EuroVis14: Eurographics Conference on Visualization

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https://diglib.eg.org/handle/10.2312/13889

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Visualizing Validation of Protein Surface Classifiers
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Sarikaya, Alper; Albers, Danielle; Mitchell, Julie; Gleicher, Michael; H. Carr, P. Rheingans, and H. Schumann
Many bioinformatics applications construct classifiers that are validated in experiments that compare their results to known ground truth over a corpus. In this paper, we introduce an approach for exploring the results of such classifier validation experiments, focusing on classifiers for regions of molecular surfaces. We provide a tool that allows for examining classification performance patterns over a test corpus. The approach combines a summary view that provides information about an entire corpus of molecules with a detail view that visualizes classifier results directly on protein surfaces. Rather than displaying miniature 3D views of each molecule, the summary provides 2D glyphs of each protein surface arranged in a reorderable, small-multiples grid. Each summary is specifically designed to support visual aggregation to allow the viewer to both get a sense of aggregate properties as well as the details that form them. The detail view provides a 3D visualization of each protein surface coupled with interaction techniques designed to support key tasks, including spatial aggregation and automated camera touring. A prototype implementation of our approach is demonstrated on protein surface classifier experiments.
Illustrative Visualization of Molecular Reactions using Omniscient Intelligence and Passive Agents
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Muzic, Mathieu Le; Parulek, Julius; Stavrum, Anne Kristin; Viola, Ivan; H. Carr, P. Rheingans, and H. Schumann
In this paper we propose a new type of a particle systems, tailored for illustrative visualization purposes, in particular for visualizing molecular reactions in biological networks. Previous visualizations of biochemical processes were exploiting the results of agent-based modeling. Such modeling aims at reproducing accurately the stochastic nature of molecular interactions. However, it is impossible to expect events of interest happening at a certain time and location, which is impractical for storytelling. To obtain the means of controlling molecular interactions, we propose to govern passive agents with an omniscient intelligence, instead of giving to the agents the freedom of initiating reaction autonomously. This makes it possible to generate illustrative animated stories that communicate the functioning of the molecular machinery. The rendering performance delivers for interactive framerates of massive amounts of data, based on the dynamic tessellation capabilities of modern graphics cards. Finally, we report an informal expert feedback we obtained from the potential users.
Comparative Exploration of Document Collections: a Visual Analytics Approach
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Oelke, Daniela; Strobelt, Hendrik; Rohrdantz, Christian; Gurevych, Iryna; Deussen, Oliver; H. Carr, P. Rheingans, and H. Schumann
We present an analysis and visualization method for computing what distinguishes a given document collection from others. We determine topics that discriminate a subset of collections from the remaining ones by applying probabilistic topic modeling and subsequently approximating the two relevant criteria distinctiveness and characteristicness algorithmically through a set of heuristics. Furthermore, we suggest a novel visualization method called DiTop-View, in which topics are represented by glyphs (topic coins) that are arranged on a 2D plane. Topic coins are designed to encode all information necessary for performing comparative analyses such as the class membership of a topic, its most probable terms and the discriminative relations. We evaluate our topic analysis using statistical measures and a small user experiment and present an expert case study with researchers from political sciences analyzing two real-world datasets.
Parallel Irradiance Caching for Interactive Monte-Carlo Direct Volume Rendering
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Khlebnikov, Rostislav; Voglreiter, Philip; Steinberger, Markus; Kainz, Bernhard; Schmalstieg, Dieter; H. Carr, P. Rheingans, and H. Schumann
We propose a technique to build the irradiance cache for isotropic scattering simultaneously with Monte Carlo progressive direct volume rendering on a single GPU, which allows us to achieve up to four times increased convergence rate for complex scenes with arbitrary sources of light. We use three procedures that run concurrently on a single GPU. The first is the main rendering procedure. The second procedure computes new cache entries, and the third one corrects the errors that may arise after creation of new cache entries. We propose two distinct approaches to allow massive parallelism of cache entry creation. In addition, we show a novel extrapolation approach which outputs high quality irradiance approximations and a suitable prioritization scheme to increase the convergence rate by dedicating more computational power to more complex rendering areas.
