@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/", } @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/", } @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{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{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/", } @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_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/", } @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/", } @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{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/", } @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_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{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{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/", } @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/", } @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_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{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{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/", } @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/", } @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{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/", }