EuroVis15: Eurographics Conference on Visualization

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https://diglib.eg.org/handle/10.2312/13890

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Map-based Visualizations Increase Recall Accuracy of Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Saket, Bahador; Scheidegger, Carlos; Kobourov, Stephen G.; Börner, Katy; H. Carr, K.-L. Ma, and G. Santucci
We investigate the memorability of data represented in two different visualization designs. In contrast to recent studies that examine which types of visual information make visualizations memorable, we examine the effect of different visualizations on time and accuracy of recall of the displayed data, minutes and days after interaction with the visualizations. In particular, we describe the results of an evaluation comparing the memorability of two different visualizations of the same relational data: node-link diagrams and map-based visualization. We find significant differences in the accuracy of the tasks performed, and these differences persist days after the original exposure to the visualizations. Specifically, participants in the study recalled the data better when exposed to map-based visualizations as opposed to node-link diagrams. We discuss the scope of the study and its limitations, possible implications, and future directions.
Interactive Visual Analysis for Vehicle Detector Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Chen, Yi-Cheng; Wang, Yu-Shuen; Lin, Wen-Chieh; Huang, Wei-Xiang; Lin, I-Chen; H. Carr, K.-L. Ma, and G. Santucci
Visualization of vehicle detection (VD) data is essential because the data play an important role in traffic control and policy development. Most previous works focus on visualizing trajectories obtained from global positioning system (GPS), which are detailed but less representative. In contrast, VD data report the traffic statistic at each sensing site during a time span, including speed, flow, and occupancy of each lane, which contain comprehensive traffic information for analysis. In this work, we visualize three-year VD data of freeways in Taiwan. The visualization depicts the traffic situation at a site over time using a color-coded chart that extends from left to right over time. The charts are vertically stacked and horizontally aligned according to VD's located mileage and data time, respectively, to provide global insight. Our system allows semantic zoom, which changes the chart appearance in a continuous manner, to enable macro- and micro- scopic visualizations. Analysts can explore events that span an area with different sizes and that persist a time span with various lengths. To ensure the feasibility of our visualization, before the system design, we conducted a study with experts who work in the national freeway bureau and the institute of transportation of Taiwan. We also showed our results to the experts after the prototype system was built. The feedback shows that our VD data visualization is helpful to traffic control and policy development.
Compressive Volume Rendering
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Liu, Xiaoyang; Alim, Usman R.; H. Carr, K.-L. Ma, and G. Santucci
Compressive rendering refers to the process of reconstructing a full image from a small subset of the rendered pixels, thereby expediting the rendering task. In this paper, we empirically investigate three image order techniques for compressive rendering that are suitable for direct volume rendering. The first technique is based on the theory of compressed sensing and leverages the sparsity of the image gradient in the Fourier domain. The latter techniques exploit smoothness properties of the rendered image; the second technique recovers the missing pixels via a total variation minimization procedure while the third technique incorporates a smoothness prior in a variational reconstruction framework employing interpolating cubic B-splines. We compare and contrast the three techniques in terms of quality, efficiency and sensitivity to the distribution of pixels. Our results show that smoothness-based techniques significantly outperform techniques that are based on compressed sensing and are also robust in the presence of highly incomplete information. We achieve high quality recovery with as little as 20% of the pixels distributed uniformly in screen space.
Rule-Enhanced Transfer Function Generation for Medical Volume Visualization
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Cai, Li-Le; Nguyen, Binh P.; Chui, Chee-Kong; Ong, Sim-Heng; H. Carr, K.-L. Ma, and G. Santucci
In volume visualization, transfer functions are used to classify the volumetric data and assign optical properties to the voxels. In general, transfer functions are generated in a transfer function space, which is the feature space constructed by data values and properties derived from the data. If volumetric objects have the same or overlapping data values, it would be difficult to separate them in the transfer function space. In this paper, we present a rule-enhanced transfer function design method that allows important structures of the volume to be more effectively separated and highlighted. We define a set of rules based on the local frequency distribution of volume attributes. A rule-selection method based on a genetic algorithm is proposed to learn the set of rules that can distinguish the user-specified target tissue from other tissues. In the rendering stage, voxels satisfying these rules are rendered with higher opacities in order to highlight the target tissue. The proposed method was tested on various volumetric datasets to enhance the visualization of important structures that are difficult to be visualized by traditional transfer function design methods. The results demonstrate the effectiveness of the proposed method.