GuideME: Slice-guided Semiautomatic Multivariate Exploration of Volumes
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Zhou, Liang; Hansen, Charles; H. Carr, P. Rheingans, and H. Schumann
Multivariate volume visualization is important for many applications including petroleum exploration and medicine. State-of-the-art tools allow users to interactively explore volumes with multiple linked parameter-space views. However, interactions in the parameter space using trial-and-error may be unintuitive and time consuming. Furthermore, switching between different views may be distracting. In this paper, we propose GuideME: a novel slice-guided semiautomatic multivariate volume exploration approach. Specifically, the approach comprises four stages: attribute inspection, guided uncertainty-aware lasso creation, automated feature extraction and optional spatial fine tuning and visualization. Throughout the exploration process, the user does not need to interact with the parameter views at all and examples of complex real-world data demonstrate the usefulness, efficiency and ease-of-use of our method.
Visual Analysis of Sets of Heterogeneous Matrices Using Projection-Based Distance Functions and Semantic Zoom
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Behrisch, Michael; Davey, James; Fischer, Fabian; Thonnard, Olivier; Schreck, Tobias; Keim, Daniel; Kohlhammer, Jörn; H. Carr, P. Rheingans, and H. Schumann
Matrix visualization is an established technique in the analysis of relational data. It is applicable to large, dense networks, where node-link representations may not be effective. Recently, domains have emerged in which the comparative analysis of sets of matrices of potentially varying size is relevant. For example, to monitor computer network traffic a dynamic set of hosts and their peer-to-peer connections on different ports must be analysed. A matrix visualization focused on the display of one matrix at a time cannot cope with this task. We address the research problem of the visual analysis of sets of matrices. We present a technique for comparing matrices of potentially varying size. Our approach considers the rows and/or columns of a matrix as the basic elements of the analysis. We project these vectors for pairs of matrices into a low-dimensional space which is used as the reference to compare matrices and identify relationships among them. Bipartite graph matching is applied on the projected elements to compute a measure of distance. A key advantage of this measure is that it can be interpreted and manipulated as a visual distance function, and serves as a comprehensible basis for ranking, clustering and comparison in sets of matrices. We present an interactive system in which users may explore the matrix distances and understand potential differences in a set of matrices. A flexible semantic zoom mechanism enables users to navigate through sets of matrices and identify patterns at different levels of detail. We demonstrate the effectiveness of our approach through a case study and provide a technical evaluation to illustrate its strengths.
ConVis: A Visual Text Analytic System for Exploring Blog Conversations
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Hoque, Enamul; Carenini, Giuseppe; H. Carr, P. Rheingans, and H. Schumann
Today it is quite common for people to exchange hundreds of comments in online conversations (e.g., blogs). Often, it can be very difficult to analyze and gain insights from such long conversations. To address this problem, we present a visual text analytic system that tightly integrates interactive visualization with novel text mining and summarization techniques to fulfill information needs of users in exploring conversations. At first, we perform a user requirement analysis for the domain of blog conversations to derive a set of design principles. Following these principles, we present an interface that visualizes a combination of various metadata and textual analysis results, supporting the user to interactively explore the blog conversations. We conclude with an informal user evaluation, which provides anecdotal evidence about the effectiveness of our system and directions for further design.
SimilarityExplorer: A Visual Inter-Comparison Tool for Multifaceted Climate Data
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Poco, Jorge; Dasgupta, Aritra; Wei, Yaxing; Hargrove, William; Schwalm, Christopher; Cook, Robert; Bertini, Enrico; Silva, Claudio; H. Carr, P. Rheingans, and H. Schumann
Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, like, simulations of photosynthesis and respiration, using algorithms and driving variables such as climate and land use. While it is widely accepted that interactive visualization can enable scientists to better explore model similarity from different perspectives and different granularity of space and time, currently there is a lack of such visualization tools. In this paper we present three main contributions. First, we propose a domain characterization for the TBM community by systematically defining the domain-specific intents for analyzing model similarity and characterizing the different facets of the data. Second, we define a classification scheme for combining visualization tasks and multiple facets of climate model data in one integrated framework, which can be leveraged for translating the tasks into the visualization design. Finally, we present SimilarityExplorer, an exploratory visualization tool that facilitates similarity comparison tasks across both space and time through a set of coordinated multiple views. We present two case studies from three climate scientists, who used our tool for a month for gaining scientific insights into model similarity. Their experience and results validate the effectiveness of our tool.
