploration of Geometry Generators with Parallel Coordinates and Radial Trees", "date": "2014-12", "abstract": "Geometry generators are commonly used in video games and evaluation systems for computer vision to create geometric shapes such as terrains, vegetation or airplanes. The parameters of the generator are often sampled automatically which can lead to many similar or unwanted geometric shapes. In this paper, we propose a novel visual exploration approach that combines the abstract parameter space of the geometry generator with the resulting 3D shapes in a composite visualization. Similar geometric shapes are first grouped using hierarchical clustering and then nested within an illustrative parallel coordinates visualization. This helps the user to study the sensitivity of the generator with respect to its parameter space and to identify invalid parameter settings. Starting from a compact overview representation, the user can iteratively drill-down into local shape differences by clicking on the respective clusters. Additionally, a linked radial tree gives an overview of the cluster hierarchy and enables the user to manually split or merge clusters. We evaluate our approach by exploring the parameter space of a cup generator and provide feedback from domain experts.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 307, "image_height": 255, "name": "beham-2014-cupid-teaser.png", "type": "image/png", "size": 235549, "path": "Publication:beham-2014-cupid", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 816, 1193, 166, 983 ], "date_from": "2014-11-09", "date_to": "2014-11-14", "event": "IEEE VIS 2014", "issn": "1077-2626", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 816 ], "location": "Paris, France", "number": "12", "pages_from": "1693", "pages_to": "1702 ", "volume": "20", "research_areas": [ "InfoVis" ], "keywords": [ "3D shape analysis", "radial trees", "hierarchical clustering", "illustrative parallel coordinates", "composite visualization" ], "weblinks": [ { "href": "http://dx.doi.org/10.1109/TVCG.2014.2346626", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": "comparison of selected 3D shapes", "filetitle": "data-comparison", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 349, "image_height": 310, "name": "beham-2014-cupid-data-comparison.png", "type": "image/png", "size": 325461, "path": "Publication:beham-2014-cupid", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-data-comparison.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-data-comparison:thumb{{size}}.png" }, { "description": "draft report (accepted for publication by IEEE)", "filetitle": "draft", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 717, "preview_image_height": 643, "name": "beham-2014-cupid-draft.pdf", "type": "application/pdf", "size": 7298756, "path": "Publication:beham-2014-cupid", "preview_name": "beham-2014-cupid-draft:preview.png", "preview_type": "image/png", "preview_size": 1386025, "url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-draft.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-draft:thumb{{size}}.png" }, { "description": "cluster view, where clusters can be merged/split", "filetitle": "radial-tree", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 345, "image_height": 337, "name": "beham-2014-cupid-radial-tree.png", "type": "image/png", "size": 349754, "path": "Publication:beham-2014-cupid", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-radial-tree.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-radial-tree:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 307, "image_height": 255, "name": "beham-2014-cupid-teaser.png", "type": "image/png", "size": 235549, "path": "Publication:beham-2014-cupid", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-teaser:thumb{{size}}.png" }, { "description": "animated transitions between different levels in the cluster hierarchy", "filetitle": "transitions", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 303, "image_height": 178, "name": "beham-2014-cupid-transitions.png", "type": "image/png", "size": 162296, "path": "Publication:beham-2014-cupid", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-transitions.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-transitions:thumb{{size}}.png" } ], "projects_workgroups": [ "ViMaL" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/", "__class": "Publication" }, { "id": "Groeller_2014_RWA", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Run Watchers: Automatic Simulation-Based Decision Support in Flood Management", "date": "2014-12", "abstract": "In this paper, we introduce a simulation-based approach to design protection plans for flood events. Existing solutions require a lot of computation time for an exhaustive search, or demand for a time-consuming expert supervision and steering. We\npresent a faster alternative based on the automated control of multiple parallel simulation runs. Run Watchers are dedicated system components authorized to monitor simulation runs, terminate them, and start new runs originating from existing ones according to domain-specific rules. This approach allows for a more efficient traversal of the search space and overall performance improvements\ndue to a re-use of simulated states and early termination of failed runs. In the course of search, Run Watchers generate large and complex decision trees. We visualize the entire set of decisions made by Run Watchers using interactive, clustered timelines. In\naddition, we present visualizations to explain the resulting response plans. Run Watchers automatically generate storyboards to convey plan details and to justify the underlying decisions, including those which leave particular buildings unprotected. We evaluate\nour solution with domain experts.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1205, 798, 1058, 877, 1206, 1207, 166 ], "booktitle": "IEEE Transactions on Visualization and Computer Graphics/Proceedings of VAST 2014", "date_from": "2014-11-09", "date_to": "2014-11-14", "event": "Euro Vis 2014", "issn": "1077-2626", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 1205 ], "location": "Paris, France", "number": "12", "pages_from": "1873", "pages_to": "1882", "publisher": "IEEE", "volume": "20", "research_areas": [ "InfoVis" ], "keywords": [ "visual evidence", "Disaster management", "simulation control", "storytelling", "decision making" ], "weblinks": [ { "href": "http://dx.doi.org/10.1109/TVCG.2014.2346930", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Groeller_2014_RWA-Paper.pdf", "type": "application/pdf", "size": 1021356, "path": "Publication:Groeller_2014_RWA", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/Groeller_2014_RWA/Groeller_2014_RWA-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/Groeller_2014_RWA/Groeller_2014_RWA-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/Groeller_2014_RWA/", "__class": "Publication" }, { "id": "Matkovic-2014-ieee", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Visual Analytics for Complex Engineering Systems: Hybrid Visual Steering of Simulation Ensembles", "date": "2014-12", "abstract": "In this paper we propose a novel approach to hybrid visual steering of simulation ensembles. A simulation ensemble is a collection of simulation runs of the same simulation model using different sets of control parameters. Complex engineering systems have very large parameter spaces so a nai?ve sampling can result in prohibitively large simulation ensembles. Interactive steering of simulation ensembles provides the means to select relevant points in a multi-dimensional parameter space (design of experiment). Interactive steering efficiently reduces the number of simulation runs needed by coupling simulation and visualization and allowing a user to request new simulations on the fly. As system complexity grows, a pure interactive solution is not always sufficient. The new approach of hybrid steering combines interactive visual steering with automatic optimization. Hybrid steering allows a domain expert to interactively (in a visualization) select data points in an iterative manner, approximate the values in a continuous region of the simulation space (by regression) and automatically find the “best” points in this continuous region based on the specified constraints and objectives (by optimization). We argue that with the full spectrum of optimization options, the steering process can be improved substantially. We describe an integrated system consisting of a simulation, a visualization, and an optimization component. We also describe typical tasks and propose an interactive analysis workflow for complex engineering systems. We demonstrate our approach on a case study from automotive industry, the optimization of a hydraulic circuit in a high pressure common rail Diesel injection system.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 235, 581, 1204, 579, 959, 176, 190 ], "date_from": "2014-11-09", "date_to": "2014-11-14", "event": "IEEE VAST 2014", "issn": "1077-2626", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 235 ], "location": "Paris, France", "number": "12", "pages_from": "1803", "pages_to": "1812", "volume": "20", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://dx.doi.org/10.1109/TVCG.2014.2346744", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/Matkovic-2014-ieee/", "__class": "Publication" }, { "id": "ymca", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "YMCA - Your Mesh Comparison Application", "date": "2014-11", "abstract": "Polygonal meshes can be created in several different ways. In this paper we focus on the reconstruction of meshes from point clouds, which are sets of points in 3D. Several algorithms that tackle this task already exist, but they have different benefits and drawbacks, which leads to a large number of possible reconstruction results (i.e., meshes). The evaluation of those techniques requires extensive comparisons between different meshes which is up to now done by either placing images of rendered meshes side-by-side, or by encoding differences by heat maps. A major drawback of both approaches is that they do not scale well with the number of meshes. This paper introduces a new comparative visual analysis technique for 3D meshes which enables the simultaneous comparison of several meshes and allows for the interactive exploration of their differences. Our approach gives an overview of the differences of the input meshes in a 2D view. By selecting certain areas of interest, the user can switch to a 3D representation and explore the spatial differences in detail. To inspect local variations, we provide a magic lens tool in 3D. The location and size of the lens provide further information on the variations of the reconstructions in the selected area. With our comparative visualization approach, differences between several mesh reconstruction algorithms can be easily localized and inspected.