Evaluating 2D Flow Visualization Using Eye Tracking
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Ho, Hsin-Yang; Yeh, I-Cheng; Lai, Yu-Chi; Lin, Wen-Chieh; Cherng, Fu-Yin; H. Carr, K.-L. Ma, and G. Santucci
Flow visualization is recognized as an essential tool for many scientific research fields and different visualization approaches are proposed. Several studies are also conducted to evaluate their effectiveness but these studies rarely examine the performance from the perspective of visual perception. In this paper, we aim at exploring how users' visual perception is influenced by different 2D flow visualization methods. An eye tracker is used to analyze users' visual behaviors when they perform the free viewing, advection prediction, flow feature detection, and flow feature identification tasks on the flow field images generated by different visualizations methods. We evaluate the illustration capability of five representative visualization algorithms. Our results show that the eye-tracking-based evaluation provides more insights to quantitatively analyze the effectiveness of these visualization methods.
Visualizing Time-Specific Hurricane Predictions, with Uncertainty, from Storm Path Ensembles
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Liu, Le; Mirzargar, Mahsa; Kirby, Robert M.; Whitaker, Ross; House, Donald H.; H. Carr, K.-L. Ma, and G. Santucci
The U.S. National Hurricane Center (NHC) issues advisories every six hours during the life of a hurricane. These advisories describe the current state of the storm, and its predicted path, size, and wind speed over the next five days. However, from these data alone, the question ''What is the likelihood that the storm will hit Houston with hurricane strength winds between 12:00 and 14:00 on Saturday?'' cannot be directly answered. To address this issue, the NHC has recently begun making an ensemble of potential storm paths available as part of each storm advisory. Since each path is parameterized by time, predicted values such as wind speed associated with the path can be inferred for a specific time period by analyzing the statistics of the ensemble. This paper proposes an approach for generating smooth scalar fields from such a predicted storm path ensemble, allowing the user to examine the predicted state of the storm at any chosen time. As a demonstration task, we show how our approach can be used to support a visualization tool, allowing the user to display predicted storm position - including its uncertainty - at any time in the forecast. In our approach, we estimate the likelihood of hurricane risk for a fixed time at any geospatial location by interpolating simplicial depth values in the path ensemble. Adaptivelysized radial basis functions are used to carry out the interpolation. Finally, geometric fitting is used to produce a simple graphical visualization of this likelihood. We also employ a non-linear filter, in time, to assure frame-toframe coherency in the visualization as the prediction time is advanced. We explain the underlying algorithm and definitions, and give a number of examples of how our algorithm performs for several different storm predictions, and for two different sources of predicted path ensembles.
Learning Probabilistic Transfer Functions: A Comparative Study of Classifiers
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Soundararajan, Krishna Prasad; Schultz, Thomas; H. Carr, K.-L. Ma, and G. Santucci
Complex volume rendering tasks require high-dimensional transfer functions, which are notoriously difficult to design. One solution to this is to learn transfer functions from scribbles that the user places in the volumetric domain in an intuitive and natural manner. In this paper, we explicitly model and visualize the uncertainty in the resulting classification. To this end, we extend a previous intelligent system approach to volume rendering, and we systematically compare five supervised classification techniques - Gaussian Naive Bayes, k Nearest Neighbor, Support Vector Machines, Neural Networks, and Random Forests - with respect to probabilistic classification, support for multiple materials, interactive performance, robustness to unreliable input, and easy parameter tuning, which we identify as key requirements for the successful use in this application. Based on theoretical considerations, as well as quantitative and visual results on volume datasets from different sources and modalities, we conclude that, while no single classifier can be expected to outperform all others under all circumstances, random forests are a useful off-the-shelf technique that provides fast, easy, robust and accurate results in many scenarios.
Vector Field Visualization of Advective-Diffusive Flows
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Hochstetter, Hendrik; Wurm, Maximilian; Kolb, Andreas; H. Carr, K.-L. Ma, and G. Santucci
We propose a framework for unified visualization of advective and diffusive concentration fluxes, which play a key role in many phenomena like, e.g. Marangoni convection and microscopic mixing. The main idea is the decomposition of fluxes into their concentration and velocity parts. Using this flux decomposition, we are able to convey advective-diffusive concentration transport using integral lines. In order to visualize superimposed flux effects, we introduce a new graphical metaphor, the stream feather, which adds extensions to stream tubes pointing in the directions of deviating fluxes. The resulting unified visualization of macroscopic advection and microscopic diffusion allows for deeper insight into complex flow scenarios that cannot be achieved with current volume and surface rendering techniques alone. Our approach for flux decomposition and visualization of advective-diffusive flows can be applied to any kind of (simulation) data if velocity and concentration data are available. We demonstrate that our techniques can easily be integrated into Smoothed Particle Hydrodynamics (SPH) based simulations.
