@article{furmanova_2020, title = "VAPOR: Visual Analytics for the Exploration of Pelvic Organ Variability in Radiotherapy", author = "Katar\'{i}na Furmanov\'{a} and Nicolas Grossmann and Ludvig Paul Muren and Oscar Casares-Magaz and Vitali Moiseenko and John P. Einck and Eduard Gr\"{o}ller and Renata Raidou", year = "2020", 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.", month = oct, doi = "https://doi.org/10.1016/j.cag.2020.07.001", journal = "Computer & Graphics", note = "Special Section on VCBM 2019", volume = "91", pages = "25--38", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/furmanova_2020/", } @inproceedings{raidou_pingu2020, title = "PINGU Principles of Interactive Navigation for Geospatial Understanding", author = "Zoltan Oremus and Kahin Akram Hassan and Jiri Chmelik and Michaela Knazkova and Jan Byska and Renata Raidou and Barbora Kozlikova", year = "2020", 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.", month = jun, event = "IEEE Pacific Vis 2020", doi = "10.1109/PacificVis48177.2020.7567", booktitle = "2020 IEEE Pacific Visualization Symposium (PacificVis)", pages = "216--225", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/", } @article{wu-2020-eurovis-star, title = "A Survey on Transit Map Layout – from Design, Machine, and Human Perspectives", author = "Hsiang-Yun Wu and Benjamin Niedermann and Shigeo Takahashi and Maxwell J. Roberts and Martin N\"{o}llenburg", year = "2020", 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.", month = may, journal = "Computer Graphics Forum", volume = "39", number = "3", issn = "1467-8659", doi = "10.1111/cgf.14030", pages = "28", pages = "619--646", keywords = "Computer Graphics and Computer-Aided Design", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/", } @inproceedings{raidou_visgap2020, title = "Lessons Learnt from Developing Visual Analytics Applications for Adaptive Prostate Cancer Radiotherapy", author = "Renata Raidou and Katar\'{i}na Furmanov\'{a} and Nicolas Grossmann and Oscar Casares-Magaz and Vitali Moiseenko and John P. Einck and Eduard Gr\"{o}ller and Ludvig Paul Muren", year = "2020", abstract = "In radiotherapy (RT), changes in patient anatomy throughout the treatment period might lead to deviations between planned and delivered dose, resulting in inadequate tumor coverage and/or overradiation of healthy tissues. Adapting the treatment to account for anatomical changes is anticipated to enable higher precision and less toxicity to healthy tissues. Corresponding tools for the in-depth exploration and analysis of available clinical cohort data were not available before our work. In this paper, we discuss our on-going process of introducing visual analytics to the domain of adaptive RT for prostate cancer. This has been done through the design of three visual analytics applications, built for clinical researchers working on the deployment of robust RT treatment strategies. We focus on describing our iterative design process, and we discuss the lessons learnt from our fruitful collaboration with clinical domain experts and industry, interested in integrating our prototypes into their workflow.", month = may, event = "EGEV2020 - VisGap Workshop", booktitle = "The Gap between Visualization Research and Visualization Software (VisGap) (2020)", pages = "1--8", keywords = "Visual Analytics, Life and Medical Sciences", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_visgap2020/", } @article{waldner-2020-tbg, title = "Interactive exploration of large time-dependent bipartite graphs", author = "Manuela Waldner and Daniel Steinb\"{o}ck and Eduard Gr\"{o}ller", year = "2020", 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.", month = apr, doi = "https://doi.org/10.1016/j.cola.2020.100959", journal = "Journal of Computer Languages", volume = "57", keywords = "Information visualization, Bipartite graphs, Clustering, Time series data, Insight-based evaluation", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/", } @phdthesis{Cornel_2020, title = "Interactive Visualization of Simulation Data for GeospatialDecision Support", author = "Daniel Cornel", year = "2020", 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. ", month = jan, pages = "167", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Research Unit of Computer Graphics, Institute of Visual Computing and Human-Centered Technology, Faculty of Informatics, TU Wien ", keywords = "Interactive visualization, uncertainty, flood management, decision support, flood simulation", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/", } @inproceedings{sorger-2019-odn, title = "Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation", author = "Johannes Sorger and Manuela Waldner and Wolfgang Knecht and Alessio Arleo", year = "2019", 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.", month = dec, organization = "IEEE", location = "San Diego, California, USA", event = "AIVR 2019", booktitle = "2nd International Conference on Artificial Intelligence & Virtual Reality", pages = "144--151", keywords = "Immersive Network Analytics, Web-Based Visualization, Dynamic Graph Visualization", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/sorger-2019-odn/", } @inproceedings{sietzen-ifv-2019, title = "Interactive Feature Visualization in the Browser", author = "Stefan Sietzen and Manuela Waldner", year = "2019", 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.", month = oct, booktitle = "Proceedings of the Workshop on Visualization for AI explainability (VISxAI)", editor = "El-Assady, Mennatallah and Chau, Duen Horng (Polo) and Hohman, Fred and Perer, Adam and Strobelt, Hendrik and Vi\'{e}gas, Fernanda", location = "Vancouver", event = "Workshop on Visualization for AI explainability (VISxAI) at IEEE VIS 2019", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/", } @article{waldner-2019-rld, title = "A Comparison of Radial and Linear Charts for Visualizing Daily Patterns", author = "Manuela Waldner and Alexandra Diehl and Denis Gracanin and Rainer Splechtna and Claudio Delrieux and Kresimir Matkovic", year = "2019", 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 drawbacks 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.", month = oct, journal = "IEEE Transactions on Visualization and Computer Graphics", volume = "26", doi = "10.1109/TVCG.2019.2934784", pages = "1033--1042", keywords = "radial charts, time series data, daily patterns, crowd-sourced experiment", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/", } @inproceedings{Arleo-2019-vis, title = "Sabrina: Modeling and Visualization of Economy Data with Incremental Domain Knowledge", author = "Alessio Arleo and Christos Tsigkanos and Chao Jia and Roger Leite and Ilir Murturi and Manfred Klaffenb\"{o}ck and Schahram Dustdar and Silvia Miksch and Michael Wimmer and Johannes Sorger", year = "2019", 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.", month = oct, location = "Vancouver, British Columbia, Canada", event = " IEEE Visualization Conference (VIS)", booktitle = "IEEE VIS 2019", keywords = "Visualization, Visual Analytics", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/Arleo-2019-vis/", } @inproceedings{raidou_2019_pelvisrunner, title = "Pelvis Runner: Visualizing Pelvic Organ Variability in a Cohort of Radiotherapy Patients", author = "Nicolas Grossmann and Oscar Casares-Magaz and Ludvig Paul Muren and Vitali Moiseenko and John P. Einck and Eduard Gr\"{o}ller and Renata Raidou", year = "2019", 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.", month = sep, event = "Eurographics Workshop on Visual Computing for Biology and Medicine (2019)", doi = "10.2312/vcbm.20191233", booktitle = "Eurographics Workshop on Visual Computing for Biology and Medicine (2019)", pages = "69--78", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_pelvisrunner/", } @inproceedings{raidou_2019_preha, title = "preha: Establishing Precision Rehabilitation with Visual Analytics", author = "Georg Bernold and Kresimir Matkovic and Eduard Gr\"{o}ller and Renata Raidou", year = "2019", 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.", month = sep, event = "Eurographics Workshop on Visual Computing for Biology and Medicine (2019)", doi = "10.2312/vcbm.20191234", booktitle = "Eurographics Workshop on Visual Computing for Biology and Medicine (2019)", pages = "79--89", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/", } @incollection{raidou_2019_springer, title = "Visual Analytics for the Representation, Exploration and Analysis of High-Dimensional, Multi-Faceted Medical Data", author = "Renata Raidou", year = "2019", abstract = "Medicine is among research fields with a significant impact on humans and their health. Already for decades, medicine has established a tight coupling with the visualization domain, proving the importance of developing visualization techniques, designed exclusively for this research discipline. However, medical data is steadily increasing in