33-Issue 3

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https://diglib.eg.org/handle/10.2312/11785

EuroVis

2014: Eurographics Conference on Visualization

Co-located EuroVis Events:

History

since 2012: Eurographics Conference on Visualization
since 2008: Issue 3 of Computer Graphics Forum
since 1999: Joint Eurographics - IEEE TCVG Symposium on Visualization, ISSN 1727-5296

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Visual Multiplexing
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Chen, Min; Walton, Simon; Berger, Kai; Thiyagalingam, Jeyan; Duffy, Brian; Fang, Hui; Holloway, Cameron; Trefethen, Anne E.; H. Carr, P. Rheingans, and H. Schumann
The majority of display devices used in visualization are 2D displays. Inevitably, it is often necessary to overlay one piece of visual information on top of another, especially in applications such as multi-field visualization and geospatial information visualization. In this paper, we present a conceptual framework for studying the mechanisms for overlaying multiple pieces of visual information while allowing users to recover occluded information. We adopt the term 'multiplexing' from tele- and data communication to encompass all such overlapping mechanisms. We establish 10 categories of visual multiplexing mechanisms. We draw support evidence from both perception literature and existing works in visualization to support this conceptual framework. We examine the relationships between multiplexing and information theoretic measures. This new conceptual categorization provides the muchneeded theory of visualization with an integral component.
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.
Visual-interactive Exploration of Interesting Multivariate Relations in Mixed Research Data Sets
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Bernard, Jürgen; Steiger, Martin; Widmer, Sven; Lücke-Tieke, Hendrik; May, Thorsten; Kohlhammer, Jörn; H. Carr, P. Rheingans, and H. Schumann
The analysis of research data plays a key role in data-driven areas of science. Varieties of mixed research data sets exist and scientists aim to derive or validate hypotheses to find undiscovered knowledge. Many analysis techniques identify relations of an entire dataset only. This may level the characteristic behavior of different subgroups in the data. Like automatic subspace clustering, we aim at identifying interesting subgroups and attribute sets. We present a visual-interactive system that supports scientists to explore interesting relations between aggregated bins of multivariate attributes in mixed data sets. The abstraction of data to bins enables the application of statistical dependency tests as the measure of interestingness. An overview matrix view shows all attributes, ranked with respect to the interestingness of bins. Complementary, a node-link view reveals multivariate bin relations by positioning dependent bins close to each other. The system supports information drill-down based on both expert knowledge and algorithmic support. Finally, visual-interactive subset clustering assigns multivariate bin relations to groups. A list-based cluster result representation enables the scientist to communicate multivariate findings at a glance. We demonstrate the applicability of the system with two case studies from the earth observation domain and the prostate cancer research domain. In both cases, the system enabled us to identify the most interesting multivariate bin relations, to validate already published results, and, moreover, to discover unexpected relations.
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
Stability of Dissipation Elements: A Case Study in Combustion
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Gyulassy, Attila; Bremer, Peer-Timo; Grout, Ray; Kolla, Hemanth; Chen, Jacqueline; Pascucci, Valerio; H. Carr, P. Rheingans, and H. Schumann
Recently, dissipation elements have been gaining popularity as a mechanism for measurement of fundamental properties of turbulent flow, such as turbulence length scales and zonal partitioning. Dissipation elements segment a domain according to the source and destination of streamlines in the gradient flow field of a scalar function f :M!R. They have traditionally been computed by numerically integrating streamlines from the center of each voxel in the positive and negative gradient directions, and grouping those voxels whose streamlines terminate at the same extremal pair. We show that the same structures map well to combinatorial topology concepts developed recently in the visualization community. Namely, dissipation elements correspond to sets of cells of the Morse- Smale complex. The topology-based formulation enables a more exploratory analysis of the nature of dissipation elements, in particular, in understanding their stability with respect to small scale variations. We present two examples from combustion science that raise significant questions about the role of small scale perturbation and indeed the definition of dissipation elements themselves.
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.
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.
Evaluating the Impact of User Characteristics and Different Layouts on an Interactive Visualization for Decision Making
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Conati, Cristina; Carenini, Giuseppe; Hoque, Enamul; Steichen, Ben; Toker, Dereck; H. Carr, P. Rheingans, and H. Schumann
There is increasing evidence that user characteristics can have a significant impact on visualization effectiveness, suggesting that visualizations could be designed to better fit each user's specific needs. Most studies to date, how-ever, have looked at static visualizations. Studies considering interactive visualizations have only looked at a li-mited number of user characteristics, and consider either low-level tasks (e.g., value retrieval), or high-level tasks (in particular: discovery), but not both. This paper contributes to this line of work by looking at the impact of a large set of user characteristics on user performance with interactive visualizations, for both low and high-level tasks. We focus on interactive visualizations that support decision making, exemplified by a visualization known as Value Charts. We include in the study two versions of ValueCharts that differ in terms of layout, to ascertain whether layout mediates the impact of individual differences and could be considered as a form of personalization. Our key findings are that (i) performance with low and high-level tasks is affected by different user characteristics, and (ii) users with low visual working memory perform better with a horizontal layout. We discuss how these find-ings can inform the provision of personalized support to visualization processing.
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.
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.
Methods for Compensating Contrast Effects in Information Visualization
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Mittelstädt, Sebastian; Stoffel, Andreas; Keim, Daniel A.; H. Carr, P. Rheingans, and H. Schumann