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 644, "image_height": 661, "name": "ymca-teaser.png", "type": "image/png", "size": 1279857, "path": "Publication:ymca", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 950, 799, 808, 193, 166, 161 ], "booktitle": "IEEE Visual Analytics Science and Technology", "date_from": "2014-11-09", "date_to": "2014-11-14", "lecturer": [ 950 ], "location": "Paris, France", "note": "http://dx.doi.org/10.1109/VAST.2014.7042491", "publisher": "IEEE Computer Society", "series": "VAST ", "research_areas": [ "InfoVis" ], "keywords": [ "mesh comparison", "3D data exploration", "focus+context", "comparative visualization", "Visual analysis" ], "weblinks": [], "files": [ { "description": "paper (authors personal copy, accepted for publication by IEEE)", "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 669, "preview_image_height": 430, "name": "ymca-paper.pdf", "type": "application/pdf", "size": 2169351, "path": "Publication:ymca", "preview_name": "ymca-paper:preview.png", "preview_type": "image/png", "preview_size": 864893, "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 644, "image_height": 661, "name": "ymca-teaser.png", "type": "image/png", "size": 1279857, "path": "Publication:ymca", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-teaser:thumb{{size}}.png" }, { "description": "demonstration of the application - 4:30 min - 20.2 MB", "filetitle": "video-demo", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 64, "preview_image_height": 41, "name": "ymca-video-demo.wmv", "type": "application/octet-stream", "size": 21207342, "path": "Publication:ymca", "preview_name": "ymca-video-demo:preview.png", "preview_type": "image/png", "preview_size": 8002, "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-video-demo.wmv", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-video-demo:thumb{{size}}.png" } ], "projects_workgroups": [ "ViMaL" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/", "__class": "Publication" }, { "id": "waldner-2014-ghi", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Graphical Histories of Information Foraging", "date": "2014-10", "abstract": "During information foraging, knowledge workers iteratively seek, filter, read, and extract information. When using multiple information sources and different applications for information processing, re-examination of activities for validation of previous decisions or re-discovery of previously used information sources is challenging. In this paper, we present a novel representation of cross-application histories to support recall of past operations and re-discovery of information resources. Our graphical history consists of a cross-scale visualization combining an overview node-link diagram of used desktop resources with nested (animated) snapshot sequences, based on a recording of the visual screen output during the users’ desktop work. This representation makes key elements of the users’ tasks visually stand out, while exploiting the power of visual memory to recover subtle details of their activities. In a preliminary study, users found our graphical history helpful to recall details of an information foraging task and commented positively on the ability to expand overview nodes into snapshot and video sequences.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 748, "image_height": 668, "name": "waldner-2014-ghi-.png", "type": "image/png", "size": 118153, "path": "Publication:waldner-2014-ghi", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/waldner-2014-ghi/waldner-2014-ghi-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/waldner-2014-ghi/waldner-2014-ghi-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1110, 161, 171 ], "booktitle": "Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational ", "date_from": "2014-10-26", "date_to": "2014-10-30", "isbn": "978-1-4503-2542-4", "lecturer": [ 1110 ], "location": "Helsinki, Finland", "organization": "NordiCHI’14 - Nordic Conference on Human-Computer Interaction", "pages_from": "295", "pages_to": "304", "publisher": "ACM", "research_areas": [ "InfoVis", "NetVis" ], "keywords": [ "Graph visualization", "Interaction history", "Provenance" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 748, "image_height": 668, "name": "waldner-2014-ghi-.png", "type": "image/png", "size": 118153, "path": "Publication:waldner-2014-ghi", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/waldner-2014-ghi/waldner-2014-ghi-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/waldner-2014-ghi/waldner-2014-ghi-:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "waldner-2014-ghi-paper.pdf", "type": "application/pdf", "size": 3116802, "path": "Publication:waldner-2014-ghi", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/waldner-2014-ghi/waldner-2014-ghi-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/waldner-2014-ghi/waldner-2014-ghi-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/waldner-2014-ghi/", "__class": "Publication" }, { "id": "birsak-2014-agtb", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Automatic Generation of Tourist Brochures", "date": "2014-04", "abstract": "We present a novel framework for the automatic generation of tourist brochures that include routing instructions and additional information presented in the form of so-called detail lenses.\nThe first contribution of this paper is the automatic creation of layouts for the brochures. Our approach is based on the minimization of an energy function that combines multiple goals: positioning of the lenses as close as possible to the corresponding region shown in an overview map, keeping the number of lenses low, and an efficient numbering of the lenses.\nThe second contribution is a route-aware simplification of the graph of streets used for traveling between the points of interest (POIs). This is done by reducing the graph consisting of all shortest paths through the minimization of an energy function. The output is a subset of street segments that enable traveling between all the POIs without considerable detours, while at the same time guaranteeing a clutter-free visualization.\n\nVideo: http://www.youtube.com/watch?v=t3w7uxzSR-Y", "authors_et_al": false, "substitute": null, "main_image": { "description": "image", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1063, "image_height": 553, "name": "birsak-2014-agtb-image.png", "type": "image/png", "size": 497017, "path": "Publication:birsak-2014-agtb", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/birsak-2014-agtb/birsak-2014-agtb-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/birsak-2014-agtb/birsak-2014-agtb-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 836, 844, 194, 193 ], "date_from": "2014-04-07", "date_to": "2014-04-11", "event": "EUROGRAPHICS 2014", "issn": "1467-8659", "journal": "Computer Graphics Forum (Proceedings of EUROGRAPHICS 2014)", "lecturer": [ 836 ], "location": "Strasbourg, France", "number": "2", "pages_from": "449", "pages_to": "458", "volume": "33", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://onlinelibrary.wiley.com/doi/10.1111/cgf.12333/abstract", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": "example brochures", "filetitle": "examples", "main_file": false, "use_in_gallery": false, "access": "public", "name": "birsak-2014-agtb-examples.rar", "type": "application/x-rar", "size": 16542177, "path": "Publication:birsak-2014-agtb", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/birsak-2014-agtb/birsak-2014-agtb-examples.rar", "thumb_image_sizes": [] }, { "description": "image", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1063, 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"https://www.cg.tuwien.ac.at/research/publications/2014/birsak-2014-agtb/", "__class": "Publication" }, { "id": "raidou_vcbm14", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "The iCoCooN:Integration of Cobweb Charts with Parallel Coordinates forVisual Analysis of DCE-MRI Modeling Variations", "date": "2014", "abstract": "Efficacy of radiotherapy treatment depends on the specific characteristics of tumorous tissues. For the determi-nation of these characteristics, clinical practice uses Dynamic Contrast Enhanced (DCE) Magnetic ResonanceImaging (MRI). DCE-MRI data is acquired and modeled using pharmacokinetic modeling, to derive per voxela set of parameters, indicative of tissue properties. Different pharmacokinetic modeling approaches make differ-ent assumptions, resulting in parameters with different distributions. A priori, it is not known whether there aresignificant differences between modeling assumptions and which assumption is best to apply. Therefore, clinicalresearchers need to know at least how different choices in modeling affect the resulting pharmacokinetic parame-ters and also where parameter variations appear. In this paper, we introduce iCoCooN: a visualization applicationfor the exploration and analysis of model-induced variations in pharmacokinetic parameters. We designed a visualrepresentation, the Cocoon, by integrating perpendicularly Parallel Coordinate Plots (PCPs) with Cobweb Charts(CCs). PCPs display the variations in each parameter between modeling choices, while CCs present the relationsin a whole parameter set for each modeling choice. The Cocoon is equipped with interactive features to supportthe exploration of all data aspects in a single combined view. Additionally, interactive brushing allows to link theobservations from the Cocoon to the anatomy. We conducted evaluations with experts and also general users. Theclinical experts judged that the Cocoon in combination with its features facilitates the exploration of all significantinformation and, especially, enables them to find anatomical correspondences. The results of the evaluation withgeneral users indicate that the Cocoon produces more accurate results compared to independent multiples", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_vcbm14-.mp4", "type": "video/mp4", "size": 44770304, "path": "Publication:raidou_vcbm14", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/raidou_vcbm14-.