complexity with the appearance of heterogeneous, multi-modal, multiparametric, cohort or population, as well as uncertain data. To deal with this kind of complex data, the field of Visual Analytics has emerged. In this chapter, we discuss the many dimensions and facets of medical data. Based on this classification, we provide a general overview of state-of-the-art visualization systems and solutions dealing with highdimensional, multi-faceted data. Our particular focus will be on multimodal, multi-parametric data, on data from cohort or population studies and on uncertain data, especially with respect to Visual Analytics applications for the representation, exploration, and analysis of highdimensional, multi-faceted medical data.", month = jul, 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", publisher = "Springer", volume = "2", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_springer/", } @article{mizuno-2019-eurovis, title = "Optimizing Stepwise Animation in Dynamic Set Diagrams", author = "Kazuyo Mizuno and Hsiang-Yun Wu and Shigeo Takahashi and Takeo Igarashi", year = "2019", 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.", month = jul, journal = "Computer Graphics Forum", volume = "38", note = "Best Paper Honorable Mention at EuroVis 2019", doi = "https://doi.org/10.1111/cgf.13668", pages = "13--24", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/", } @inproceedings{maruyama-2019-iv, title = "Scale-Aware Cartographic Displacement Based on Constrained Optimization", author = "Ken Maruyama and Shigeo Takahashi and Hsiang-Yun Wu and Kazuo Misue and Masatoshi Arikawa", year = "2019", 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.", month = jul, event = " The 23th International Conference on Information Visualisation ", doi = "https://dx.doi.org/10.1109/IV.2019.00022", booktitle = "Proceedings of the 23th International Conference on Information Visualisation (iV2019)", pages = "74--80", keywords = "Cartographic generalization, displacement, constrained optimization, scale-aware mapping", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/maruyama-2019-iv/", } @article{takahashi-2019-acdt, title = "Mental Map Preservation for Progressively Labeling Railway Networks", author = "Shigeo Takahashi and Ken Maruyama and Takamasa Kawagoe and Hsiang-Yun Wu and Kazuo Misue and Masatoshi Arikawa", year = "2019", 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.", month = jun, doi = "https://doi.org/10.4018/IJACDT.2019010103", journal = "International Journal of Art, Culture and Design Technologies", number = "1", volume = "8", pages = "31--50", keywords = "Geodesic Distances, Mental Maps, Mixed-Integer Programming, Progressive Annotation, Railway Maps, Schematic Layouts", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/takahashi-2019-acdt/", } @article{byska-2019-mdfc, title = "Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization", author = "Jan Byska and Thomas Trautner and Sergio Marques and Jiri Damborsky and Barbora Kozlikova and Manuela Waldner", year = "2019", 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.", month = jun, journal = "Computer Graphics Forum", volume = "38", number = "3", doi = "10.1111/cgf.13701", pages = "441--453", keywords = "scientific visualization, user centered design", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/", } @article{wu-2019-bmc, title = "Metabopolis: Scalable Network Layout for Biological Pathway Diagrams in Urban Map Style", author = "Hsiang-Yun Wu and Martin N\"{o}llenburg and Filipa L. Sousa and Ivan Viola", year = "2019", abstract = "Background Biological 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. Results Our 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. Conclusions We 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.", month = may, doi = "http://doi.org/10.1186/s12859-019-2779-4", journal = "BMC Bioinformatics", number = "187", volume = "20", pages = "1--20", keywords = "Biological pathways, Graph drawing, Mapmetaphor, Orthogonallayout, Floorplanning, Edgerouting", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/", } @misc{vasileva-2019-smw, title = "OptiRoute: Interactive Maps for Wayfinding in a Complex Environment", author = "Elitza Vasileva and Hsiang-Yun Wu", year = "2019", 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.", month = apr, note = "Best Poster Award", event = "schematic Mapping Workshop 2019", Conference date = "Poster presented at schematic Mapping Workshop 2019 (2019)", keywords = " Maps, Route finding, Wayfinding", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/vasileva-2019-smw/", } @misc{wu-2019-smwp, title = "Aspect-Ratio-Preserved Labeling on Metro Maps", author = "Hsiang-Yun Wu and Ken Maruyama and Takamasa Kawagoe and Kazuo Misue and Masatoshi Arikawa and Shigeo Takahashi", year = "2019", 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.", month = apr, event = "Schematic Mapping Workshop 2019", doi = "https://www.ac.tuwien.ac.at/files/pub/smw19-paper-5.pdf", Conference date = "Poster presented at Schematic Mapping Workshop 2019 (2019)", keywords = "Progressive Annotation, Geodesic Distances, Schematic Layout, Mental Maps, Mixed-Integer Programming", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smwp/", } @techreport{wu-2019-report, title = "From Cells to Atoms - Biological Information Visualization (in Chinese)", author = "Hsiang-Yun Wu and Haichao Miao and Ivan Viola", year = "2019", month = mar, number = "TR-193-02-2019-1", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", institution = "Research Unit of Computer Graphics, Institute of Visual Computing and Human-Centered Technology, Faculty of Informatics, TU Wien ", note = "human contact: technical-report@cg.tuwien.ac.at", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/", } @article{raidou2019_prsps, title = "Relaxing Dense Scatter Plots with Pixel-Based Mappings", author = "Renata Raidou and Eduard Gr\"{o}ller and Martin Eisemann", year = "2019", 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.", month = mar, journal = "IEEE Transactions on Visualization and Computer Graphics", volume = "25", doi = "10.1109/TVCG.2019.2903956", pages = "1--12", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/raidou2019_prsps/", } @article{waldin-2019-ccm, title = "Cuttlefish: Color Mapping for Dynamic Multi‐Scale Visualizations", author = "Nicholas Waldin and Manuela Waldner and Mathieu Le Muzic and Eduard Gr\"{o}ller and David Goodsell and Ludovic Autin and Arthur Olson and Ivan Viola", year = "2019", 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.", month = mar, doi = "10.1111/cgf.13611", journal = "Computer Graphics Forum", number = "6", volume = "38", pages = "150--164", keywords = "multiscale visualization, illustrative visualization, molecular visualization", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/waldin-2019-ccm/", } @inproceedings{STEINLECHNER-2019-ICT, title = "A Novel Approach for Immediate, Interactive CT Data Visualization andEvaluation using GPU-based Segmentation and Visual Analysis", author = "Harald Steinlechner and Georg Haaser and Bernd Oberdorfer and Daniel Habe and Stefan Maierhofer and Michael Schw\"{a}rzler and Eduard Gr\"{o}ller", year = "2019", abstract = "CT data of industrially produced cast metal parts are often afflicted with artefacts due to complex geometries ill-suited for the scanning process. Simple global threshold-based porosity detection algorithms usually fail to deliver meaningful results. Other adaptive methods can handle image artefacts, but require long preprocessing times. This makes an efficient analysis workflow infeasible. We propose an alternative approach for analyzing and visualizing volume defects in a fully interactive manner, where analyzing volumes becomes more of an interactive exploration instead of time-consuming parameter guessing interrupted by long processing times. Our system is based on a highly efficient GPU implementation of a segmentation algorithm for porosity detection. The runtime is on the order of seconds for a full volume and parametrization is kept simple due to a single threshold parameter. A fully interactive user interface comprised of multiple linked views allows to quickly identify defects of interest, while filtering out artefacts even in noisy areas.", month = feb, location = "Padova, Italy", event = "International Conference on Industrial Computed Tomography (ICT) 2019", editor = "Simone Carmignato", booktitle = "International Conference on Industrial Computed Tomography (ICT) 2019", pages = "1--6", keywords = "CT, GPU, Inclusion Detection, Interactive Visualisation, VisualAnalysis, Parallel Coordinates, Volume Rendering", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/STEINLECHNER-2019-ICT/", } @article{YOGHOURDJIAN2019, title = "Exploring the limits of complexity: A survey of empirical studies ongraph visualisation", author = "Vahan Yoghourdjian and Daniel Archambault and