An Evaluation of the Impact of Visual Embellishments in Bar Charts
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Skau, Drew; Harrison, Lane; Kosara, Robert; H. Carr, K.-L. Ma, and G. Santucci
As data visualization becomes further intertwined with the field of graphic design and information graphics, small graphical alterations are made to many common chart formats. Despite the growing prevalence of these embellishments, their effects on communication of the charts' data is unknown. From an overview of the design space, we have outlined some of the common embellishments that are made to bar charts. We have studied the effects of these chart embellishments on the communication of the charts' data through a series of user studies on Amazon's Mechanical Turk platform. The results of these studies lead to a better understanding of how each chart type is perceived, and help provide guiding principles for the graphic design of charts.
VIMTEX: A Visualization Interface for Multivariate, Time-Varying, Geological Data Exploration
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Dasgupta, Aritra; Kosara, Robert; Gosink, Luke; H. Carr, K.-L. Ma, and G. Santucci
Observing interactions among chemical species and microorganisms in the earth's sub-surface is a common task in the field of geology. Bioremediation experiments constitute one such class of interactions which focus on getting rid of pollutants through processes such as carbon sequestration. The main goal of scientists' observations is to analyze the dynamics of the chemical reactions and understand how they collectively affect the carbon content of the soil. In our work, we extract the high-level goals of geologists and propose a visual analytics solution which helps scientists in deriving insights about multivariate, temporal behavior of these chemical species. Specifically, our key contributions are the following: i) characterization of the domain-specific goals and their translation to exploratory data analysis tasks, ii) developing an analytical abstraction in the form of perceptually motivated screen-space metrics for bridging the gap between the tasks and the visualization, and iii) realization of the tasks and metrics in the form of VIMTEX, which is a set of coordinated multiple views for letting scientists observe multivariate, temporal relationships in the data. We provide several examples and case studies along with expert feedback for demonstrating the efficacy of our solution.
Fiber Surfaces: Generalizing Isosurfaces to Bivariate Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Carr, Hamish; Geng, Zhao; Tierny, Julien; Chattopadhyay, Amit; Knoll, Aaron; H. Carr, K.-L. Ma, and G. Santucci
Scientific visualization has many effective methods for examining and exploring scalar and vector fields, but rather fewer for bivariate fields. We report the first general purpose approach for the interactive extraction of geometric separating surfaces in bivariate fields. This method is based on fiber surfaces: surfaces constructed from sets of fibers, the multivariate analogues of isolines. We show simple methods for fiber surface definition and extraction. In particular, we show a simple and efficient fiber surface extraction algorithm based on Marching Cubes. We also show how to construct fiber surfaces interactively with geometric primitives in the range of the function. We then extend this to build user interfaces that generate parameterized families of fiber surfaces with respect to arbitrary polygons. In the special case of isovalue-gradient plots, fiber surfaces capture features geometrically for quantitative analysis that have previously only been analysed visually and qualitatively using multi-dimensional transfer functions in volume rendering. We also demonstrate fiber surface extraction on a variety of bivariate data.
Perfopticon: Visual Query Analysis for Distributed Databases
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Moritz, Dominik; Halperin, Daniel; Howe, Bill; Heer, Jeffrey; H. Carr, K.-L. Ma, and G. Santucci
Distributed database performance is often unpredictable due to issues such as system complexity, network congestion, or imbalanced data distribution. These issues are difficult for users to assess in part due to the opaque mapping between declaratively specified queries and actual physical execution plans. Database developers currently must expend significant time and effort scanning log files to isolate and debug the root causes of performance issues. In response, we present Perfopticon, an interactive query profiling tool that enables rapid insight into common problems such as performance bottlenecks and data skew. Perfopticon combines interactive visualizations of (1) query plans, (2) overall query execution, (3) data flow among servers, and (4) execution traces. These views coordinate multiple levels of abstraction to enable detection, isolation, and understanding of performance issues. We evaluate our design choices through engagements with system developers, scientists, and students. We demonstrate that Perfopticon enables performance debugging for real-world tasks.