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/raidou_vcbm14-:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/raidou_vcbm14-:video.mp4" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1446, 1459, 679, 459 ], "journal": "Eurographics Workshop on Visual Computing for Biology and Medicine ", "lecturer": [ 171, 231, 951 ], "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_vcbm14-.mp4", "type": "video/mp4", "size": 44770304, "path": "Publication:raidou_vcbm14", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/raidou_vcbm14-.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/raidou_vcbm14-:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/raidou_vcbm14-:video.mp4" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_vcbm14-paper.pdf", "type": "application/pdf", "size": 2017346, "path": "Publication:raidou_vcbm14", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/raidou_vcbm14-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/raidou_vcbm14-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/", "__class": "Publication" }, { "id": "raidou_vis14", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Visual analytics for the exploration of multiparametric cancer imaging", "date": "2014", "abstract": "Tumor tissue characterization can play an important role in thediagnosis and design of effective treatment strategies. In orderto gather and combine the necessary tissue information, multi-modal imaging is used to derive a number of parameters indica-tive of tissue properties. The exploration and analysis of relation-ships between parameters and, especially, of differences among dis-tinct intra-tumor regions is particularly interesting for clinical re-searchers to individualize tumor treatment. However, due to highdata dimensionality and complexity, the current clinical workflowis time demanding and does not provide the necessary intra-tumorinsight. We implemented a new application for the exploration ofthe relationships between parameters and heterogeneity within tu-mors. In our approach, we employ a well-known dimensionalityreduction technique [5] to map the high-dimensional space of tis-sue properties into a 2D information space that can be interactivelyexplored with integrated information visualization techniques. Weconducted several usage scenarios with real-patient data, of whichwe present a case of advanced cervical cancer. First indicationsshow that our application introduces new features and functionali-ties that are not available within the current clinical approach.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1457, 1458, 679, 459 ], "journal": "In Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on Visualization", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_vis14-paper.pdf", "type": "application/pdf", "size": 492922, "path": "Publication:raidou_vis14", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vis14/raidou_vis14-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vis14/raidou_vis14-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vis14/", "__class": "Publication" }, { "id": "kehrer-2013-SBC", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "A Model for Structure-based Comparison of Many Categories in Small-Multiple Displays", "date": "2013-12", "abstract": "Many application domains deal with multi-variate data that consists of both categorical and numerical information. Small-multiple\ndisplays are a powerful concept for comparing such data by juxtaposition. For comparison by overlay or by explicit encoding\nof computed differences, however, a specification of references is necessary. In this paper, we present a formal model for defining\nsemantically meaningful comparisons between many categories in a small-multiple display. Based on pivotized data that are hierarchically\npartitioned by the categories assigned to the x and y axis of the display, we propose two alternatives for structure-based\ncomparison within this hierarchy. With an absolute reference specification, categories are compared to a fixed reference category.\nWith a relative reference specification, in contrast, a semantic ordering of the categories is considered when comparing them either to\nthe previous or subsequent category each. Both reference specifications can be defined at multiple levels of the hierarchy (including\naggregated summaries), enabling a multitude of useful comparisons. We demonstrate the general applicability of our model in several\napplication examples using different visualizations that compare data by overlay or explicit encoding of differences.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 759, "image_height": 903, "name": "kehrer-2013-SBC-image.jpg", "type": "image/jpeg", "size": 208520, "path": "Publication:kehrer-2013-SBC", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 983, 451, 961, 166 ], "date_from": "2013-10-13", "date_to": "2013-10-18", "event": "IEEE Information Visualization Conference", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 983 ], "location": "Atlanta, Georgia, USA", "number": "12", "pages_from": "2287", "pages_to": "2296", "volume": "19", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://dx.doi.org/10.1109/TVCG.2013.122", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "curve", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 718, "image_height": 723, "name": "kehrer-2013-SBC-curve.jpg", "type": "image/jpeg", "size": 151440, "path": "Publication:kehrer-2013-SBC", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-curve.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-curve:thumb{{size}}.png" }, { "description": null, "filetitle": "Draft", 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"https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-image:thumb{{size}}.png" }, { "description": null, "filetitle": "parameters", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 720, "image_height": 603, "name": "kehrer-2013-SBC-parameters.jpg", "type": "image/jpeg", "size": 139132, "path": "Publication:kehrer-2013-SBC", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-parameters.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-parameters:thumb{{size}}.png" }, { "description": null, "filetitle": "scatterplots", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 720, "image_height": 674, "name": "kehrer-2013-SBC-scatterplots.jpg", "type": "image/jpeg", "size": 118024, "path": "Publication:kehrer-2013-SBC", "url": 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"type": "application/pdf", "size": 1863926, "path": "Publication:kehrer-2013-SBC", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-Slides.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-Slides:thumb{{size}}.png" } ], "projects_workgroups": [ "ViMaL" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/", "__class": "Publication" }, { "id": "vaico", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "VAICo: Visual Analysis for Image Comparison", "date": "2013-12", "abstract": "Scientists, engineers, and analysts are confronted with ever larger and more complex sets of data, whose analysis poses special challenges. In many situations it is necessary to compare two or more datasets. Hence there is a need for comparative visualization tools to help analyze differences or similarities among datasets. In this paper an approach for comparative visualization for sets of images is presented. Well-established techniques for comparing images frequently place them side-by-side. A major drawback of such approaches is that they do not scale well. Other image comparison methods encode differences in images by abstract parameters like color. In this case information about the underlying image data gets lost. This paper introduces a new method for visualizing differences and similarities in large sets of images which preserves contextual information, but also allows the detailed analysis of subtle variations. Our approach identifies local changes and applies cluster analysis techniques to embed them in a hierarchy. The results of this process are then presented in an interactive web application which allows users to rapidly explore the space of differences and drill-down on particular features. We demonstrate the flexibility of our approach by applying it to multiple distinct domains.