Color, as one of the most effective visual variables, is used in many techniques to encode and group data points according to different features. Relations between features and groups appear as visual patterns in the visualization. However, optical illusions may bias the perception at the first level of the analysis process. For instance, in pixel-based visualizations contrast effects make pixels appear brighter if surrounded by a darker area, which distorts the encoded metric quantity of the data points. Even if we are aware of these perceptual issues, our visual cognition system is not able to compensate these effects accurately. To overcome this limitation, we present a color optimization algorithm based on perceptual metrics and color perception models to reduce physiological contrast or color effects. We evaluate our technique with a user study and find that the technique doubles the accuracy of users comparing and estimating color encoded data values. Since the presented technique can be used in any application without adaption to the visualization itself, we are able to demonstrate its effectiveness on data visualizations in different domains.
Glyphs for Exploring Crowd-sourced Subjective Survey Classification
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Kachkaev, Alex; Wood, Jo; Dykes, Jason; H. Carr, P. Rheingans, and H. Schumann
The findings drawn from opinion survey responses are usually made by producing summary charts or conducting statistical analysis. Both involve data aggregation and filtering as exploring the unaggregated data has traditionally been impractical or error-prone for large numbers of responses. We propose the use of glyphs with parallel coordinate plots to show all survey responses in a single view and design an interactive visual analytics tool around the representation to explore the data. We use this software for a 'photo content assessment' survey, where 359 participants classify 900 images by seven criteria. The proposed approach allows all 8,434 responses (49,285 answers to questions in total) to be represented in a single view and helps analysts to both clean the data and understand the nature of the survey responses. We describe the construction of the survey response glyphs and the interface to the interactive visual analytics software and generalise the design principles that arise from the approach. We apply the tool to two other datasets to evaluate the technique and to confirm its wider applicability for surveys with Likert scale responses.
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.
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.
LoVis: Local Pattern Visualization for Model Refinement
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Zhao, Kaiyu; Ward, Matthew O.; Rundensteiner, Elke A.; Higgins, Huong N.; H. Carr, P. Rheingans, and H. Schumann
Linear models are commonly used to identify trends in data. While it is an easy task to build linear models using pre-selected variables, it is challenging to select the best variables from a large number of alternatives. Most metrics for selecting variables are global in nature, and thus not useful for identifying local patterns. In this work, we present an integrated framework with visual representations that allows the user to incrementally build and verify models in three model spaces that support local pattern discovery and summarization: model complementarity, model diversity, and model representivity. Visual representations are designed and implemented for each of the model spaces. Our visualizations enable the discovery of complementary variables, i.e., those that perform well in modeling different subsets of data points. They also support the isolation of local models based on a diversity measure. Furthermore, the system integrates a hierarchical representation to identify the outlier local trends and the local trends that share similar directions in the model space. A case study on financial risk analysis is discussed, followed by a user study.
Mandatory Critical Points of 2D Uncertain Scalar Fields
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Günther, David; Salmon, Joseph; Tierny, Julien; H. Carr, P. Rheingans, and H. Schumann
This paper introduces a novel, non-local characterization of critical points and their global relation in 2D uncertain scalar fields. The characterization is based on the analysis of the support of the probability density functions (PDF) of the input data. Given two scalar fields representing reliable estimations of the bounds of this support, our strategy identifies mandatory critical points: spatial regions and function ranges where critical points have to occur in any realization of the input. The algorithm provides a global pairing scheme for mandatory critical points which is used to construct mandatory join and split trees. These trees enable a visual exploration of the common topological structure of all possible realizations of the uncertain data. To allow multi-scale visualization, we introduce a simplification scheme for mandatory critical point pairs revealing the most dominant features. Our technique is purely combinatorial and handles parametric distribution models and ensemble data. It does not depend on any computational parameter and does not suffer from numerical inaccuracy or global inconsistency. The algorithm exploits ideas of the established join/split tree computation. It is therefore simple to implement, and its complexity is output-sensitive. We illustrate, evaluate, and verify our method on synthetic and real-world data.
Lyra: An Interactive Visualization Design Environment
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Satyanarayan, Arvind; Heer, Jeffrey; H. Carr, P. Rheingans, and H. Schumann
We present Lyra, an interactive environment for designing customized visualizations without writing code. Using drag-and-drop interactions, designers can bind data to the properties of graphical marks to author expressive visualization designs. Marks can be moved, rotated and resized using handles; relatively positioned using connectors; and parameterized by data fields using property drop zones. Lyra also provides a data pipeline interface for iterative, visual specification of data transformations and layout algorithms. Visualizations created with Lyra are represented as specifications in Vega, a declarative visualization grammar that enables sharing and reuse. We evaluate Lyra's expressivity and accessibility through diverse examples and studies with journalists and visualization designers. We find that Lyra enables users to rapidly develop customized visualizations, covering a design space comparable to existing programming-based tools.
Sparse Representation and Visualization for Direct Numerical Simulation of Premixed Combustion
(The Eurographics Association and John Wiley and Sons Ltd., 2014) Oster, Timo; Lehmann, Dirk J.; Frau, Gordon; Theisel, Holger; Thévenin, Dominique; H. Carr, P. Rheingans, and H. Schumann
Direct Numerical Simulations of premixed combustion produce terabytes of raw data, which are prohibitively large to be stored, and have to be analyzed and visualized. A simultaneous and integrated treatment of data storage, data analysis and data visualization is required. For this, we introduce a sparse representation tailored to DNS data which can directly be used for both analysis and visualization. The method is based on the observation that most information is located in narrow-band regions where the chemical reactions take place, but these regions are not well defined. An approach for the visual investigation of feature surfaces of the scalar fields involved in the simulation is shown as a possible application. We demonstrate our approach on multiple real datasets.
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.

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