Stephan Diehl and Tim Dwyer and Karsten Klein and Helen C. Purchase and Hsiang-Yun Wu", year = "2019", abstract = "For decades, researchers in information visualisation and graph drawing have focused on developing techniques for the layout and display of very large and complex networks. Experiments involving human participants have also explored the readability of different styles of layout and representations for such networks. In both bodies of literature, networks are frequently referred to as being ‘large’ or ‘complex’, yet these terms are relative. From a human-centred, experiment point-of-view, what constitutes ‘large’ (for example) depends on several factors, such as data complexity, visual complexity, and the technology used. In this paper, we survey the literature on human-centred experiments to understand how, in practice, different features and characteristics of node–link diagrams affect visual complexity.", month = jan, doi = "https://doi.org/10.1016/j.visinf.2018.12.006", issn = "2468-502X", journal = "Visual Informatics", number = "4", volume = "2", pages = "264--282", keywords = "Graph visualisation, Network visualisation, node–link diagrams, Evaluations, Empirical studies, Cognitive scalability", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/", } @techreport{wu-2018-shonan, title = "Lost in Translation: Alignment of Mental Representations for Visual Analytics, Reimagining the Mental Map and Drawing Stability (NII Shonan Meeting Seminar 127)", author = "Daniel Archambault and Jessie Kennedy and Tatiana von Landesberger and Mark McCann and Fintan McGee and Benjamin Renoust and Hsiang-Yun Wu", year = "2018", month = dec, number = "TR-193-02-2018-1", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", institution = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", note = "human contact: technical-report@cg.tuwien.ac.at", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-shonan/", } @inproceedings{steinboeck-2018-lbg, title = "Casual Visual Exploration of Large Bipartite Graphs Using Hierarchical Aggregation and Filtering", author = "Daniel Steinb\"{o}ck and Eduard Gr\"{o}ller and Manuela Waldner", year = "2018", abstract = "Bipartite graphs are typically visualized using linked lists or matrices. However, these classic visualization techniques do not scale well with the number of nodes. Biclustering has been used to aggregate edges, but not to create linked lists with thousands of nodes. In this paper, we present a new casual exploration interface for large, weighted bipartite graphs, which allows for multi-scale exploration through hierarchical aggregation of nodes and edges using biclustering in linked lists. We demonstrate the usefulness of the technique using two data sets: a database of media advertising expenses of public authorities and author-keyword co-occurrences from the IEEE Visualization Publication collection. Through an insight-based study with lay users, we show that the biclustering interface leads to longer exploration times, more insights, and more unexpected findings than a baseline interface using only filtering. However, users also perceive the biclustering interface as more complex.", month = oct, organization = "IEEE", location = "Konstanz, Germany", event = "4th International Symposium on Big Data Visual and Immersive Analytics", booktitle = "International Symposium on Big Data Visual and Immersive Analytics", keywords = "information visualization, bipartite graphs, biclustering, insight-based evaluation", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/", } @phdthesis{Muehlbacher_diss_2018, title = "Human-Oriented Statistical Modeling: Making Algorithms Accessible through Interactive Visualization", author = "Thomas M\"{u}hlbacher", year = "2018", 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 visual 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. This thesis provides multiple contributions towards a more human-oriented modeling process: 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 for 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 thesis 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 modeling process. First, a new technique called TreePOD guides the selection of decision trees along trade-offs between accuracy and other objectives, such as interpretability. Users 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 domain 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 building 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 reduction and increased transparency of the modeling process. All 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 models more accessible for domain experts, making this work relevant for practitioners and application-oriented researchers alike.", month = aug, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/Muehlbacher_diss_2018/", } @inproceedings{8564188, title = "Progressive Annotation of Schematic Railway Maps", author = "Yuka Yoshida and Ken Maruyama and Takamasa Kawagoe and Hsiang-Yun Wu and Masatoshi Arikawa and Shigeo Takahashi", year = "2018", abstract = "Octilinear network layouts are commonly used as the schematic representation of railway maps due to their enhanced readability. However, it is often time-consuming to place station names on such railway maps by trial and error, especially within the limited labeling space around interchange stations. This paper presents a progressive approach to placing station names around stations in schematic railway maps for better automation of map labeling processes. The idea behind our approach is to annotate stations in dense downtown areas around the interchange stations first and then those in sparse rural areas. This is achieved by introducing the sum of geodesic distances over the railway network to identify the proper order in which to annotate stations. In the actual annotation process, we increase the labeling space around the railway network when necessary by progressively stretching railway line segments while retaining their original directions, which allows us to respect the original schematic layout as much as possible. We present several experimental results to demonstrate the effectiveness of the proposed approach, together with a discussion on parameter tuning in our formulation.", month = jul, event = "The 22nd International Conference Information Visualisation (IV)", doi = "10.1109/iV.2018.00070", booktitle = "Proceedings of the 22nd International Conference Information Visualisation (IV)", pages = "373-378", keywords = "Rail transportation;Layout;Labeling;Spacestations;Optimization;Programming;Visualization;Progressive annotation,geodesic distances, schematic layouts, railway maps, mixed-integerprogramming", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/8564188/", } @article{mazurek-2018-veq, title = "Visualizing Expanded Query Results", author = "Michael Mazurek and Manuela Waldner", year = "2018", abstract = "When performing queries in web search engines, users often face difficulties choosing appropriate query terms. Search engines therefore usually suggest a list of expanded versions of the user query to disambiguate it or to resolve potential term mismatches. However, it has been shown that users find it difficult to choose an expanded query from such a list. In this paper, we describe the adoption of set-based text visualization techniques to visualize how query expansions enrich the result space of a given user query and how the result sets relate to each other. Our system uses a linguistic approach to expand queries and topic modeling to extract the most informative terms from the results of these queries. In a user study, we compare a common text list of query expansion suggestions to three set-based text visualization techniques adopted for visualizing expanded query results – namely, Compact Euler Diagrams, Parallel Tag Clouds, and a List View – to resolve ambiguous queries using interactive query expansion. Our results show that text visualization techniques do not increase retrieval efficiency, precision, or recall. Overall, users rate Parallel Tag Clouds visualizing key terms of the expanded query space lowest. Based on the results, we derive recommendations for visualizations of query expansion results, text visualization techniques in general, and discuss alternative use cases of set-based text visualization techniques in the context of web search.", month = jun, journal = "Computer Graphics Forum", pages = "87--98", keywords = "Information visualization, search interfaces, empirical studies in visualization", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/", } @article{miao2018Dimsum, title = "DimSUM: Dimension and Scale Unifying Maps for Visual Abstraction of DNA Origami Structures", author = "Haichao Miao and Elisa De Llano and Tobias Isenberg and Eduard Gr\"{o}ller and Ivan Barisic and Ivan Viola", year = "2018", month = jun, journal = "Computer Graphics Forum", volume = "37", number = "3", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/", } @misc{wu-2018-metabo, title = "A Visual Comparison of Hand-Drawn and Machine-Generated Human Metabolic Pathways", author = "Hsiang-Yun Wu and Martin N\"{o}llenburg and Ivan Viola", year = "2018", 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. ", month = jun, event = "EuroVis", Conference date = "Poster presented at EuroVis (2018-06-04--2018-06-08)", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/", } @misc{gusenbauer-2018-P, title = "Bitstream - Top-Down/Bottom-Up Data Processing for Interactive Bitcoin Visualization.", author = "Matthias Gusenbauer", year = "2018", abstract = "Analyzing large amounts of data is becoming an ever increasing problem. Bitcoin as an example 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 protocol 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 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. We 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.", month = may, event = "EPILOG", Conference date = "Poster presented at EPILOG (2018-06-18)", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018-P/", } @article{birsak-2017-dpe, title = "Dynamic Path Exploration on Mobile Devices", author = "Michael Birsak and Przemyslaw Musialski and Peter Wonka and Michael Wimmer", year = "2018", abstract = "We present a novel framework for visualizing routes on mobile devices. Our framework is suitable for helping users explore their environment. First, 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.", month = may, doi = "10.1109/TVCG.2017.2690294", issn = "1077-2626", journal = "IEEE Transactions on Visualization and Computer Graphics", number = "5", volume = "24", pages = "1784--1798", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/birsak-2017-dpe/", } @article{wu-2018-JVLC, title = "Overlap-Free Labeling of Clustered Networks Based on Voronoi Tessellation", author = "Hsiang-Yun Wu and Shigeo Takahashi and Rie Ishida", year = "2018", month = feb, journal = "Journal of Visual Languages & Computing", number = "44", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-JVLC/", } @article{polatsek-2018-stv, title = "Exploring visual attention and saliency modeling for task-based visual analysis", author = "Patrik Polatsek and Manuela Waldner and Ivan Viola and Peter Kapec and Wanda Benesova", year = "2018", 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.", month = feb, doi = "https://doi.org/10.1016/j.cag.2018.01.010", journal = "Computers & Graphics", number = "2", keywords = "Information visualization, Eye-tracking experiment, Saliency, Visual attention, Low-level analytical tasks", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/", } @techreport{wu-2017-dagstuhl, title = "Mapifying the Genome, Scalable Set Visualizations (Dagstuhl Seminar 17332)", author = "Radu Jianu and Martin Krzywinski and Luana Micallef and Hsiang-Yun Wu", year = "2018", number = "TR-193-02-2018-2", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", institution = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", note = "human contact: technical-report@cg.tuwien.ac.at", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2017-dagstuhl/", } @phdthesis{sorger-2017-thesis, title = "Integration Strategies in the Visualization of Multifaceted Spatial Data", author = "Johannes Sorger", year = "2017", 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. This 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. The 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. In 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. Another 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. ", month = sep, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", URL = "https://www.cg.tuwien.ac.at/research/publications/2017/sorger-2017-thesis/", } @inproceedings{geymayer-2017-std, title = "How Sensemaking Tools Influence Display Space Usage", author = "Thomas Geymayer and Manuela Waldner and Alexander Lex and Dieter Schmalstieg", year = "2017", abstract = "We explore how the availability of a sensemaking tool influences users’ knowledge externalization strategies. On a large display, users were asked to solve an intelligence analysis task with or without a bidirectionally linked concept-graph (BLC) to organize insights into concepts (nodes) and relations (edges). In BLC, both nodes and edges maintain “deep links” to the exact source phrases and sections in associated documents. In our control condition, we were able to reproduce previously described spatial organization behaviors using document windows on the large display. When using BLC, however, we found that analysts apply spatial organization to BLC nodes instead, use significantly less display space and have significantly fewer open windows.", month = jun, event = "EuroVis 2017", booktitle = "EuroVis Workshop on Visual Analytics", keywords = "sensemaking, large displays, evaluation", URL = "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/", } @inproceedings{waldner-2017-vph, title = "Exploring Visual Prominence of Multi-Channel Highlighting in Visualizations", author = "Manuela Waldner and Alexey Karimov and Eduard Gr\"{o}ller", year = "2017", abstract = "Visualizations make rich use of multiple visual channels so that there are few resources left to make selected focus elements visually distinct from their surrounding context. A large variety of highlighting techniques for visualizations has been presented in the past, but there has been little systematic evaluation of the design space of highlighting. We explore highlighting from the perspective of visual marks and channels – the basic building blocks of visualizations that are directly controlled by visualization designers. We present the results from two experiments, exploring the visual prominence of highlighted marks in scatterplots: First, using luminance as a single highlight channel, we found that visual prominence is mainly determined by the luminance difference between the focus mark and the brightest context mark. The brightness differences between context marks and the overall brightness level have negligible influence. Second, multi-channel highlighting using luminance and blur leads to a good trade-off between highlight effectiveness and aesthetics. From the results, we derive a simple highlight model to balance highlighting across multiple visual channels and focus and context marks, respectively.", month = may, booktitle = "Spring Conference on Computer Graphics 2017", keywords = "information visualization, highlighting, focus+context, visual prominence", URL = "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/", } @inproceedings{vad_viktor-2017-WVE, title = "Watergate: Visual Exploration of Water Trajectories in Protein Dynamics", author = "Viktor Vad and Jan Byska and Adam Jurcik and Ivan Viola and Eduard Gr\"{o}ller and Helwig Hauser and Sergio M. Margues and Jiri Damborsky and Barbora Kozlikova", year = "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.", location = "September, 2017 Bremen, Germany", booktitle = "Eurographics Workshop on Visual Computing for Biology and Medicine 2017", pages = "33--42", URL = "https://www.cg.tuwien.ac.at/research/publications/2017/vad_viktor-2017-WVE/", } @inproceedings{Groeller_2016_P6, title = "PorosityAnalyzer: Visual Analysis and Evaluation of Segmentation Pipelines to Determine the Porosity in Fiber-Reinforced Polymers", author = "Johannes Weissenb\"{o}ck and Artem Amirkhanov and Eduard Gr\"{o}ller and Johannes Kastner and Christoph Heinzl", year = "2016", 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.", month = oct, publisher = "IEEE Computer Society", booktitle = "IEEE Conference on Visual Analytics Science and Technology, 2016 (VAST 2016)", pages = "101--110", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P6/", } @article{Groeller_2016_P4, title = "Visual Analytics for the Exploration and Assessment of Segmentation Errors", author = "Renata Raidou and Freek Marcelis and Marcel Breeuwer and Eduard Gr\"{o}ller and Anna Vilanova i Bartroli and Huub van de Wetering", year = "2016", 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 performance 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.", month = sep, journal = "Eurographics Workshop on Visual Computing for Biology and Medicine", pages = "193--202", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P4/", } @phdthesis{schmidt-phd, title = "Scalable Comparative Visualization", author = "Johanna Schmidt", year = "2016", 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. In 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.", month = jun, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/schmidt-phd/", } @article{ortner-2016-tunnel, title = "Visual analytics and rendering for tunnel crack analysis", author = "Thomas Ortner and Johannes Sorger and Harald Piringer and Gerd Hesina and Eduard Gr\"{o}ller", year = "2016", 