Volumetric Data Reduction in a Compressed Sensing Framework
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Xu, Xie; Sakhaee, Elham; Entezari, Alireza; H. Carr, P. Rheingans, and H. Schumann
In this paper, we investigate compressed sensing principles to devise an in-situ data reduction framework for visualization of volumetric datasets. We exploit the universality of the compressed sensing framework and show that the proposed method offers a refinable data reduction approach for volumetric datasets. The accurate reconstruction is obtained from partial Fourier measurements of the original data that are sensed without any prior knowledge of specific feature domains for the data. Our experiments demonstrate the superiority of surfacelets for efficient representation of volumetric data. Moreover, we establish that the accuracy of reconstruction can further improve once a more effective basis for a sparser representation of the data becomes available.
A Gaze-enabled Graph Visualization to Improve Graph Reading Tasks
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Okoe, Mershack; Alam, Sayeed Safayet; Jianu, Radu; H. Carr, P. Rheingans, and H. Schumann
Performing typical network tasks such as node scanning and path tracing can be difficult in large and dense graphs. To alleviate this problem we use eye-tracking as an interactive input to detect tasks that users intend to perform and then produce unobtrusive visual changes that support these tasks. First, we introduce a novel fovea based filtering that dims out edges with endpoints far removed from a user's view focus. Second, we highlight edges that are being traced at any given moment or have been the focus of recent attention. Third, we track recently viewed nodes and increase the saliency of their neighborhoods. All visual responses are unobtrusive and easily ignored to avoid unintentional distraction and to account for the imprecise and low-resolution nature of eyetracking. We also introduce a novel gaze-correction approach that relies on knowledge about the network layout to reduce eye-tracking error. Finally, we present results from a controlled user study showing that our methods led to a statistically significant accuracy improvement in one of two network tasks and that our gaze-correction algorithm enables more accurate eye-tracking interaction.
Comparative Visualization of Molecular Surfaces Using Deformable Models
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Scharnowski, Katrin; Krone, Michael; Reina, Guido; Kulschewski, Tobias; Pleiss, Jürgen; Ertl, Thomas; H. Carr, P. Rheingans, and H. Schumann
The comparison of molecular surface attributes is of interest for computer aided drug design and the analysis of biochemical simulations. Due to the non-rigid nature of molecular surfaces, partial shape matching is feasible for mapping two surfaces onto each other. We present a novel technique to obtain a mapping relation between two surfaces using a deformable model approach. This relation is used for pair-wise comparison of local surface attributes (e.g. electrostatic potential). We combine the difference value as well as the comparability as derived from the local matching quality in a 3D molecular visualization by mapping them to color. A 2D matrix shows the global dissimilarity in an overview of different data sets in an ensemble. We apply our visualizations to simulation results provided by collaborators from the field of biochemistry to evaluate the effectiveness of our results.
Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Liu, Shusen; Wang, Bei; Bremer, Peer-Timo; Pascucci, Valerio; H. Carr, P. Rheingans, and H. Schumann
Dimension reduction techniques are essential for feature selection and feature extraction of complex highdimensional data. These techniques, which construct low-dimensional representations of data, are typically geometrically motivated, computationally efficient and approximately preserve certain structural properties of the data. However, they are often used as black box solutions in data exploration and their results can be difficult to interpret. To assess the quality of these results, quality measures, such as co-ranking [LV09], have been proposed to quantify structural distortions that occur between high-dimensional and low-dimensional data representations. Such measures could be evaluated and visualized point-wise to further highlight erroneous regions [MLGH13]. In this work, we provide an interactive visualization framework for exploring high-dimensional data via its twodimensional embeddings obtained from dimension reduction, using a rich set of user interactions. We ask the following question: what new insights do we obtain regarding the structure of the data, with interactive manipulations of its embeddings in the visual space? We augment the two-dimensional embeddings with structural abstractions obtained from hierarchical clusterings, to help users navigate and manipulate subsets of the data. We use point-wise distortion measures to highlight interesting regions in the domain, and further to guide our selection of the appropriate level of clusterings that are aligned with the regions of interest. Under the static setting, point-wise distortions indicate the level of structural uncertainty within the embeddings. Under the dynamic setting, on-thefly updates of point-wise distortions due to data movement and data deletion reflect structural relations among different parts of the data, which may lead to new and valuable insights.