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 400, "image_height": 289, "name": "vaico-teaser.png", "type": "image/png", "size": 206295, "path": "Publication:vaico", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/vaico/vaico-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/vaico/vaico-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 950, 166, 161 ], "date_from": "2013-10-13", "date_to": "2013-10-18", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 950 ], "note": "Demo: http://www.cg.tuwien.ac.at/~jschmidt/vaico/", "number": "12", "pages_from": "2090", "pages_to": "2099", "volume": "19", "research_areas": [ "InfoVis" ], "keywords": [ "focus+context", "image-set comparison", "Comparative visualization" ], "weblinks": [ { "href": "http://dx.doi.org/10.1109/TVCG.2013.213", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": "Fast-Forward Video - 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3:50min - 27MB - DivX5", "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 960, "preview_image_height": 720, "name": "vaico-video.avi", "type": "video/x-msvideo", "size": 27666804, "path": "Publication:vaico", "preview_name": "vaico-video:preview.png", "preview_type": "image/png", "preview_size": 187664, "url": "https://www.cg.tuwien.ac.at/research/publications/2013/vaico/vaico-video.avi", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/vaico/vaico-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2013/vaico/vaico-video:video.mp4" } ], "projects_workgroups": [ "ViMaL" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/vaico/", "__class": "Publication" }, { "id": "sorger-2013-neuromap", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "neuroMAP - Interactive Graph-Visualization of the Fruit Fly's Neural Circuit", "date": "2013-10", "abstract": "Neuroscientists study the function of neural circuits in the brain of the common fruit fly Drosophila melanogaster to discover how complex behavior is generated. To establish models of neural information processing, knowledge about potential connections between individual neurons is required. Connections can occur when the arborizations of two neurons overlap. Judging connectivity by analyzing overlaps using traditional volumetric visualization is difficult since the examined objects occlude each other. A more abstract form of representation is therefore desirable. In collaboration with a group of neuroscientists, we designed and implemented neuroMap, an interactive two-dimensional graph that renders the brain and its interconnections in the form of a circuit-style wiring diagram. neuroMap provides a clearly structured overview of all possible connections between neurons and offers means for interactive exploration of the underlying neuronal database. In this paper, we discuss the design decisions that formed neuroMap and evaluate its application in discussions with the scientists.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 947, "image_height": 703, "name": "sorger-2013-neuromap-teaser.jpg", "type": "image/jpeg", "size": 113971, "path": "Publication:sorger-2013-neuromap", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/sorger-2013-neuromap/sorger-2013-neuromap-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/sorger-2013-neuromap/sorger-2013-neuromap-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1072, 231, 1142, 1278, 820 ], "booktitle": "Biological Data Visualization (BioVis), 2013 IEEE Symposium on ", "lecturer": [ 1072 ], "location": "Atlanta", "pages_from": "73", "pages_to": "80", "publisher": "IEEE", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "sorger-2013-neuromap-paper.pdf", "type": "application/pdf", "size": 1416747, "path": "Publication:sorger-2013-neuromap", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/sorger-2013-neuromap/sorger-2013-neuromap-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/sorger-2013-neuromap/sorger-2013-neuromap-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 947, "image_height": 703, "name": "sorger-2013-neuromap-teaser.jpg", "type": "image/jpeg", "size": 113971, "path": "Publication:sorger-2013-neuromap", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/sorger-2013-neuromap/sorger-2013-neuromap-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/sorger-2013-neuromap/sorger-2013-neuromap-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/sorger-2013-neuromap/", "__class": "Publication" }, { "id": "borgo-2013-gly", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Glyph-based Visualization: Foundations, Design Guidelines, Techniques and Applications", "date": "2013-05", "abstract": "This state of the art report focuses on glyph-based visualization, a common form of visual design where a data set is depicted by a collection of visual objects referred to as glyphs. Its major strength is that patterns of multivariate data involving more than two attribute dimensions can often be more readily perceived in the context of a spatial relationship, whereas many techniques for spatial data such as direct volume rendering find difficult to depict with multivariate or multi-field data, and many techniques for non-spatial data such as parallel coordinates are less able to convey spatial relationships encoded in the data. This report fills several major gaps in the literature, drawing the link between the fundamental concepts in semiotics and the broad spectrum of glyph-based visualization, reviewing existing design guidelines and implementation techniques, and surveying the use of glyph-based visualization in many applications.", "authors_et_al": false, "substitute": null, "main_image": { "description": "teaser image", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 640, "image_height": 533, "name": "borgo-2013-gly-teaser.jpg", "type": "image/jpeg", "size": 127128, "path": "Publication:borgo-2013-gly", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1081, 983, 1085, 1084, 221, 176, 1082, 1083 ], "date_from": "2013-05-06", "date_to": "2013-05-10", "journal": "Eurographics State of the Art Reports", "lecturer": [ 1081, 983, 1085, 1083 ], "location": "Girona, Spain", "note": "http://diglib.eg.org/EG/DL/conf/EG2013/stars/039-063.pdf", "pages_from": "39", "pages_to": "63", "publisher": "Eurographics Association", "series": "EG STARs", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": "State-of-the-Art Report", "filetitle": "report", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 675, "preview_image_height": 476, "name": "borgo-2013-gly-report.pdf", "type": "application/pdf", "size": 3898692, "path": "Publication:borgo-2013-gly", "preview_name": "borgo-2013-gly-report:preview.png", "preview_type": "image/png", "preview_size": 965988, "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-report:thumb{{size}}.png" }, { "description": "presentation by R. Borgo", "filetitle": "slides Borgo", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1161, "preview_image_height": 772, "name": "borgo-2013-gly-slides Borgo.pdf", "type": "application/pdf", "size": 2324846, "path": "Publication:borgo-2013-gly", "preview_name": "borgo-2013-gly-slides Borgo:preview.png", "preview_type": "image/png", "preview_size": 2694057, "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides Borgo.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides Borgo:thumb{{size}}.png" }, { "description": "presentation by D.H.S. Chung", "filetitle": "slides Chung", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1161, "preview_image_height": 865, "name": "borgo-2013-gly-slides Chung.pdf", "type": "application/pdf", "size": 2236108, "path": "Publication:borgo-2013-gly", "preview_name": "borgo-2013-gly-slides Chung:preview.png", "preview_type": "image/png", "preview_size": 3018582, "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides Chung.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides Chung:thumb{{size}}.png" }, { "description": "presentation by J. Kehrer", "filetitle": "slides J. Kehrer", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1161, "preview_image_height": 866, "name": "borgo-2013-gly-slides J. Kehrer.pdf", "type": "application/pdf", "size": 2141660, "path": "Publication:borgo-2013-gly", "preview_name": "borgo-2013-gly-slides J. Kehrer:preview.png", "preview_type": "image/png", "preview_size": 3022083, "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides J. Kehrer.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides J. Kehrer:thumb{{size}}.png" }, { "description": "teaser image", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 640, "image_height": 533, "name": "borgo-2013-gly-teaser.jpg", "type": "image/jpeg", "size": 127128, "path": "Publication:borgo-2013-gly", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "ViMaL" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/", "__class": "Publication" }, { "id": "waldner-2013-facetCloudsGI", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "FacetClouds: Exploring Tag Clouds for Multi-Dimensional Data", "date": "2013-05", "abstract": "Tag clouds are simple yet very widespread representations of how often certain words appear in a collection. In conventional tag clouds, only a single visual text variable is actively controlled: the tags’ font size. Previous work has demonstrated that font size is indeed the most influential visual text variable. However, there are other variables, such as text color, font style and tag orientation, that could be manipulated to encode additional data dimensions.\n\nFacetClouds manipulate intrinsic visual text variables to encode multiple data dimensions within a single tag cloud. We conducted a series of experiments to detect the most appropriate visual text variables for encoding nominal and ordinal values in a cloud with tags of varying font size. Results show that color is the most expressive variable for both data types, and that a combination of tag rotation and background color range leads to the best overall performance when showing multiple data dimensions in a single tag cloud.