EuroVis16: Eurographics Conference on Visualization

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https://diglib.eg.org/handle/10.2312/15437

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Arcs, Angles, or Areas: Individual Data Encodings in Pie and Donut Charts
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Skau, Drew; Kosara, Robert; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
Pie and donut charts have been a hotly debated topic in the visualization community for some time now. Even though pie charts have been around for over 200 years, our understanding of the perceptual factors used to read data in them is still limited. Data is encoded in pie and donut charts in three ways: arc length, center angle, and segment area. For our first study, we designed variations of pie charts to test the importance of individual encodings for reading accuracy. In our second study, we varied the inner radius of a donut chart from a filled pie to a thin outline to test the impact of removing the central angle. Both studies point to angle being the least important visual cue for both charts, and the donut chart being as accurate as the traditional pie chart.
AVOCADO: Visualization of Workflow-Derived Data Provenance for Reproducible Biomedical Research
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Stitz, Holger; Luger, Stefan; Streit, Marc; Gehlenborg, Nils; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
A major challenge in data-driven biomedical research lies in the collection and representation of data provenance information to ensure that findings are reproducibile. In order to communicate and reproduce multi-step analysis workflows executed on datasets that contain data for dozens or hundreds of samples, it is crucial to be able to visualize the provenance graph at different levels of aggregation. Most existing approaches are based on node-link diagrams, which do not scale to the complexity of typical data provenance graphs. In our proposed approach, we reduce the complexity of the graph using hierarchical and motif-based aggregation. Based on user action and graph attributes, a modular degree-of-interest (DoI) function is applied to expand parts of the graph that are relevant to the user. This interest-driven adaptive approach to provenance visualization allows users to review and communicate complex multi-step analyses, which can be based on hundreds of files that are processed by numerous workflows. We have integrated our approach into an analysis platform that captures extensive data provenance information, and demonstrate its effectiveness by means of a biomedical usage scenario.
BubbleNet: A Cyber Security Dashboard for Visualizing Patterns
(The Eurographics Association and John Wiley & Sons Ltd., 2016) McKenna, Sean; Staheli, Diane; Fulcher, Cody; Meyer, Miriah; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
The field of cyber security is faced with ever-expanding amounts of data and a constant barrage of cyber attacks. Within this space, we have designed BubbleNet as a cyber security dashboard to help network analysts identify and summarize patterns within the data. This design study faced a range of interesting constraints from limited time with various expert users and working with users beyond the network analyst, such as network managers. To overcome these constraints, the design study employed a user-centered design process and a variety of methods to incorporate user feedback throughout the design of BubbleNet. This approach resulted in a successfully evaluated dashboard with users and further deployments of these ideas in both research and operational environments. By explaining these methods and the process, it can benefit future visualization designers to help overcome similar challenges in cyber security or alternative domains.
Comparing Bar Chart Authoring with Microsoft Excel and Tangible Tiles
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Wun, Tiffany; Payne, Jennifer; Huron, Samuel; Carpendale, Sheelagh; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
Providing tools that make visualization authoring accessible to visualization non-experts is a major research challenge. Currently the most common approach to generating a visualization is to use software that quickly and automatically produces visualizations based on templates. However, it has recently been suggested that constructing a visualization with tangible tiles may be a more accessible method, especially for people without visualization expertise. There is still much to be learned about the differences between these two visualization authoring practices. To better understand how people author visualizations in these two conditions, we ran a qualitative study comparing the use of software to the use of tangible tiles, for the creation of bar charts. Close observation of authoring activities showed how each of the following varied according to the tool used: 1) sequences of action; 2) distribution of time spent on different aspects of the InfoVis pipeline; 3) pipeline task separation; and 4) freedom to manipulate visual variables. From these observations, we discuss the implications of the variations in activity sequences, noting tool design considerations and pointing to future research questions.
Comparing Node-Link and Node-Link-Group Visualizations From An Enjoyment Perspective
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Saket, Bahador; Scheidegger, Carlos; Kobourov, Stephen; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
While evaluation studies in visualization often involve traditional performance measurements, there has been a concerted effort to move beyond time and accuracy. Of these alternative aspects, memorability and recall of visualizations have been recently considered, but other aspects such as enjoyment and engagement are not as well explored. We study the enjoyment of two different visualization methods through a user study. In particular, we describe the results of a three-phase experiment comparing the enjoyment of two different visualizations of the same relational data: node-link and node-link-group visualizations. The results indicate that the participants in this study found node-link-group visualizations more enjoyable than node-link visualizations.