Extracting Features from Time-Dependent Vector Fields Using Internal Reference Frames
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Bhatia, Harsh; Pascucci, Valerio; Kirby, Robert M.; Bremer, Peer-Timo; H. Carr, P. Rheingans, and H. Schumann
Extracting features from complex, time-dependent flow fields remains a significant challenge despite substantial research efforts, especially because most flow features of interest are defined with respect to a given reference frame. Pathline-based techniques, such as the FTLE field, are complex to implement and resource intensive, whereas scalar transforms, such as l2, often produce artifacts and require somewhat arbitrary thresholds. Both approaches aim to analyze the flow in a more suitable frame, yet neither technique explicitly constructs one. This paper introduces a new data-driven technique to compute internal reference frames for large-scale complex flows. More general than uniformly moving frames, these frames can transform unsteady fields, which otherwise require substantial processing of resources, into a sequence of individual snapshots that can be analyzed using the large body of steady-flow analysis techniques. Our approach is simple, theoretically well-founded, and uses an embarrassingly parallel algorithm for structured as well as unstructured data. Using several case studies from fluid flow and turbulent combustion, we demonstrate that internal frames are distinguished, result in temporally coherent structures, and can extract well-known as well as notoriously elusive features one snapshot at a time.
Visualizing Multidimensional Data with Glyph SPLOMs
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Yates, Andrew; Webb, Allison; Sharpnack, Michael; Chamberlin, Helen; Huang, Kun; Machiraju, Raghu; H. Carr, P. Rheingans, and H. Schumann
Scatterplot matrices or SPLOMs provide a feasible method of visualizing and representing multi-dimensional data especially for a small number of dimensions. For very high dimensional data, we introduce a novel technique to summarize a SPLOM, as a clustered matrix of glyphs, or a Glyph SPLOM. Each glyph visually encodes a general measure of dependency strength, distance correlation, and a logical dependency class based on the occupancy of the scatterplot quadrants. We present the Glyph SPLOM as a general alternative to the traditional correlation based heatmap and the scatterplot matrix in two examples: demography data from the World Health Organization (WHO), and gene expression data from developmental biology. By using both, dependency class and strength, the Glyph SPLOM illustrates high dimensional data in more detail than a heatmap but with more summarization than a SPLOM. More importantly, the summarization capabilities of Glyph SPLOM allow for the assertion of ''necessity'' causal relationships in the data and the reconstruction of interaction networks in various dynamic systems.
Comparative Blood Flow Visualization for Cerebral Aneurysm Treatment Assessment
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Pelt, Roy van; Gasteiger, Rocco; Lawonn, Kai; Meuschke, Monique; Preim, Bernhard; H. Carr, P. Rheingans, and H. Schumann
A pathological vessel dilation in the brain, termed cerebral aneurysm, bears a high risk of rupture, and is associated with a high mortality. In recent years, incidental findings of unruptured aneurysms have become more frequent, mainly due to advances in medical imaging. The pathological condition is often treated with a stent that diverts the blood flow from the aneurysm sac back to the original vessel. Prior to treatment, neuroradiologists need to decide on the optimal stent configuration and judge the long-term rupture risk, for which blood flow information is essential. Modern patient-specific simulations can model the hemodynamics for various stent configurations, providing important indicators to support the decision-making process. However, the necessary visual analysis of these data becomes tedious and time-consuming, because of the abundance of information. We introduce a comprehensive comparative visualization that integrates morphology with blood flow indicators to facilitate treatment assessment. To deal with the visual complexity, we propose a details-on-demand approach, combining established medical visualization techniques with innovative glyphs inspired by information visualization concepts. In an evaluation we have obtained informal feedback from domain experts, gauging the value of our visualization.