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 362, "image_height": 360, "name": "waldner-2013-facetCloudsGI-image.png", "type": "image/png", "size": 49904, "path": "Publication:waldner-2013-facetCloudsGI", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-facetCloudsGI/waldner-2013-facetCloudsGI-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-facetCloudsGI/waldner-2013-facetCloudsGI-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1110, 1111, 1112, 1113, 1114, 1115 ], "address": "Regina, Saskatchewan, Canada", "booktitle": "Proceedings of the 2013 Graphics Interface Conference", "date_from": "2013-05-29", "date_to": "2013-05-31", "isbn": "978-1-4822-1680-6 ", "lecturer": [ 1111 ], "location": "Regina, Saskatchewan, Canada", "organization": "ACM Siggraph", "pages_from": "17", "pages_to": "24", "publisher": "ACM Publishing House", "research_areas": [ "InfoVis", "Perception" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 362, "image_height": 360, "name": "waldner-2013-facetCloudsGI-image.png", "type": "image/png", "size": 49904, "path": "Publication:waldner-2013-facetCloudsGI", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-facetCloudsGI/waldner-2013-facetCloudsGI-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-facetCloudsGI/waldner-2013-facetCloudsGI-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "preview_image_width": 636, "preview_image_height": 708, "name": "waldner-2013-facetCloudsGI-paper.pdf", "type": "application/pdf", "size": 2184510, "path": "Publication:waldner-2013-facetCloudsGI", "preview_name": "waldner-2013-facetCloudsGI-paper:preview.png", "preview_type": "image/png", "preview_size": 189512, "url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-facetCloudsGI/waldner-2013-facetCloudsGI-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-facetCloudsGI/waldner-2013-facetCloudsGI-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-facetCloudsGI/", "__class": "Publication" }, { "id": "waldner-2013-ubiWM", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Towards Ubiquitous Information Space Management", "date": "2013-05", "abstract": "Large, high-resolution display spaces are usually created by carefully aligning multiple monitors or projectors to obtain a perfectly flat, rectangular display. In this paper, we suggest the usage of imperfect surfaces as extension of personal workspaces to create ubiquitous, personalized information spaces. We identify five environmental factors ubiquitous information spaces need to consider: 1) user location and display visibility, 2) display gaps and holes, 3) corners and non-planarity of the display surface, 4) physical objects within and around the display surface, and 5) non-rectangular display shapes. Instead of compensating for fragmentations and non-planarity of the information space, we propose a ubiquitous information space manager, adapting interaction and window rendering techniques to the above mentioned factors. We hypothesize that knowledge workers will benefit from such ubiquitous information spaces due to increased exploitation of spatial cognition.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 300, "image_height": 238, "name": "waldner-2013-ubiWM-.png", "type": "image/png", "size": 39630, "path": "Publication:waldner-2013-ubiWM", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-ubiWM/waldner-2013-ubiWM-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-ubiWM/waldner-2013-ubiWM-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1110, 202 ], "booktitle": "POWERWALL: International Workshop on Interactive, Ultra-High-Resolution Displays, part of the SIGCHI Conference on Human Factors in Computing Systems (2013)", "date_from": "2013-04-27", "date_to": "2013-05-02", "isbn": "978-1-4503-1952-2", "lecturer": [ 1110 ], "location": "Paris, France", "pages_from": "1", "pages_to": "6", "publisher": "ACM", "research_areas": [ "InfoVis" ], "keywords": [ "information management", "ubiquitous displays" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 300, "image_height": 238, "name": "waldner-2013-ubiWM-.png", "type": "image/png", "size": 39630, "path": "Publication:waldner-2013-ubiWM", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-ubiWM/waldner-2013-ubiWM-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-ubiWM/waldner-2013-ubiWM-:thumb{{size}}.png" }, { "description": null, "filetitle": "Position Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "waldner-2013-ubiWM-Position Paper.pdf", "type": "application/pdf", "size": 846295, "path": "Publication:waldner-2013-ubiWM", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-ubiWM/waldner-2013-ubiWM-Position Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-ubiWM/waldner-2013-ubiWM-Position Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-ubiWM/", "__class": "Publication" }, { "id": "Kehrer-2013-STAR", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Visualization and Visual Analysis of Multi-faceted Scientific Data: A Survey", "date": "2013-03", "abstract": "Visualization and visual analysis play important roles in exploring, analyzing and presenting scientific data. In many disciplines, data and model scenarios are becoming multi-faceted: data are often spatio-temporal and multi-variate; they stem from different data sources (multi-modal data), from multiple simulation runs (multi-run/ensemble data), or from multi-physics simulations of interacting phenomena (multi-model data resulting from coupled simulation models). Also, data can be of different dimensionality or structured on various types of grids that need to be related or fused in the visualization. This heterogeneity of data characteristics presents new opportunities as well as technical challenges for visualization research. Visualization and interaction techniques are thus often combined with computational analysis. In this survey, we study existing methods for visualization and interactive visual analysis of multi-faceted scientific data. Based on a thorough literature review, a categorization of approaches is proposed. We cover a wide range of fields and discuss to which degree the different challenges are matched with existing solutions for visualization and visual analysis. This leads to conclusions with respect to promising research directions, for instance, to pursue new solutions for multi-run and multi-model data as well as techniques that support a multitude of facets.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Overview of topics discussed in the survey", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 600, "image_height": 218, "name": "Kehrer-2013-STAR-image.png", "type": "image/png", "size": 13343, "path": "Publication:Kehrer-2013-STAR", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 983, 176 ], "issn": "1077-2626", "journal": "IEEE Transactions on Visualization and Computer Graphics", "note": "Spotlight paper of the March issue of TVCG", "number": "3", "pages_from": "495", "pages_to": "513", "volume": "19", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://dx.doi.org/10.1109/TVCG.2012.110", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "Categorization", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1024, "image_height": 553, "name": "Kehrer-2013-STAR-Categorization.png", "type": "image/png", "size": 87430, "path": "Publication:Kehrer-2013-STAR", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-Categorization.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-Categorization:thumb{{size}}.png" }, { "description": null, "filetitle": "Draft", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Kehrer-2013-STAR-Draft.pdf", "type": "application/pdf", "size": 4037427, "path": "Publication:Kehrer-2013-STAR", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-Draft.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-Draft:thumb{{size}}.png" }, { "description": "Overview of topics discussed in the survey", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 600, "image_height": 218, "name": "Kehrer-2013-STAR-image.png", "type": "image/png", "size": 13343, "path": "Publication:Kehrer-2013-STAR", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Presentation-extended", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Kehrer-2013-STAR-Presentation-extended.pdf", "type": "application/pdf", "size": 4087204, "path": "Publication:Kehrer-2013-STAR", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-Presentation-extended.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-Presentation-extended:thumb{{size}}.png" }, { "description": null, "filetitle": "Slides", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Kehrer-2013-STAR-Slides.pdf", "type": "application/pdf", "size": 2544317, "path": "Publication:Kehrer-2013-STAR", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-Slides.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-Slides:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/", "__class": "Publication" }, { "id": "Konyha_2013_IVA", "type_id": "phdthesis", "tu_id": null, "repositum_id": null, "title": "Interactive Visual Analysis in Automotive Engineering Design", "date": "2013-01", "abstract": "Computational simulation has become instrumental in the design process in automotive engineering.\nVirtually all components and subsystems of automobiles can be simulated. The simulation can be repeated many times with varied parameter settings, thereby simulating many possible design choices. Each simulation run can produce a complex, multivariate, and usually timedependent result data set. The engineers’ goal is to generate useful knowledge from those data.\nThey need to understand the system’s behavior, find correlations in the results, conclude how results depend on the parameters, find optimal parameter combinations, and exclude the ones\nthat lead to undesired results.\n\nComputational analysis methods are widely used and necessary to analyze simulation data sets, but they are not always sufficient. They typically require that problems and interesting\ndata features can be precisely defined from the beginning. The results of automated analysis of complex problems may be difficult to interpret. Exploring trends, patterns, relations, and dependencies in time-dependent data through statistical aggregates is not always intuitive.\n\nIn this thesis, we propose techniques and methods for the interactive visual analysis (IVA) of simulation data sets. Compared to computational methods, IVA offers new and different analysis\nopportunities. Visual analysis utilizes human cognition and creativity, and can also incorporate the experts’ domain knowledge. Therefore, their insight into the data can be amplified, and also\nless precisely defined problems can be solved.