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.", month = may, journal = "The Visual Computer", volume = "32", number = "6", pages = "859--869", keywords = "Integration of spatial and non-spatial data, Methodology, Visual analytics", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-tunnel/", } @techreport{TR1862162, title = "Visual Analysis of Volume Ensembles Based on Local Features", author = "Johanna Schmidt and Bernhard Fr\"{o}hler and Reinhold Preiner and Johannes Kehrer and Eduard Gr\"{o}ller and Stefan Bruckner and Christoph Heinzl", year = "2016", 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 industrial domain and two from the medical domain.", month = may, number = "TR-186-2-16-2", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", institution = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", note = "human contact: technical-report@cg.tuwien.ac.at", keywords = "ensemble visualization, guided local exploration, variance analysis", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/", } @misc{klein-2016-WCL, title = "Towards Interactive Visual Exploration of Parallel Programs using a Domain-Specific Language", author = "Tobias Klein and Stefan Bruckner and Eduard Gr\"{o}ller and Markus Hadwiger and Peter Rautek", year = "2016", 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.", month = apr, publisher = "ACM", location = "Vienna, Austria", event = "4th International Workshop on OpenCL (IWOCL '16)", Conference date = "Poster presented at 4th International Workshop on OpenCL (IWOCL '16) ()", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/", } @article{ortner-2016-visaware, title = "Vis-a-ware: Integrating spatial and non-spatial visualization for visibility-aware urban planning", author = "Thomas Ortner and Johannes Sorger and Harald Steinlechner and Gerd Hesina and Harald Piringer and Eduard Gr\"{o}ller", year = "2016", 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.", month = jan, journal = "Visualization and Computer Graphics, IEEE Transactions on", issn = "1077-2626 ", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/ortner-2016-visaware/", } @article{sorger-2015-litevis, title = "LiteVis: Integrated Visualization for Simulation-Based Decision Support in Lighting Design", author = "Johannes Sorger and Thomas Ortner and Christian Luksch and Michael Schw\"{a}rzler and Eduard Gr\"{o}ller and Harald Piringer", year = "2016", 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.", month = jan, journal = "Visualization and Computer Graphics, IEEE Transactions on", volume = "22", number = "1", issn = "1077-2626 ", pages = "290--299", keywords = "Integrating Spatial and Non-Spatial Data", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2015-litevis/", } @article{Groeller_2016_P2, title = "Towards Quantitative Visual Analytics with Structured Brushing and Linked Statistics", author = "Sanjin Rados and Rainer Splechtna and Kresimir Matkovic and Mario Duras and Eduard Gr\"{o}ller and Helwig Hauser", year = "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 linking&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- ally, we introduce two novel brushing techniques: the percentile brush and the Mahalanobis brush. Both use the underlying data 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.", journal = "Computer Graphics Forum (2016)", volume = "35", number = "3", pages = "251--260", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P2/", } @article{miao_2016_cgf, title = "Visual Quantification of the Circle of Willis: An Automated Identification and Standardized Representation", author = "Haichao Miao and Gabriel Mistelbauer and Christian Nasel and Eduard Gr\"{o}ller", year = "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.", issn = "1467-8659", journal = "Computer Graphics Forum", keywords = "Circle of Willis, medical visualization, information visualization", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/", } @article{raidou_eurovis16, title = "Visual Analysis of Tumor Control Models for Prediction of Radiotherapy Response.", author = "Renata Raidou and Oscar Casares-Magaz and Ludvig Paul Muren and Uulke A van der Heide and Jarle Roervik and Marcel Breeuwer and Anna Vilanova i Bartroli", year = "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.", journal = "EuroVis - Eurographics/IEEE-VGTC Symposium on Visualization 2016", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_eurovis16/", } @article{raidou_miccai16, title = "Employing Visual Analytics to Aid the Design of White Matter Hyperintensity Classifiers.", author = "Renata Raidou and Hugo J. Kuijf and Neda Sepasian and Nicola Pezzotti and Willem H. Bouvy and Marcel Breeuwer and Anna Vilanova i Bartroli", year = "2016", abstract = "Accurate segmentation of brain white matter hyperintensi-ties (WMHs) is important for prognosis and disease monitoring. To thisend, classi ers are often trained { usually, using T1 and FLAIR weightedMR images. Incorporating additional features, derived from di usionweighted MRI, could improve classi cation. However, the multitude ofdi usion-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 erent approach, introducing asemi-automated pipeline to select interactively features for WMH classi -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 usivity (MD), and RadialDi usivity (RD) { and secondarily,CSand Fractional Anisotropy (FA).The next step in the pipeline is to train a classi er with these features,and compare its results to a similar classi er, used in previous work withautomated feature selection. Finally, VA is employed again, to analyzeand understand the classi er performance and results.", journal = "Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/raidou_miccai16/", } @article{Groeller_2016_P1, title = " Visual Analysis of Defects in Glass Fiber Reinforced Polymers for 4DCT Interrupted In situ Tests", author = "Aleksandr Amirkhanov and Artem Amirkhanov and Dietmar Salaberger and Johannes Kastner and Eduard Gr\"{o}ller and Christoph Heinzl", year = "2016", abstract = "Material engineers use interrupted in situ tensile testing to investigate the damage mechanisms in composite materials. For each 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 automatic 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, we evaluate our solution and demonstrate its practical applicability.", journal = "Computer Graphics Forum (2016)", volume = " 35", number = "3", issn = "doi: 10.1111/cgf.12896", pages = "201--210", URL = "https://www.cg.tuwien.ac.at/research/publications/2016/Groeller_2016_P1/", } @misc{Diehl_2015, title = "Albero: A Visual Analytics Tool for Probabilistic Weather Forecasting.", author = "Alexandra Diehl and Leandro Pelorosso and Kresimir Matkovic and Claudio Delrieux and Marc Ruiz and Eduard Gr\"{o}ller and Stefan Bruckner", year = "2015", month = nov, location = "University of Buenos Aires", event = "Poster at Workshop Big Data & Environment", Conference date = "Poster presented at Poster at Workshop Big Data & Environment (2015-11)", URL = "https://www.cg.tuwien.ac.at/research/publications/2015/Diehl_2015/", } @inproceedings{sorger-2015-taxintec, title = "A Taxonomy of Integration Techniques for Spatial and Non-Spatial Visualizations", author = "Johannes Sorger and Thomas Ortner and Harald Piringer and Gerd Hesina and Eduard Gr\"{o}ller", year = "2015", 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.", month = oct, series = "Springer Lecture Notes in Computer Science (LNCS) series", publisher = "The Eurographics Association", location = "Aachen, Germany", issn = "0302-9743", editor = "David Bommes and Tobias Ritschel and Thomas Schultz", booktitle = "20th International Symposium on Vision, Modeling and Visualization (VMV 2015)", URL = "https://www.cg.tuwien.ac.at/research/publications/2015/sorger-2015-taxintec/", } @misc{Ganuza_ML_2015_ISA, title = "Interactive Semi-Automatic Categorization for Spinel Group Minerals", author = " Mar\'{i}a Luj\'{a}n Ganuza and Maria Florencia Gargiulo and Gabriela Ferracutti and Silvia Castro and Ernesto Bjerg and Eduard Gr\"{o}ller and Kresimir Matkovic", year = "2015", 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.", month = oct, location = "Chicago, IL, USA ", isbn = " 978-1-4673-9783-4", event = "2015 IEEE Conference on Visual Analytics Science and Technology (VAST) (2015)", Conference date = "Poster presented at 2015 IEEE Conference on Visual Analytics Science and Technology (VAST) (2015) (2015-10-25--2015-10-30)", note = "197--198", pages = "197 – 198", URL = "https://www.cg.tuwien.ac.at/research/publications/2015/Ganuza_ML_2015_ISA/", } @inproceedings{Miao_2015_VCBM, title = "CoWRadar: Visual Quantification of the Circle of Willis in Stroke Patients", author = "Haichao Miao and Gabriel Mistelbauer and Christian Nasel and Eduard Gr\"{o}ller", year = "2015", abstract = "This paper presents a method for the visual quantification of cerebral arteries, known as the Circle of Willis (CoW). The 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 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 advanced technologies in medical image processing and visualization. The goal of this paper is to create 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 display 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. An enumeration technique for the labeling of the arterial segments is therefore suggested. We also propose a method for detecting the CoW’s main supplying arteries by analyzing the coronal, sagittal and transverse image planes of the data sets. 