Composite Flow Maps
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Cornel, Daniel; Konev, Artem; Sadransky, Bernhard; Horváth, Zsolt; Brambilla, Andrea; Viola, Ivan; Waser, Jürgen; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
Flow maps are widely used to provide an overview of geospatial transportation data. Existing solutions lack the support for the interactive exploration of multiple flow components at once. Flow components are given by different materials being transported, different flow directions, or by the need for comparing alternative scenarios. In this paper, we combine flows as individual ribbons in one composite flow map. The presented approach can handle an arbitrary number of sources and sinks. To avoid visual clutter, we simplify our flow maps based on a force-driven algorithm, accounting for restrictions with respect to application semantics. The goal is to preserve important characteristics of the geospatial context. This feature also enables us to highlight relevant spatial information on top of the flow map such as traffic conditions or accessibility. The flow map is computed on the basis of flows between zones. We describe a method for auto-deriving zones from geospatial data according to application requirements. We demonstrate the method in real-world applications, including transportation logistics, evacuation procedures, and water simulation. Our results are evaluated with experts from corresponding fields.
ConToVi: Multi-Party Conversation Exploration using Topic-Space Views
(The Eurographics Association and John Wiley & Sons Ltd., 2016) El-Assady, Mennatallah; Gold, Valentin; Acevedo, Carmela; Collins, Christopher; Keim, Daniel; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
We introduce a novel visual analytics approach to analyze speaker behavior patterns in multi-party conversations. We propose Topic-Space Views to track the movement of speakers across the thematic landscape of a conversation. Our tool is designed to assist political science scholars in exploring the dynamics of a conversation over time to generate and prove hypotheses about speaker interactions and behavior patterns. Moreover, we introduce a glyph-based representation for each speaker turn based on linguistic and statistical cues to abstract relevant text features. We present animated views for exploring the general behavior and interactions of speakers over time and interactive steady visualizations for the detailed analysis of a selection of speakers. Using a visual sedimentation metaphor we enable the analysts to track subtle changes in the flow of a conversation over time while keeping an overview of all past speaker turns. We evaluate our approach on real-world datasets and the results have been insightful to our domain experts.
Critical Points of Gaussian-Distributed Scalar Fields on Simplicial Grids
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Liebmann, Tom; Scheuermann, Gerik; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
Simulations and measurements often result in scalar fields with uncertainty due to errors or output sensitivity estimates. Methods for analyzing topological features of such fields usually are not capable of handling all aspects of the data. They either are not deterministic due to using Monte Carlo approaches, approximate the data with confidence intervals, or miss out on incorporating important properties, such as correlation. In this paper, we focus on the analysis of critical points of Gaussiandistributed scalar fields. We introduce methods to deterministically extract critical points, approximate their probability with high precision, and even capture relations between them resulting in an abstract graph representation. Unlike many other methods, we incorporate all information contained in the data including global correlation. Our work therefore is a first step towards a reliable and complete description of topological features of Gaussian-distributed scalar fields.
Cytosplore: Interactive Immune Cell Phenotyping for Large Single-Cell Datasets
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Höllt, Thomas; Pezzotti, Nicola; Unen, Vincent van; Koning, Frits; Eisemann, Elmar; Lelieveldt, Boudewijn P. F.; Vilanova, Anna; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single-cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high-dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation.
Decoupled Shading for Real-time Heterogeneous Volume Illumination
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Zhang, Yubo; Ma, Kwan-Liu; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
Existing real-time volume rendering techniques which support global illumination are limited in modeling distinct realistic appearances for classified volume data, which is a desired capability in many fields of study for illustration and education. Directly extending the emission-absorption volume integral with heterogeneous material shading becomes unaffordable for real-time applications because the high-frequency view-dependent global lighting needs to be evaluated per sample along the volume integral. In this paper, we present a decoupled shading algorithm for multi-material volume rendering that separates global incident lighting evaluation from per-sample material shading under multiple light sources. We show how the incident lighting calculation can be optimized through a sparse volume integration method. The quality, performance and usefulness of our new multi-material volume rendering method is demonstrated through several examples.
Designing Multiple Coordinated Visualizations for Tablets
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Sadana, Ramik; Stasko, John; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
The use of multiple coordinated views (MCV) in data visualization provides analytic power because it allows a person to explore data under a variety of different perspectives. Since this design pattern utilizes multiple visualizations and requires coordinated interactions across the views, a clever use of screen space is vital and many synchronized interface operations must be provided. Bringing this design pattern to tablet computers is challenging due to their small display size and the absence of keyboard and mouse input. In this article, we explain important design considerations for MCV visualization on tablets and describe a prototype MCV visualization system we have built for the iPad. The design is based on the principles of maximizing screen space for data presentation, promoting consistent interactions across visualizations, and minimizing occlusion from a person's hands.
Dynamic Change Arcs to Explore Model Forecasts
(The Eurographics Association and John Wiley & Sons Ltd., 2016) St. Jean, Carmen; Ware, Colin; Gamble, Robert; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
In many planning applications, a computational model is used to make predictions about the effects of management or engineering decisions. To understand the implications of alternative scenarios, a user typically adjusts one or more of the input parameters, runs the model, and examines the outcomes using simple charts. For example, a time series showing changes in productivity or revenue might be generated. While this approach can be effective in showing the projected effects of changes to the model's input parameters, it fails to show the mechanisms that cause those changes. In order to promote understanding of model mechanics using a simple graphical device, we propose dynamic change arcs. Dynamic change arcs graphically reveal the internal model structure as cause and effect linkages. They are signed to show both positive and negative effects. We implemented this concept using a species interaction model developed for fisheries management based on a system of Lotka-Volterra equations. The model has 10 economically important fish species and incorporates both predation and competition between species. The model predicts that changing the catch of one species can sometimes result in changes in biomass of another species through multi-step causal chains. The dynamic change arcs make it possible to interpret the resulting complex causal chains and interaction effects. We carried out an experiment to evaluate three alternative forms of arcs for portraying causal connections in the model. The results show that all linkage representations enabled participants to reason better about complex chains of causality than not showing linkages. However, none of them were significantly better than the others.