\n\nWe introduce a data model that effectively represents the multi-run, time-dependent simulation\nresults as families of function graphs. This concept is central to the thesis, and many of the innovations in this thesis are closely related to it.We present visualization techniques for families of function graphs. Those visualizations, as well as well-known information visualization plots,\nare integrated into a coordinated multiple views framework. All views provide focus+context visualization.\nCompositions of brushes spanning several views can be defined iteratively to select\ninteresting features and promote information drill-down. Valuable insight into the spatial aspect\nof the data can be gained from (generally domain-specific) spatio-temporal visualizations. In\nthis thesis, we propose interactive, glyph-based 3D visualization techniques for the analysis of rigid and elastic multibody system simulations.\n\nWe integrate the on-demand computation of derived data attributes of families of function graphs into the analysis workflow. This facilitates the selection of deeply hidden data features\nthat cannot be specified by combinations of simple brushes on the original data attributes. The\ncombination of these building blocks supports interactive knowledge discovery. The analyst can\nbuild a mental model of the system; explore also unexpected features and relations; and generate, verify or reject hypotheses with visual tools; thereby gaining more insight into the data.\nComplex tasks, such as parameter sensitivity analysis and optimization can be solved. Although\nthe primary motivation for our work was the analysis of simulation data sets in automotive engineering,\nwe learned that this data model and the analysis procedures we identified are also applicable to several other problem domains. We discuss common tasks in the analysis of data\ncontaining families of function graphs.\n\nTwo case studies demonstrate that the proposed approach is indeed applicable to the analysis of simulation data sets in automotive engineering. Some of the contributions of this thesis have\nbeen integrated into a commercially distributed software suite for engineers. This suggests that\ntheir impact can extend beyond the visualization research community.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 1800, "image_height": 1750, "name": "Konyha_2013_IVA-Image.jpg", "type": "image/jpeg", "size": 490763, "path": "Publication:Konyha_2013_IVA", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Konyha_2013_IVA/Konyha_2013_IVA-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Konyha_2013_IVA/Konyha_2013_IVA-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 756 ], "co_supervisor": [ 176 ], "date_end": "2013", "date_start": "2006", "reviewer_1": [ 166 ], "reviewer_2": [ 176 ], "rigorosum": "2013-02-01", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 1800, "image_height": 1750, "name": "Konyha_2013_IVA-Image.jpg", "type": "image/jpeg", "size": 490763, "path": "Publication:Konyha_2013_IVA", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Konyha_2013_IVA/Konyha_2013_IVA-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Konyha_2013_IVA/Konyha_2013_IVA-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Konyha_2013_IVA-Thesis.pdf", "type": "application/pdf", "size": 10012799, "path": "Publication:Konyha_2013_IVA", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Konyha_2013_IVA/Konyha_2013_IVA-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Konyha_2013_IVA/Konyha_2013_IVA-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Konyha_2013_IVA/", "__class": "Publication" }, { "id": "Sorger_2013_nMI", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "neuroMap - Interactive Graph-Visualization of the Fruit Fly’s Neural Circuit", "date": "2013-01", "abstract": "Neuroscientists study the function of neural circuits in the brain of the common fruit\nfly Drosophila Melanogaster to discover how complex behavior is generated. Through\na combination of molecular-genetic techniques and confocal microscopy the scientists\nare able to highlight single neurons and produce three-dimensional images of the fly’s\nbrain. Neurons are segmented, annotated, and compiled into a digital atlas. Brain atlases\noffer tools for exploring and analyzing their underlying data. To establish models\nof neural information processing, knowledge about possible connections between individual\nneurons is necessary. Connections can occur when arborizations (the terminal\nbranchings of nerve fibers) of two neurons are overlapping. However, analyzing overlapping\nobjects using traditional volumetric visualization is difficult since the examined\nobjects occlude each other. A more abstract form of representation is therefore required.\nThe work in this thesis was motivated by a manually constructed two-dimensional\ncircuit diagram of potential neuronal connections that represents a novel way of visualizing\nneural connectivity data. Through abstracting the complex volumetric data, the\ndiagram offers an intuitive and clear overview of potential connectivity.\nIn collaboration with a group of neuroscientists neuroMap was designed and implemented\nin an attempt to deliver the visual features and encoded information of this\ncircuit diagram in an automatically generated interactive graph, with the goal of facilitating\nhypothesis formation and exploration of neural connectivity.\nIn this thesis the visual and interaction design decisions that went into neuroMap are\npresented, as well as the result of evaluative discussions that shows that the integration\nof this novel type of visualization into the existing datamining infrastructure of our\nclients is indeed beneficial to their research.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 947, "image_height": 703, "name": "Sorger_2013_nMI-Image.jpg", "type": "image/jpeg", "size": 107141, "path": "Publication:Sorger_2013_nMI", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Sorger_2013_nMI/Sorger_2013_nMI-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Sorger_2013_nMI/Sorger_2013_nMI-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1072 ], "matrikelnr": "0225843", "supervisor": [ 166, 231 ], "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 947, "image_height": 703, "name": "Sorger_2013_nMI-Image.jpg", "type": "image/jpeg", "size": 107141, "path": "Publication:Sorger_2013_nMI", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Sorger_2013_nMI/Sorger_2013_nMI-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Sorger_2013_nMI/Sorger_2013_nMI-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Sorger_2013_nMI-Poster.pdf", "type": "application/pdf", "size": 2704019, "path": "Publication:Sorger_2013_nMI", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Sorger_2013_nMI/Sorger_2013_nMI-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Sorger_2013_nMI/Sorger_2013_nMI-Poster:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Sorger_2013_nMI-Thesis.pdf", "type": "application/pdf", "size": 15581070, "path": "Publication:Sorger_2013_nMI", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Sorger_2013_nMI/Sorger_2013_nMI-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Sorger_2013_nMI/Sorger_2013_nMI-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Sorger_2013_nMI/", "__class": "Publication" }, { "id": "Ribicic_2012_VAS", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Visual analysis and steering of flooding simulations", "date": "2012", "abstract": "We present a visualization tool for the real-time analysis of interactively steered ensemble-simulation runs, and apply it to flooding simulations. Simulations are performed on-the-fly, generating large quantities of data. The user wants to make sense of the data as it is created. The tool facilitates understanding: of what happens in all scenarios, where important events occur and how simulation runs are related. We combine different approaches to achieve this goal. To maintain an overview, data is aggregated and embedded into the simulation rendering, showing trends, outliers, and robustness. For a detailed view, we use information-visualization views and interactive visual analysis techniques. A selection mechanism connects the two approaches. Points of interest are selected by clicking on aggregates, supplying data for visual analysis. This allows the user to maintain an overview of the ensemble and perform analysis even as new data is supplied through simulation steering. Unexpected or unwanted developments are detected easily, and the user can focus the exploration on them. The solution was evaluated with two case studies focusing on placing and testing flood defense measures. Both were evaluated by a consortium of flood simulation and defense experts, who found the system to be both intuitive and relevant.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 889, 798, 672, 1330, 166 ], "journal": "IEEE Transaction on Visualization and Computer Graphics", "number": "99", "volume": "PP", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6280550", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2012/Ribicic_2012_VAS/", "__class": "Publication" }, { "id": "Groeller_2011_NR", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Nodes on Ropes: A Comprehensive Data and Control Flow for Steering Ensemble Simulations", "date": "2011-12", "abstract": "Flood disasters are the most common natural risk and tremendous efforts are spent to improve their simulation and\nmanagement. However, simulation-based investigation of actions that can be taken in case of flood emergencies is rarely done.