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 of the CoW.", month = sep, isbn = "978-3-905674-82-8", publisher = "The Eurographics Association", organization = "EG Digital Library", location = "Chester, United Kingdom", issn = "2070-5786", editor = "Katja B\"{u}hler and Lars Linsen and Nigel W. John", booktitle = "EG Workshop on Visual Computing for Biology and Medicine", pages = "1--10", URL = "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/", } @habilthesis{Matkovic_Kresimir_2015_, title = "Interactive Visual Analysis of Multi-Parameter Scientific Data", author = "Kresimir Matkovic", year = "2015", 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 data is often heterogeneous. A single data point does not contain scalars or vectors 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. Our 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 of user interaction and computational analysis. The 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 approach 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.", month = may, URL = "https://www.cg.tuwien.ac.at/research/publications/2015/Matkovic_Kresimir_2015_/", } @inproceedings{Bruckner_Stefan_2015_VAS, title = "Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting", author = "Alexandra Diehl and Eduard Gr\"{o}ller and Stefan Bruckner", year = "2015", abstract = "Weather conditions affect multiple aspects of human life such as economy, safety, security, and social activities. For this reason, weather forecast plays a major role in society. Currently weather forecasts are based on Numerical Weather Prediction (NWP) models that generate a representation of the atmospheric flow. Interactive visualization of geo-spatial data has been widely used in order to facilitate the analysis of NWP models. This paper presents a visualization system for the analysis of spatio-temporal patterns in short-term weather forecasts. For this purpose, we provide an interactive visualization interface that guides users from simple visual overviews to more advanced visualization techniques. Our solution presents multiple views that include a timeline with geo-referenced maps, an integrated webmap view, a forecast operation tool, a curve-pattern selector, spatial filters, and a linked meteogram. Two key contributions of this work are the timeline with geo-referenced maps and the curve-pattern selector. The latter provides novel functionality that allows users to specify and search for meaningful patterns in the data. The visual interface of our solution allows users to detect both possible weather trends and errors in the weather forecast model.We illustrate the usage of our solution with a series of case studies that were designed and validated in collaboration with domain experts.", month = may, location = "Cagliari, Sardinia, Italy", booktitle = "Computer Graphic Forum", pages = "381--390", URL = "https://www.cg.tuwien.ac.at/research/publications/2015/Bruckner_Stefan_2015_VAS/", } @article{raidou_EuroVis15, title = "Visual analytics for the exploration of tumor tissue characterization", author = "Renata Raidou and Uulke A van der Heide and Cuong V Dinh and Ghazaleh Ghobadi and Jesper Follsted Kallehauge and Marcel Breeuwer and Anna Vilanova i Bartroli", year = "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.", journal = "In Computer Graphics Forum", URL = "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_EuroVis15/", } @article{raidou_vis15, title = "Orientation-Enhanced Parallel Coordinate Plots", author = "Renata Raidou and Martin Eisemann and Marcel Breeuwer and Elmar Eisemann and Anna Vilanova i Bartroli", year = "2015", journal = "IEEE transactions on visualization and computer graphics", volume = "22", number = "1", pages = "589--598", URL = "https://www.cg.tuwien.ac.at/research/publications/2015/raidou_vis15/", } @article{beham-2014-cupid, title = "Cupid: Cluster-based Exploration of Geometry Generators with Parallel Coordinates and Radial Trees", author = "Michael Beham and Wolfgang Herzner and Eduard Gr\"{o}ller and Johannes Kehrer", year = "2014", 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.", month = dec, journal = "IEEE Transactions on Visualization and Computer Graphics", volume = "20", number = "12", issn = "1077-2626", pages = "1693--1702 ", keywords = "3D shape analysis, radial trees, hierarchical clustering, illustrative parallel coordinates, composite visualization", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/", } @article{Groeller_2014_RWA, title = "Run Watchers: Automatic Simulation-Based Decision Support in Flood Management", author = "Artem Konev and J\"{u}rgen Waser and Berhard Sadransky and Daniel Cornel and Rui A.P. Perdigao and Zsolt Horvath and Eduard Gr\"{o}ller", year = "2014", 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 present 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 due 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 addition, 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 our solution with domain experts.", month = dec, journal = "IEEE Transactions on Visualization and Computer Graphics", volume = "20", number = "12", issn = "1077-2626", booktitle = "IEEE Transactions on Visualization and Computer Graphics/Proceedings of VAST 2014", publisher = "IEEE", pages = "1873--1882", keywords = "visual evidence, Disaster management, simulation control, storytelling, decision making", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/Groeller_2014_RWA/", } @article{Matkovic-2014-ieee, title = "Visual Analytics for Complex Engineering Systems: Hybrid Visual Steering of Simulation Ensembles", author = "Kresimir Matkovic and Denis Gracanin and Rainer Splechtna and M. Jelovic and Benedikt Stehno and Helwig Hauser and Werner Purgathofer", year = "2014", 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.", month = dec, journal = "IEEE Transactions on Visualization and Computer Graphics", volume = "20", number = "12", issn = "1077-2626", pages = "1803--1812", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/Matkovic-2014-ieee/", } @inproceedings{ymca, title = "YMCA - Your Mesh Comparison Application", author = "Johanna Schmidt and Reinhold Preiner and Thomas Auzinger and Michael Wimmer and Eduard Gr\"{o}ller and Stefan Bruckner", year = "2014", 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.", month = nov, series = "VAST ", publisher = "IEEE Computer Society", note = "http://dx.doi.org/10.1109/VAST.2014.7042491", location = "Paris, France", booktitle = "IEEE Visual Analytics Science and Technology", keywords = "mesh comparison, 3D data exploration, focus+context, comparative visualization, Visual analysis", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/", } @inproceedings{waldner-2014-ghi, title = "Graphical Histories of Information Foraging", author = "Manuela Waldner and Stefan Bruckner and Ivan Viola", year = "2014", 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.", month = oct, isbn = "978-1-4503-2542-4", publisher = "ACM", organization = "NordiCHI’14 - Nordic Conference on Human-Computer Interaction", location = "Helsinki, Finland", booktitle = "Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational ", pages = "295--304", keywords = "Graph visualization, Interaction history, Provenance", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/waldner-2014-ghi/", } @article{birsak-2014-agtb, title = "Automatic Generation of Tourist Brochures", author = "Michael Birsak and Przemyslaw Musialski and Peter Wonka and Michael Wimmer", year = "2014", 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. The 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. The 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. Video: http://www.youtube.com/watch?v=t3w7uxzSR-Y", month = apr, journal = "Computer Graphics Forum (Proceedings of EUROGRAPHICS 2014)", volume = "33", number = "2", issn = "1467-8659", pages = "449--458", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/birsak-2014-agtb/", } @article{raidou_vis14, title = "Visual analytics for the exploration of multiparametric cancer imaging", author = "Renata Raidou and Marta Paes Moreira and Wouter van Elmpt and Marcel Breeuwer and Anna Vilanova i Bartroli", year = "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.", journal = "In Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on