Preface and Table of Contents
(The Eurographics Association and Blackwell Publishing Ltd., 2014) H. Carr, P. Rheingans, and H. Schumann
Authoring Narrative Visualizations with Ellipsis
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Satyanarayan, Arvind; Heer, Jeffrey; H. Carr, P. Rheingans, and H. Schumann
Data visualization is now a popular medium for journalistic storytelling. However, current visualization tools either lack support for storytelling or require significant technical expertise. Informed by interviews with journalists, we introduce a model of storytelling abstractions that includes state-based scene structure, dynamic annotations and decoupled coordination of multiple visualization components. We instantiate our model in Ellipsis: a system that combines a domain-specific language (DSL) for storytelling with a graphical interface for story authoring. User interactions are automatically translated into statements in the Ellipsis DSL. By enabling storytelling without programming, the Ellipsis interface lowers the threshold for authoring narrative visualizations. We evaluate Ellipsis through example applications and user studies with award-winning journalists. Study participants find Ellipsis to be a valuable prototyping tool that can empower journalists in the creation of interactive narratives.
Papilio: Visualizing Android Application Permissions
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Loorak, Mona Hosseinkhani; Fong, Philip W. L.; Carpendale, Sheelagh; H. Carr, P. Rheingans, and H. Schumann
We introduce Papilio, a new visualization technique for visualizing permissions of real-world Android applications. We explore the development of layouts that exploit the directed acyclic nature of Android application permission data to develop a new explicit layout technique that incorporates aspects of set membership, node-link diagrams and matrix layouts. By grouping applications based on sets of requested permissions, a structure can be formed with partially ordered relations. The Papilio layout shows sets of applications centrally, the relations among applications on one side and application permissions, as the reason behind the existence of the partial order, on the other side. Using Papilio to explore a set of Android applications as a case study has led to new security findings regarding permission usage by Android applications
Towards an Unbiased Comparison of CC, BCC, and FCC Lattices in Terms of Prealiasing
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Vad, Viktor; Csébfalvi, Balázs; Rautek, Peter; Gröller, Eduard; H. Carr, P. Rheingans, and H. Schumann
In the literature on optimal regular volume sampling, the Body-Centered Cubic (BCC) lattice has been proven to be optimal for sampling spherically band-limited signals above the Nyquist limit. On the other hand, if the sampling frequency is below the Nyquist limit, the Face-Centered Cubic (FCC) lattice was demonstrated to be optimal in reducing the prealiasing effect. In this paper, we confirm that the FCC lattice is indeed optimal in this sense in a certain interval of the sampling frequency. By theoretically estimating the prealiasing error in a realistic range of the sampling frequency, we show that in other frequency intervals, the BCC lattice and even the traditional Cartesian Cubic (CC) lattice are expected to minimize the prealiasing. The BCC lattice is superior over the FCC lattice if the sampling frequency is not significantly below the Nyquist limit. Interestingly, if the original signal is drastically undersampled, the CC lattice is expected to provide the lowest prealiasing error. Additionally, we give a comprehensible clarification that the sampling efficiency of the FCC lattice is lower than that of the BCC lattice. Although this is a well-known fact, the exact percentage has been erroneously reported in the literature. Furthermore, for the sake of an unbiased comparison, we propose to rotate the Marschner-Lobb test signal such that an undue advantage is not given to either lattice
Networks of Names: Visual Exploration and Semi-Automatic Tagging of Social Networks from Newspaper Articles
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Kochtchi, Artjom; Landesberger, Tatiana von; Biemann, Chris; H. Carr, P. Rheingans, and H. Schumann
Understanding relationships between people and organizations by reading newspaper articles is difficult to manage for humans due to the large amount of data. To address this problem, we present and evaluate a new visual analytics system, which offers interactive exploration and tagging of social networks extracted from newspapers. For the visual exploration of the network, we extract ''interesting'' neighbourhoods of nodes, using a new degree of interest (DOI) measure based on edges instead of nodes. It improves the seminal definition of DOI, which we find to produce the same ''globally interesting'' neighbourhoods in our use case, regardless of the query. Our approach allows answering different user queries appropriately, avoiding uniform search results. We propose a user-driven pattern-based classifier for discovery and tagging of non-taxonomic semantic relations. Our approach does not require any a-priori user knowledge, such as expertise in syntax or pattern creation. An evaluation shows that our classifier is capable of identifying known lexico-syntactic patterns as well as various domain-specific patters. Our classifier yields good results already with a small amount of training, and continuously improves through user feedback. We conduct a user study to evaluate whether our visual interactive system has an impact on how users tag relationships, as compared to traditional text-based interfaces. Study results suggest that users of the visual system tend to tag more concisely, avoiding too abstract or overly specific relationship labels.

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