\nThis is in part due to the lack of a comprehensive framework which integrates and facilitates these efforts. In this paper, we tackle\nseveral problems which are related to steering a flood simulation. One issue is related to uncertainty. We need to account for\nuncertain knowledge about the environment, such as levee-breach locations. Furthermore, the steering process has to reveal how\nthese uncertainties in the boundary conditions affect the confidence in the simulation outcome. Another important problem is that the\nsimulation setup is often hidden in a black-box. We expose system internals and show that simulation steering can be comprehensible\nat the same time. This is important because the domain expert needs to be able to modify the simulation setup in order to include local\nknowledge and experience. In the proposed solution, users steer parameter studies through the World Lines interface to account for\ninput uncertainties. The transport of steering information to the underlying data-flow components is handled by a novel meta-flow. The\nmeta-flow is an extension to a standard data-flow network, comprising additional nodes and ropes to abstract parameter control. The\nmeta-flow has a visual representation to inform the user about which control operations happen. Finally, we present the idea to use\nthe data-flow diagram itself for visualizing steering information and simulation results. We discuss a case-study in collaboration with a\ndomain expert who proposes different actions to protect a virtual city from imminent flooding. The key to choosing the best response\nstrategy is the ability to compare different regions of the parameter space while retaining an understanding of what is happening\ninside the data-flow system.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2126, "image_height": 1673, "name": "Groeller_2011_NR-Image.png", "type": "image/png", "size": 514334, "path": "Publication:Groeller_2011_NR", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_NR/Groeller_2011_NR-Image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_NR/Groeller_2011_NR-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 798, 889, 672, 978, 829, 1330, 166 ], "issn": "1077-2626", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 798 ], "number": "12", "pages_from": "1872", "pages_to": "1881", "volume": "17", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6064950", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2126, "image_height": 1673, "name": "Groeller_2011_NR-Image.png", "type": "image/png", "size": 514334, "path": "Publication:Groeller_2011_NR", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_NR/Groeller_2011_NR-Image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_NR/Groeller_2011_NR-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Groeller_2011_NR-Paper.pdf", "type": "application/pdf", "size": 1829746, "path": "Publication:Groeller_2011_NR", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_NR/Groeller_2011_NR-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_NR/Groeller_2011_NR-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "ViMaL" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_NR/", "__class": "Publication" }, { "id": "Groeller_2011_CW", "type_id": "WorkshopTalk", "tu_id": null, "repositum_id": null, "title": "Contingency Wheel: Visual Analysis of Large Contingency Tables", "date": "2011-05-31", "abstract": "We present the Contingency Wheel, a visual method for finding and analyzing associations in a large nm contingency\ntable with m < 100 and n being two to three orders of magnitude larger than m. The method is demonstrated on a large\ntable from the Book-Crossing dataset, which counts the number of ratings each book received from each country. It\nenables finding books that received a disproportionately high number of ratings from a specific country. It further allows\nto visually analyze what these books have in common, and with which countries they are also highly associated. Pairs of\nsimilar countries can further be identified (in the sense that many books are associated with both countries). Compared\nwith existing visual methods, our approach enables analyzing and gaining insight into larger tables.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 734, 166, 966, 665 ], "event": "International Workshop on Visual Analytics (2011)", "lecturer": [ 734 ], "location": "Bergen, Norway", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Groeller_2011_CW-Paper.pdf", "type": "application/pdf", "size": 693452, "path": "Publication:Groeller_2011_CW", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_CW/Groeller_2011_CW-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_CW/Groeller_2011_CW-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_CW/", "__class": "Publication" }, { "id": "sikachev_peter-2011-protovis", "type_id": "WorkshopTalk", "tu_id": null, "repositum_id": null, "title": "ProtoVis", "date": "2011-05-11", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 332, "image_height": 332, "name": "sikachev_peter-2011-protovis-image.png", "type": "image/png", "size": 138847, "path": "Publication:sikachev_peter-2011-protovis", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/sikachev_peter-2011-protovis/sikachev_peter-2011-protovis-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/sikachev_peter-2011-protovis/sikachev_peter-2011-protovis-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 864 ], "event": "Software Seminar", "lecturer": [ 864 ], "location": "Vienna", "research_areas": [ "InfoVis" ], "keywords": [ "Qt", "integration", "ProtoVis", "information visualization", "software engineering", "JavaScript", "C++", "VolumeShop" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 332, "image_height": 332, "name": "sikachev_peter-2011-protovis-image.png", "type": "image/png", "size": 138847, "path": "Publication:sikachev_peter-2011-protovis", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/sikachev_peter-2011-protovis/sikachev_peter-2011-protovis-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/sikachev_peter-2011-protovis/sikachev_peter-2011-protovis-image:thumb{{size}}.png" }, { 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"https://www.cg.tuwien.ac.at/research/publications/2011/sikachev_peter-2011-protovis/sikachev_peter-2011-protovis-video1.wmv", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/sikachev_peter-2011-protovis/sikachev_peter-2011-protovis-video1:thumb{{size}}.png" }, { "description": "Retrieving interaction information from ProtoVis", "filetitle": "video2", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 640, "preview_image_height": 360, "name": "sikachev_peter-2011-protovis-video2.wmv", "type": "text/plain", "size": 261198, "path": "Publication:sikachev_peter-2011-protovis", "preview_name": "sikachev_peter-2011-protovis-video2:preview.png", "preview_type": "image/jpeg", "preview_size": 24438, "url": "https://www.cg.tuwien.ac.at/research/publications/2011/sikachev_peter-2011-protovis/sikachev_peter-2011-protovis-video2.wmv", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/sikachev_peter-2011-protovis/sikachev_peter-2011-protovis-video2:thumb{{size}}.png" } ], "projects_workgroups": [ "ViMaL" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2011/sikachev_peter-2011-protovis/", "__class": "Publication" }, { "id": "PH-2011-LDS", "type_id": "phdthesis", "tu_id": null, "repositum_id": null, "title": "Large Data Scalability in Interactive Visual Analysis", "date": "2011-05", "abstract": "In many areas of science and industry, the amount of data is growing fast and often already exceeds the ability to evaluate it. On the other hand, the unprecedented amount of available data bears an enormous potential for supporting decision-making. Turning data into comprehensible knowledge is thus a key challenge of the 21st century.\nThe power of the human visual system makes visualization an appropriate method to\ncomprehend large data. In particular interactive visualization enables a discourse between\nthe human brain and the data that can transform a cognitive problem to a perceptual one.\nHowever, the visual analysis of large and complex datasets involves both visual and computational\nchallenges. Visual limits involve perceptual and cognitive limitations of the user and\nrestrictions of the display devices while computational limits are related to the computational\ncomplexity of the involved algorithms.\nThe goal of this thesis is to advance the state of the art in visual analysis with respect to the\nscalability to large datasets. Due to the multifaceted nature of scalability, the contributions\nspan a broad range to enhance computational scalability, to improve the visual scalability of\nselected visualization approaches, and to support an analysis of high-dimensional data.\nConcerning computational scalability, this thesis describes a generic architecture to facilitate\nthe development of highly interactive visual analysis tools using multi-threading. The\narchitecture builds on the separation of the main application thread and dedicated visualization\nthreads, which can be cancelled early due to user interaction. A quantitative evaluation\nshows fast visual feedback during continuous interaction even for millions of entries.\nTwo variants of scatterplots address the visual scalability of different types of data and\ntasks. For continuous data, a combination of 2D and 3D scatterplots intends to combine\nthe advantages of 2D interaction and 3D visualization. Several extensions improve the depth\nperception in 3D and address the problem of unrecognizable point densities in both 2D and\n3D. For partly categorical data, the thesis contributes Hierarchical Difference Scatterplots\nto relate multiple hierarchy levels and to explicitly visualize differences between them in the\ncontext of the absolute position of pivoted values.\nWhile comparisons in Hierarchical Difference Scatterplots are only qualitative, this thesis\nalso contributes an approach for quantifying subsets of the data by means of statistical moments\nfor a potentially large number of dimensions. This approach has proven useful as an\ninitial overview as well as for a quantitative comparison of local features like clusters.