Visualization", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vis14/", } @article{raidou_vcbm14, title = "The iCoCooN:Integration of Cobweb Charts with Parallel Coordinates forVisual Analysis of DCE-MRI Modeling Variations", author = "Renata Raidou and Uulke A van der Heide and PJ van Houdt and Marcel Breeuwer and Anna Vilanova i Bartroli", year = "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", journal = "Eurographics Workshop on Visual Computing for Biology and Medicine ", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/raidou_vcbm14/", } @article{kehrer-2013-SBC, title = "A Model for Structure-based Comparison of Many Categories in Small-Multiple Displays", author = "Johannes Kehrer and Harald Piringer and Wolfgang Berger and Eduard Gr\"{o}ller", year = "2013", abstract = "Many application domains deal with multi-variate data that consists of both categorical and numerical information. Small-multiple displays are a powerful concept for comparing such data by juxtaposition. For comparison by overlay or by explicit encoding of computed differences, however, a specification of references is necessary. In this paper, we present a formal model for defining semantically meaningful comparisons between many categories in a small-multiple display. Based on pivotized data that are hierarchically partitioned by the categories assigned to the x and y axis of the display, we propose two alternatives for structure-based comparison within this hierarchy. With an absolute reference specification, categories are compared to a fixed reference category. With a relative reference specification, in contrast, a semantic ordering of the categories is considered when comparing them either to the previous or subsequent category each. Both reference specifications can be defined at multiple levels of the hierarchy (including aggregated summaries), enabling a multitude of useful comparisons. We demonstrate the general applicability of our model in several application examples using different visualizations that compare data by overlay or explicit encoding of differences.", month = dec, journal = "IEEE Transactions on Visualization and Computer Graphics", volume = "19", number = "12", pages = "2287--2296", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/", } @article{vaico, title = "VAICo: Visual Analysis for Image Comparison", author = "Johanna Schmidt and Eduard Gr\"{o}ller and Stefan Bruckner", year = "2013", 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.", month = dec, journal = "IEEE Transactions on Visualization and Computer Graphics", volume = "19", number = "12", note = "Demo: http://www.cg.tuwien.ac.at/~jschmidt/vaico/", pages = "2090--2099", keywords = "focus+context, image-set comparison, Comparative visualization", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/vaico/", } @inproceedings{sorger-2013-neuromap, title = "neuroMAP - Interactive Graph-Visualization of the Fruit Fly's Neural Circuit", author = "Johannes Sorger and Katja B\"{u}hler and Florian Schulze and Tianxiao Liu and Barry Dickson", year = "2013", 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.", month = oct, publisher = "IEEE", location = "Atlanta", booktitle = "Biological Data Visualization (BioVis), 2013 IEEE Symposium on ", pages = "73--80", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/sorger-2013-neuromap/", } @inproceedings{waldner-2013-facetCloudsGI, title = "FacetClouds: Exploring Tag Clouds for Multi-Dimensional Data", author = "Manuela Waldner and Johann Schrammel and Michael Klein and Katrin Kristjansdottir and Dominik Unger and Manfred Tscheligi", year = "2013", 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. FacetClouds 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. ", month = may, isbn = "978-1-4822-1680-6 ", publisher = "ACM Publishing House", organization = "ACM Siggraph", location = "Regina, Saskatchewan, Canada", address = "Regina, Saskatchewan, Canada", booktitle = "Proceedings of the 2013 Graphics Interface Conference", pages = "17--24", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-facetCloudsGI/", } @inproceedings{waldner-2013-ubiWM, title = "Towards Ubiquitous Information Space Management", author = "Manuela Waldner and Dieter Schmalstieg", year = "2013", 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. ", month = may, isbn = "978-1-4503-1952-2", publisher = "ACM", location = "Paris, France", booktitle = "POWERWALL: International Workshop on Interactive, Ultra-High-Resolution Displays, part of the SIGCHI Conference on Human Factors in Computing Systems (2013)", pages = "1--6", keywords = "information management, ubiquitous displays", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/waldner-2013-ubiWM/", } @article{borgo-2013-gly, title = "Glyph-based Visualization: Foundations, Design Guidelines, Techniques and Applications", author = "Rita Borgo and Johannes Kehrer and David H.S. Chung and Eamonn Maguire and Robert S. Laramee and Helwig Hauser and Matthew Ward and Min Chen", year = "2013", 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.", month = may, journal = "Eurographics State of the Art Reports", note = "http://diglib.eg.org/EG/DL/conf/EG2013/stars/039-063.pdf", publisher = "Eurographics Association", series = "EG STARs", pages = "39--63", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/", } @article{Kehrer-2013-STAR, title = "Visualization and Visual Analysis of Multi-faceted Scientific Data: A Survey", author = "Johannes Kehrer and Helwig Hauser", year = "2013", 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.", month = mar, issn = "1077-2626", journal = "IEEE Transactions on Visualization and Computer Graphics", note = "Spotlight paper of the March issue of TVCG", number = "3", volume = "19", pages = "495--513", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/", } @phdthesis{Konyha_2013_IVA, title = "Interactive Visual Analysis in Automotive Engineering Design", author = "Zoltan Konyha", year = "2013", abstract = "Computational simulation has become instrumental in the design process in automotive engineering. Virtually 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. They 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 that lead to undesired results. Computational 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 data 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. In 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 opportunities. 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 less precisely defined problems can be solved. We introduce a data model that effectively represents the multi-run, time-dependent simulation results 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, are integrated into a coordinated multiple views framework. All views provide focus+context visualization. Compositions of brushes spanning several views can be defined iteratively to select interesting features and promote information drill-down. Valuable insight into the spatial aspect of the data can be gained from (generally domain-specific) spatio-temporal visualizations. In this thesis, we propose interactive, glyph-based 3D visualization techniques for the analysis of rigid and elastic multibody system simulations. We 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 that cannot be specified by combinations of simple brushes on the original data attributes. The combination of these building blocks supports interactive knowledge discovery. The analyst can build 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. Complex tasks, such as parameter sensitivity analysis and optimization can be solved. Although the primary motivation for our work was the analysis of simulation data sets in automotive engineering, we 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 containing families of function graphs. Two 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 been integrated into a commercially distributed software suite for engineers. This suggests that their impact can extend beyond the visualization research community.", month = jan, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/Konyha_2013_IVA/", } @article{Ribicic_2012_VAS, title = "Visual analysis and steering of flooding simulations", author = "Hrvoje Ribi\v{c}i\'{c} and J\"{u}rgen Waser and Raphael Fuchs and G\"{u}nter Bl\"{o}schl and Eduard Gr\"{o}ller", year = "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.", journal = "IEEE Transaction on Visualization and Computer Graphics", number = "99", volume = "PP", URL = "https://www.cg.tuwien.ac.at/research/publications/2012/Ribicic_2012_VAS/", } @article{Groeller_2011_NR, title = "Nodes on Ropes: A Comprehensive Data and Control Flow for Steering Ensemble Simulations", author = "J\"{u}rgen Waser and Hrvoje Ribi\v{c}i\'{c} and Raphael Fuchs and Christian Hirsch and Benjamin Schindler and G\"{u}nter Bl\"{o}schl and Eduard Gr\"{o}ller", year = "2011", abstract = "Flood disasters are the most common natural risk and