Visual Analytics for the Exploration of Tumor Tissue Characterization
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Raidou, Renata Georgia; Heide, Uulke A. van der; Dinh, Cuong Viet; Ghobadi, Ghazaleh; Kallehauge, Jesper Follsted; Breeuwer, Marcel; Vilanova, Anna; H. Carr, K.-L. Ma, and G. Santucci
Tumors are heterogeneous tissues consisting of multiple regions with distinct characteristics. Characterization of these intra-tumor regions can improve patient diagnosis and enable a better targeted treatment. Ideally, tissue characterization could be performed non-invasively, using medical imaging data, to derive per voxel a number of features, indicative of tissue properties. However, the high dimensionality and complexity of this imaging-derived feature space is prohibiting for easy exploration and analysis - especially when clinical researchers require to associate observations from the feature space to other reference data, e.g., features derived from histopathological data. Currently, the exploratory approach used in clinical research consists of juxtaposing these data, visually comparing 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 visual analysis of the feature space of imaging-derived tissue characteristics and (2) knowledge discovery and hypothesis generation 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 the exploration and analysis of the local structure of the feature space, enabling linking to patient anatomy and clinical reference data. We performed an initial evaluation with ten clinical researchers. All participants agreed that, unlike current practice, the proposed visual tool enables them to identify, explore and analyze heterogeneous intra-tumor regions and particularly, to generate and confirm hypotheses, with respect to clinical reference data.
A Novel Framework for Visual Detection and Exploration of Performance Bottlenecks in Organic Photovoltaic Solar Cell Materials
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Aboulhassan, Amal; Baum, Daniel; Wodo, Olga; Ganapathysubramanian, Baskar; Amassian, Aram; Hadwiger, Markus; H. Carr, K.-L. Ma, and G. Santucci
Current characterization methods of the so-called Bulk Heterojunction (BHJ), which is the main material of Organic Photovoltaic (OPV) solar cells, are limited to the analysis of global fabrication parameters. This reduces the efficiency of the BHJ design process, since it misses critical information about the local performance bottlenecks in the morphology of the material. In this paper, we propose a novel framework that fills this gap through visual characterization and exploration of local structure-performance correlations. We also propose a formula that correlates the structural features with the performance bottlenecks. Since research into BHJ materials is highly multidisciplinary, our framework enables a visual feedback strategy that allows scientists to build intuition about the best choices of fabrication parameters. We evaluate the usefulness of our proposed system by obtaining new BHJ characterizations. Furthermore, we show that our approach could substantially reduce the turnaround time.
Visual Analysis of Proximal Temporal Relationships of Social and Communicative Behaviors
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Han, Yi; Rozga, Agata; Dimitrova, Nevena; Abowd, Gregory D.; Stasko, John; H. Carr, K.-L. Ma, and G. Santucci
Developmental psychology researchers examine the temporal relationships of social and communicative behaviors, such as how a child responds to a name call, to understand early typical and atypical development and to discover early signs of autism and developmental delay. These related behaviors occur together or within close temporal proximity, forming unique patterns and relationships of interest. However, the task of finding these early signs, which are in the form of atypical behavioral patterns, becomes more challenging when behaviors of multiple children at different ages need to be compared with each other in search of generalizable patterns. The ability to visually explore the temporal relationships of behaviors, including flexible redefinition of closeness, over multiple social interaction sessions with children of different ages, can make such knowledge extraction easier. We have designed a visualization tool called TipoVis that helps psychology researchers visually explore the temporal patterns of social and communicative behaviors. We present two case studies to show how TipoVis helped two researchers derive new understandings of their data.
Visualization of Object-Centered Vulnerability to Possible Flood Hazards
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Cornel, Daniel; Konev, Artem; Sadransky, Bernhard; Horvath, Zsolt; Gröller, Eduard; Waser, Jürgen; H. Carr, K.-L. Ma, and G. Santucci
As flood events tend to happen more frequently, there is a growing demand for understanding the vulnerability of infrastructure to flood-related hazards. Such demand exists both for flood management personnel and the general public. Modern software tools are capable of generating uncertainty-aware flood predictions. However, the information addressing individual objects is incomplete, scattered, and hard to extract. In this paper, we address vulnerability to flood-related hazards focusing on a specific building. Our approach is based on the automatic extraction of relevant information from a large collection of pre-simulated flooding events, called a scenario pool. From this pool, we generate uncertainty-aware visualizations conveying the vulnerability of the building of interest to different kinds of flooding events. On the one hand, we display the adverse effects of the disaster on a detailed level, ranging from damage inflicted on the building facades or cellars to the accessibility of the important infrastructure in the vicinity. On the other hand, we provide visual indications of the events to which the building of interest is vulnerable in particular. Our visual encodings are displayed in the context of urban 3D renderings to establish an intuitive relation between geospatial and abstract information. We combine all the visualizations in a lightweight interface that enables the user to study the impacts and vulnerabilities of interest and explore the scenarios of choice. We evaluate our solution with experts involved in flood management and public communication.