\nAs an important application of visual analysis, the validation of regression models also\ninvolves the scalability to multi-dimensional data. This thesis describes a design study of an\napproach called HyperMoVal for this task. The key idea is to visually relate n-dimensional\nscalar functions to known validation data within a combined visualization. The integration\nwith other multivariate views is a step towards a user-centric workflow for model building.\nBeing the result of collaboration with experts in engine design, HyperMoVal demonstrates\nhow visual analysis is suitable to significantly improve real-world tasks. Positive user feedback suggests a high impact of the contributions of this thesis also outside the visualization\nresearch community. Moreover, most contributions of this thesis have been combined in a\ncommercially distributed software framework for engineering applications that will hopefully\nraise the awareness and promote the use of visual analysis in multiple application domains.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1122, "image_height": 1590, "name": "PH-2011-LDS-Teaser.jpg", "type": "image/jpeg", "size": 278320, "path": "Publication:PH-2011-LDS", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/PH-2011-LDS/PH-2011-LDS-Teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/PH-2011-LDS/PH-2011-LDS-Teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 451 ], "date_end": "2011-05", "date_start": "2008-10", "reviewer_1": [ 166 ], "reviewer_2": [ 1324 ], "rigorosum": "2011-09-09", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "high dimensionality", "Visualization", "Scalability", "Interaction", "Data analysis", "multi-threading", "scatter plots" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1122, "image_height": 1590, "name": "PH-2011-LDS-Teaser.jpg", "type": "image/jpeg", "size": 278320, "path": "Publication:PH-2011-LDS", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/PH-2011-LDS/PH-2011-LDS-Teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/PH-2011-LDS/PH-2011-LDS-Teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "PH-2011-LDS-Thesis.pdf", "type": "application/pdf", "size": 17979794, "path": "Publication:PH-2011-LDS", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/PH-2011-LDS/PH-2011-LDS-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/PH-2011-LDS/PH-2011-LDS-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2011/PH-2011-LDS/", "__class": "Publication" }, { "id": "waser_2011_VSD", "type_id": "phdthesis", "tu_id": null, "repositum_id": null, "title": "Visual Steering to Support Decision Making in Visdom", "date": "2011-05", "abstract": "Computer simulation has become an ubiquitous tool to investigate\nthe nature of systems. When steering a simulation, users modify parameters\nto study their impact on the simulation outcome. The ability to test\nalternative options provides the basis for interactive decision making. Increasingly\ncomplex simulations are characterized by an intricate interplay\nof many heterogeneous input and output parameters. A steering concept\nthat combines simulation and visualization within a single, comprehensive\nsystem is largely missing. This thesis targets the basic components\nof a novel integrated steering system called Visdom to support the user\nin the decision making process. The proposed techniques enable users\nto examine alternative scenarios without the need for special simulation\nexpertise. To accomplish this, we propose World Lines as a management\nstrategy for multiple, related simulation runs. In a dedicated view, users\ncreate and navigate through many simulation runs. New decisions are\nincluded through the concept of branching. To account for uncertain\nknowledge about the input parameters, we provide the ability to cover\nfull parameter distributions. Via multiple cursors, users navigate a system\nof multiple linked views through time and alternative scenarios. In this\nway, the system supports comparative visual analysis of many simulation\nruns. Since the steering process generates a huge amount of information,\nwe employ the machine to support the user in the search for explanations\ninside the computed data. Visdom is built on top of a data-flow network\nto provide a high level of modularity. A decoupled meta-flow is in charge\nof transmitting parameter changes from World Lines to the affected dataflow\nnodes. To direct the user attention to the most relevant parts, we\nprovide dynamic visualization inside the flow diagram. The usefulness of\nthe presented approach is substantiated through case studies in the field\nof flood management. The Visdom application enables the design of a\nbreach closure by dropping sandbags in a virtual environment.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1000, "image_height": 985, "name": "waser_2011_VSD-Image.jpg", "type": "image/jpeg", "size": 134428, "path": "Publication:waser_2011_VSD", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/waser_2011_VSD/waser_2011_VSD-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/waser_2011_VSD/waser_2011_VSD-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 798 ], "date_end": "2011-06", "date_start": "2008-10", "reviewer_1": [ 166 ], "reviewer_2": [ 1330 ], "rigorosum": "2011-06-15", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "CFD", "Data-Flow", "Simulation Steering", "Comparative Visual Analysis", "Multiple Simulation Runs", "Problem Solving Environment", "Hypothesis Generation", "Uncertainty", "Flood Management" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1000, "image_height": 985, "name": "waser_2011_VSD-Image.jpg", "type": "image/jpeg", "size": 134428, "path": "Publication:waser_2011_VSD", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/waser_2011_VSD/waser_2011_VSD-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/waser_2011_VSD/waser_2011_VSD-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "waser_2011_VSD-Thesis.pdf", "type": "application/pdf", "size": 41981581, "path": "Publication:waser_2011_VSD", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/waser_2011_VSD/waser_2011_VSD-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/waser_2011_VSD/waser_2011_VSD-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2011/waser_2011_VSD/", "__class": "Publication" }, { "id": "karnik-09-shapegrammar", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "A Shape Grammar for Developing Glyph-based Visualizations", "date": "2009", "abstract": "In this paper we address the question of how to quickly model glyph-based GIS visualizations. Our solution is based on using shape grammars to set up the different aspects of a visualization, including the geometric content of the visualization, methods for resolving layout conflicts and interaction methods. Our approach significantly\nincreases modeling efficiency over similarly flexible systems currently in use.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Example for a city modelled with our shape grammar.", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1022, "image_height": 746, "name": "karnik-09-shapegrammar-image.jpg", "type": "image/jpeg", "size": 454584, "path": "Publication:karnik-09-shapegrammar", "url": "https://www.cg.tuwien.ac.at/research/publications/2009/karnik-09-shapegrammar/karnik-09-shapegrammar-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2009/karnik-09-shapegrammar/karnik-09-shapegrammar-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 813, 356, 809, 811, 814, 194 ], "issn": "0167-7055", "journal": "Computer Graphics Forum", "number": "8", "pages_from": "2176", "pages_to": "2188", "volume": "28", "research_areas": [ "InfoVis", "Modeling" ], "keywords": [], "weblinks": [], "files": [ { "description": "Example for a city modelled with our shape grammar.", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1022, "image_height": 746, "name": "karnik-09-shapegrammar-image.jpg", "type": "image/jpeg", "size": 454584, "path": "Publication:karnik-09-shapegrammar", "url": "https://www.cg.tuwien.ac.at/research/publications/2009/karnik-09-shapegrammar/karnik-09-shapegrammar-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2009/karnik-09-shapegrammar/karnik-09-shapegrammar-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "karnik-09-shapegrammar-paper.pdf", "type": "application/pdf", "size": 9826625, "path": "Publication:karnik-09-shapegrammar", "url": "https://www.cg.tuwien.ac.at/research/publications/2009/karnik-09-shapegrammar/karnik-09-shapegrammar-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2009/karnik-09-shapegrammar/karnik-09-shapegrammar-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2009/karnik-09-shapegrammar/", "__class": "Publication" }, { "id": "Thomas-2018", "type_id": "runmasterthesis", "tu_id": null, "repositum_id": null, "title": "PolicyMap: A Dynamic Map for Line-Up Policy in Amusement Parks", "date": null, "abstract": "The more time is spent in queues lining up for attractions in amusement parks, the less\nfunny the experience and the whole day in the park becomes. This project aims to\ninvestigate different factors that influence the waiting time and develop a tool that helps\nusers to efficiently plan their stay in an amusement park. The tool will consist of three\ndifferent parts. A dynamic map shall help users to get an overview of the current waiting\ntimes and the location of respective attractions in the park. A routing algorithm shall be\ndeveloped to suggest an appropriate route through the park while considering the local\noptimum for each visitor and the global optimum for the whole park. Finally, a 3D navigation\nshall be implemented to help users to find their way to the desired attraction easier than by\nusing conventional paper maps.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1367 ], "date_start": "2018-05-24", "matrikelnr": "01327052", "supervisor": [ 1464 ], "research_areas": [ "IllVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/ongoing/Thomas-2018/", "__class": "Publication" } ]