tremendous efforts are spent to improve their simulation and management. However, simulation-based investigation of actions that can be taken in case of flood emergencies is rarely done. This is in part due to the lack of a comprehensive framework which integrates and facilitates these efforts. In this paper, we tackle several problems which are related to steering a flood simulation. One issue is related to uncertainty. We need to account for uncertain knowledge about the environment, such as levee-breach locations. Furthermore, the steering process has to reveal how these uncertainties in the boundary conditions affect the confidence in the simulation outcome. Another important problem is that the simulation setup is often hidden in a black-box. We expose system internals and show that simulation steering can be comprehensible at the same time. This is important because the domain expert needs to be able to modify the simulation setup in order to include local knowledge and experience. In the proposed solution, users steer parameter studies through the World Lines interface to account for input uncertainties. The transport of steering information to the underlying data-flow components is handled by a novel meta-flow. The meta-flow is an extension to a standard data-flow network, comprising additional nodes and ropes to abstract parameter control. The meta-flow has a visual representation to inform the user about which control operations happen. Finally, we present the idea to use the data-flow diagram itself for visualizing steering information and simulation results. We discuss a case-study in collaboration with a domain expert who proposes different actions to protect a virtual city from imminent flooding. The key to choosing the best response strategy is the ability to compare different regions of the parameter space while retaining an understanding of what is happening inside the data-flow system.", month = dec, issn = "1077-2626", journal = "IEEE Transactions on Visualization and Computer Graphics", number = "12", volume = "17", pages = "1872--1881", URL = "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_NR/", } @phdthesis{PH-2011-LDS, title = "Large Data Scalability in Interactive Visual Analysis", author = "Harald Piringer", year = "2011", 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. The power of the human visual system makes visualization an appropriate method to comprehend large data. In particular interactive visualization enables a discourse between the human brain and the data that can transform a cognitive problem to a perceptual one. However, the visual analysis of large and complex datasets involves both visual and computational challenges. Visual limits involve perceptual and cognitive limitations of the user and restrictions of the display devices while computational limits are related to the computational complexity of the involved algorithms. The goal of this thesis is to advance the state of the art in visual analysis with respect to the scalability to large datasets. Due to the multifaceted nature of scalability, the contributions span a broad range to enhance computational scalability, to improve the visual scalability of selected visualization approaches, and to support an analysis of high-dimensional data. Concerning computational scalability, this thesis describes a generic architecture to facilitate the development of highly interactive visual analysis tools using multi-threading. The architecture builds on the separation of the main application thread and dedicated visualization threads, which can be cancelled early due to user interaction. A quantitative evaluation shows fast visual feedback during continuous interaction even for millions of entries. Two variants of scatterplots address the visual scalability of different types of data and tasks. For continuous data, a combination of 2D and 3D scatterplots intends to combine the advantages of 2D interaction and 3D visualization. Several extensions improve the depth perception in 3D and address the problem of unrecognizable point densities in both 2D and 3D. For partly categorical data, the thesis contributes Hierarchical Difference Scatterplots to relate multiple hierarchy levels and to explicitly visualize differences between them in the context of the absolute position of pivoted values. While comparisons in Hierarchical Difference Scatterplots are only qualitative, this thesis also contributes an approach for quantifying subsets of the data by means of statistical moments for a potentially large number of dimensions. This approach has proven useful as an initial overview as well as for a quantitative comparison of local features like clusters. As an important application of visual analysis, the validation of regression models also involves the scalability to multi-dimensional data. This thesis describes a design study of an approach called HyperMoVal for this task. The key idea is to visually relate n-dimensional scalar functions to known validation data within a combined visualization. The integration with other multivariate views is a step towards a user-centric workflow for model building. Being the result of collaboration with experts in engine design, HyperMoVal demonstrates how 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 research community. Moreover, most contributions of this thesis have been combined in a commercially distributed software framework for engineering applications that will hopefully raise the awareness and promote the use of visual analysis in multiple application domains.", month = may, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", keywords = "high dimensionality, Visualization, Scalability, Interaction, Data analysis, multi-threading, scatter plots", URL = "https://www.cg.tuwien.ac.at/research/publications/2011/PH-2011-LDS/", } @phdthesis{waser_2011_VSD, title = "Visual Steering to Support Decision Making in Visdom", author = "J\"{u}rgen Waser", year = "2011", abstract = "Computer simulation has become an ubiquitous tool to investigate the nature of systems. When steering a simulation, users modify parameters to study their impact on the simulation outcome. The ability to test alternative options provides the basis for interactive decision making. Increasingly complex simulations are characterized by an intricate interplay of many heterogeneous input and output parameters. A steering concept that combines simulation and visualization within a single, comprehensive system is largely missing. This thesis targets the basic components of a novel integrated steering system called Visdom to support the user in the decision making process. The proposed techniques enable users to examine alternative scenarios without the need for special simulation expertise. To accomplish this, we propose World Lines as a management strategy for multiple, related simulation runs. In a dedicated view, users create and navigate through many simulation runs. New decisions are included through the concept of branching. To account for uncertain knowledge about the input parameters, we provide the ability to cover full parameter distributions. Via multiple cursors, users navigate a system of multiple linked views through time and alternative scenarios. In this way, the system supports comparative visual analysis of many simulation runs. Since the steering process generates a huge amount of information, we employ the machine to support the user in the search for explanations inside the computed data. Visdom is built on top of a data-flow network to provide a high level of modularity. A decoupled meta-flow is in charge of transmitting parameter changes from World Lines to the affected dataflow nodes. To direct the user attention to the most relevant parts, we provide dynamic visualization inside the flow diagram. The usefulness of the presented approach is substantiated through case studies in the field of flood management. The Visdom application enables the design of a breach closure by dropping sandbags in a virtual environment.", month = may, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", keywords = "CFD, Data-Flow, Simulation Steering, Comparative Visual Analysis, Multiple Simulation Runs, Problem Solving Environment, Hypothesis Generation, Uncertainty, Flood Management", URL = "https://www.cg.tuwien.ac.at/research/publications/2011/waser_2011_VSD/", } @article{karnik-09-shapegrammar, title = "A Shape Grammar for Developing Glyph-based Visualizations", author = "Pushpak Karnik and Stefan Jeschke and David Cline and Anshuman Razdan and E. Wentz and Peter Wonka", year = "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 increases modeling efficiency over similarly flexible systems currently in use.", issn = "0167-7055", journal = "Computer Graphics Forum", number = "8", volume = "28", pages = "2176--2188", URL = "https://www.cg.tuwien.ac.at/research/publications/2009/karnik-09-shapegrammar/", }