Uncovering Representative Groups in Multidimensional Projections
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Joia, Paulo; Petronetto, Fabiano; Nonato, Luis Gustavo; H. Carr, K.-L. Ma, and G. Santucci
Multidimensional projection-based visualization methods typically rely on clustering and attribute selection mechanisms to enable visual analysis of multidimensional data. Clustering is often employed to group similar instances according to their distance in the visual space. However, considering only distances in the visual space may be misleading due to projection errors as well as the lack of guarantees to ensure that distinct clusters contain instances with different content. Identifying clusters made up of a few elements is also an issue for most clustering methods. In this work we propose a novel multidimensional projection-based visualization technique that relies on representative instances to define clusters in the visual space. Representative instances are selected by a deterministic sampling scheme derived from matrix decomposition, which is sensitive to the variability of data while still been able to handle classes with a small number of instances. Moreover, the sampling mechanism can easily be adapted to select relevant attributes from each cluster. Therefore, our methodology unifies sampling, clustering, and feature selection in a simple framework. A comprehensive set of experiments validate our methodology, showing it outperforms most existing sampling and feature selection techniques. A case study shows the effectiveness of the proposed methodology as a visual data analysis tool.
Detangler: Visual Analytics for Multiplex Networks
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Renoust, Benjamin; Melancon, Guy; Munzner, Tamara; H. Carr, K.-L. Ma, and G. Santucci
A multiplex network has links of different types, allowing it to express many overlapping types of relationships. A core task in network analysis is to evaluate and understand group cohesion; that is, to explain why groups of elements belong together based on the underlying structure of the network. We present Detangler, a system that supports visual analysis of group cohesion in multiplex networks through dual linked views. These views feature new data abstractions derived from the original multiplex network: the substrate network and the catalyst network. We contribute two novel techniques that allow the user to analyze the complex structure of the multiplex network without the extreme visual clutter that would result from simply showing it directly. The harmonized layout visual encoding technique provides spatial stability between the substrate and catalyst views. The pivot brushing interaction technique supports linked highlighting between the views based on computations in the underlying multiplex network to leapfrog between subsets of catalysts and substrates. We present results from the motivating application domain of annotated news documents with a usage scenario and preliminary expert feedback. A second usage scenario presents group cohesion analysis of the social network of the early American independence movement.
Finite-Time Mass Separation for Comparative Visualizations of Inertial Particles
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Günther, Tobias; Theisel, Holger; H. Carr, K.-L. Ma, and G. Santucci
The visual analysis of flows with inertial particle trajectories is a challenging problem because time-dependent particle trajectories additionally depend on mass, which gives rise to an infinite number of possible trajectories passing through every point in space-time. This paper presents an approach to a comparative visualization of the inertial particles' separation behavior. For this, we define the Finite-Time Mass Separation (FTMS), a scalar field that measures at each point in the domain how quickly inertial particles separate that were released from the same location but with slightly different mass. Extracting and visualizing the mass that induces the largest separation provides a simplified view on the critical masses. By using complementary coordinated views, we additionally visualize corresponding inertial particle trajectories in space-time by integral curves and surfaces. For a quantitative analysis, we plot Euclidean and arc length-based distances to a reference particle over time, which allows to observe the temporal evolution of separation events. We demonstrate our approach on a number of analytic and one real-world unsteady 2D field.
Refinery: Visual Exploration of Large, Heterogeneous Networks through Associative Browsing
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Kairam, Sanjay; Henry-Riche, Nathalie; Drucker, Steven; Fernandez, Roland; Heer, Jeffrey; H. Carr, K.-L. Ma, and G. Santucci
Browsing is a fundamental aspect of exploratory information-seeking. Associative browsing represents a common and intuitive set of exploratory strategies in which users step iteratively from familiar to novel bits of information. In this paper, we examine associative browsing as a strategy for bottom-up exploration of large, heterogeneous networks. We present Refinery, an interactive visualization system informed by guidelines for associative browsing drawn from literature on exploratory information-seeking. These guidelines motivate Refinery's query model, which allows users to simply and expressively construct queries using heterogeneous sets of nodes. This system computes degree-of-interest scores for associated content using a fast, random-walk algorithm. Refinery visualizes query nodes within a subgraph of results, providing explanatory context, facilitating serendipitous discovery, and stimulating continued exploration. A study of 12 academic researchers using Refinery to browse publication data demonstrates how the system enables discovery of valuable new content, even within existing areas of expertise.

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