34-Issue 3

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https://diglib.eg.org/handle/10.2312/12458

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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.
Feature-Driven Visual Analytics of Chaotic Parameter-Dependent Movement
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Luboschik, Martin; Röhlig, Martin; Bittig, Arne T.; Andrienko, Natalia; Schumann, Heidrun; Tominski, Christian; H. Carr, K.-L. Ma, and G. Santucci
Analyzing movements in their spatial and temporal context is a complex task. We are additionally interested in understanding the movements' dependency on parameters that govern the processes behind the movement. We propose a visual analytics approach combining analytic, visual, and interactive means to deal with the added complexity. The key idea is to perform an analytical extraction of features that capture distinct movement characteristics. Different parameter configurations and extracted features are then visualized in a compact fashion to facilitate an overview of the data. Interaction enables the user to access details about features, to compare features, and to relate features back to the original movement. We instantiate our approach with a repository of more than twenty accepted and novel features to help analysts in gaining insight into simulations of chaotic behavior of thousands of entities over thousands of data points. Domain experts applied our solution successfully to study dynamic groups in such movements in relation to thousands of parameter configurations.
Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Diehl, Alexandra; Pelorosso, Leandro; Delrieux, Claudio; Saulo, Celeste; Ruiz, Juan; Gröller, M. Eduard; Bruckner, Stefan; H. Carr, K.-L. Ma, and G. Santucci
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.
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.
Visualization of Particle-based Data with Transparency and Ambient Occlusion
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Staib, Joachim; Grottel, Sebastian; Gumhold, Stefan; H. Carr, K.-L. Ma, and G. Santucci
Particle-based simulation techniques, like the discrete element method or molecular dynamics, are widely used in many research fields. In real-time explorative visualization it is common to render the resulting data using opaque spherical glyphs with local lighting only. Due to massive overlaps, however, inner structures of the data are often occluded rendering visual analysis impossible. Furthermore, local lighting is not sufficient as several important features like complex shapes, holes, rifts or filaments cannot be perceived well. To address both problems we present a new technique that jointly supports transparency and ambient occlusion in a consistent illumination model. Our approach is based on the emission-absorption model of volume rendering. We provide analytic solutions to the volume rendering integral for several density distributions within a spherical glyph. Compared to constant transparency our approach preserves the three-dimensional impression of the glyphs much better. We approximate ambient illumination with a fast hierarchical voxel cone-tracing approach, which builds on a new real-time voxelization of the particle data. Our implementation achieves interactive frame rates for millions of static or dynamic particles without any preprocessing. We illustrate the merits of our method on real-world data sets gaining several new insights.
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.
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.
Mosaic Drawings and Cartograms
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Cano, Rafael G.; Buchin, Kevin; Castermans, Thom; Pieterse, Astrid; Sonke, Willem; Speckmann, Bettina; H. Carr, K.-L. Ma, and G. Santucci
Cartograms visualize quantitative data about a set of regions such as countries or states. There are several different types of cartograms and - for some - algorithms to automatically construct them exist. We focus on mosaic cartograms: cartograms that use multiples of simple tiles - usually squares or hexagons - to represent regions. Mosaic cartograms communicate well data that consist of, or can be cast into, small integer units (for example, electorial college votes). In addition, they allow users to accurately compare regions and can often maintain a (schematized) version of the input regions' shapes. We propose the first fully automated method to construct mosaic cartograms. To do so, we first introduce mosaic drawings of triangulated planar graphs. We then show how to modify mosaic drawings into mosaic cartograms with low cartographic error while maintaining correct adjacencies between regions. We validate our approach experimentally and compare to other cartogram methods.
Dual Adjacency Matrix: Exploring Link Groups in Dense Networks
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Dinkla, Kasper; Henry-Riche, Nathalie; Westenberg, Michel A.; H. Carr, K.-L. Ma, and G. Santucci
Node grouping is a common way of adding structure and information to networks that aids their interpretation. However, certain networks benefit from the grouping of links instead of nodes. Link communities, for example, are a form of link groups that describe high-quality overlapping node communities. There is a conceptual gap between node groups and link groups that poses an interesting visualization challenge. We introduce the Dual Adjacency Matrix to bridge this gap. This matrix combines node and link group techniques via a generalization that also enables it to be coordinated with a node-link-contour diagram. These methods have been implemented in a prototype that we evaluated with an information scientist and neuroscientist via interviews and prototype walk- throughs. We demonstrate this prototype with the analysis of a trade network and an fMRI correlation network.
Rationale Visualization for Safety and Security
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Scheepens, Roeland; Michels, Steffen; Wetering, Huub van de; Wijk, Jarke J. van; H. Carr, K.-L. Ma, and G. Santucci
In safety and security domains where objects of interest (OOI), such as people, vessels, or transactions, are continuously monitored, automated reasoning is required due to their sheer number and volume of information. We present a method to visually explain the rationale of a reasoning engine that raises an alarm if a certain situation is reached. Based both on evidence from heterogeneous and possibly unreliable sources, and on a domain specific reasoning structure, this engine concludes with a certain probability that, e.g., the OOI is suspected of smuggling. To support decision making, we visualize the rationale, an abstraction of the complicated reasoning structure. The evidence is displayed in a color-coded matrix that easily reveals if and where observations contradict. In it, domain and operational experts can quickly understand and find complicated patterns and relate them to real-world situations. Also, two groups of these experts evaluate our system through maritime use cases based on real data.
Visualnostics: Visual Guidance Pictograms for Analyzing Projections of High-dimensional Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Lehmann, Dirk J.; Kemmler, Fritz; Zhyhalava, Tatsiana; Kirschke, Marco; Theisel, Holger; H. Carr, K.-L. Ma, and G. Santucci
The visual analysis of multivariate projections is a challenging task, because complex visual structures occur. This causes fatigue or misinterpretations, which distorts the analysis. In fact, the same projection can lead to different analysis results. We provide visual guidance pictograms to improve objectivity of the visual search. A visual guidance pictogram is an iconic visual density map encoding the visual structure of certain data properties. By using them to guide the analysis, structures in the projection can be better understood and mentally linked to properties in the data. We introduce a systematic scheme for designing such pictograms and provide a set of pictograms for standard visual tasks, such as correlation and distribution analysis, for standard projections like scatterplots, RadVis, and Star Coordinates. We conduct a study that compares the visual analysis of real data with and without the support of guidance pictograms. Our tests show that the training effort for a visual search can be decreased and the analysis bias can be reduced by supporting the user's visual search with guidance pictograms.
Efficient Local Histogram Searching via Bitmap Indexing
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Wei, Tzu-Hsuan; Chen, Chun-Ming; Biswas, Ayan; H. Carr, K.-L. Ma, and G. Santucci
Representing features by local histograms is a proven technique in several volume analysis and visualization applications including feature tracking and transfer function design. The efficiency of these applications, however, is hampered by the high computational complexity of local histogram computation and matching. In this paper, we propose a novel algorithm to accelerate local histogram search by leveraging bitmap indexing. Our method avoids exhaustive searching of all voxels in the spatial domain by examining only the voxels whose values fall within the value range of user-defined local features and their neighborhood. Based on the idea that the value range of local features is in general much smaller than the dynamic range of the entire dataset, we propose a local voting scheme to construct the local histograms so that only a small number of voxels need to be examined. Experimental results show that our method can reduce much computational workload compared to the conventional approaches. To demonstrate the utility of our method, an interactive interface was developed to assist users in defining target features as local histograms and identify the locations of these features in the dataset.
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 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.
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.
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.

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