Enhancing Scatterplots with Multi-Dimensional Focal Blur
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Staib, Joachim; Grottel, Sebastian; Gumhold, Stefan; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
Scatterplots directly depict two dimensions of multi-dimensional data points, discarding all other information. To visualize all data, these plots are extended to scatterplot matrices, which distribute the information of each data point over many plots. Problems arising from the resulting visual complexity are nowadays alleviated by concepts like filtering and focus and context. We present a method based on depth of field that contains both aspects and injects information from all dimensions into each scatterplot. Our approach is a natural generalization of the commonly known focus effects from optics. It is based on a multidimensional focus selection body. Points outside of this body are defocused depending on their distance. Our method allows for a continuous transition from data points in focus, over regions of blurry points providing contextual information, to visually filtered data. Our algorithm supports different focus selection bodies, blur kernels, and point shapes. We present an optimized GPU-based implementation for interactive exploration and show the usefulness of our approach on several data sets.
EuroVis 2016: Frontmatter
(Eurographics Association, 2016) Kwan-Liu Ma; Giuseppe Santucci; Jarke van Wijk;
Evaluating Viewpoint Entropy for Ribbon Representation of Protein Structure
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Heinrich, Julian; Vuong, Jenny; Hammang, Christopher J.; Wu, Andrew; Rittenbruch, Markus; Hogan, Jim; Brereton, Margot; O'Donoghue, Sean I.; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
While many measures of viewpoint goodness have been proposed in computer graphics, none have been evaluated for ribbon representations of protein secondary structure. To fill this gap, we conducted a user study on Amazon's Mechanical Turk platform, collecting human viewpoint preferences from 65 participants for 4 representative superfamilies of protein domains. In particular, we evaluated viewpoint entropy, which was previously shown to be a good predictor for human viewpoint preference of other, mostly non-abstract objects. In a second study, we asked 7 experts in molecular biology to find the best viewpoint of the same protein domains and compared their choices with viewpoint entropy. Our results indicate that viewpoint entropy overall is a significant predictor of human viewpoint preference for ribbon representations of protein secondary structure. However, the accuracy depends on the type and composition of the structure: while most participants agree on good viewpoints for structures with mainly beta sheets, viewpoint preference varies considerably for complex arrangements of alpha helices. Finally, experts tend to choose viewpoints of both low and high viewpoint entropy to emphasize different aspects of the respective structure.
Exploratory Visual Analysis for Animal Movement Ecology
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Slingsby, Aidan; Loon, Emiel van; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
Movement ecologists study animals' movement to help understand their behaviours and interactions with each other and the environment. Data from GPS loggers are increasingly important for this. These data need to be processed, segmented and summarised for further visual and statistical analysis, often using predefined parameters. Usually, this process is separate from the subsequent visual and statistical analysis, making it difficult for these results to inform the data processing and to help set appropriate scale and thresholds parameters. This paper explores the use of highly interactive visual analytics techniques to close the gap between processing raw data and exploratory visual analysis. Working closely with animal movement ecologists, we produced requirements to enable data characteristics to be determined, initial research questions to be investigated, and the suitability of data for further analysis to be assessed. We design visual encodings and interactions to meet these requirements and provide software that implements them. We demonstrate these techniques with indicative research questions for a number of bird species, provide software, and discuss wider implications for animal movement ecology.
Exploring and Comparing Clusterings of Multivariate Data Sets Using Persistent Homology
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Rieck, Bastian; Leitte, Heike; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
Clustering algorithms support exploratory data analysis by grouping inputs that share similar features. Especially the clustering of unlabelled data is said to be a fiendishly difficult problem, because users not only have to choose a suitable clustering algorithm but also a suitable number of clusters. The known issues of existing clustering validity measures comprise instabilities in the presence of noise and restrictive assumptions about cluster shapes. In addition, they cannot evaluate individual clusters locally. We present a new measure for assessing and comparing different clusterings both on a global and on a local level. Our measure is based on the topological method of persistent homology, which is stable and unbiased towards cluster shapes. Based on our measure, we also describe a new visualization that displays similarities between different clusterings (using a global graph view) and supports their comparison on the individual cluster level (using a local glyph view). We demonstrate how our visualization helps detect different—-but equally valid-clusterings of data sets from multiple application domains.
Exploring Items and Features with IF,FI-Tables
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Corput, Paul van der; Wijk, Jarke J. van; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
The exploration of high-dimensional data is challenging because humans have difficulty to understand more than three dimensions. We present a new visualization concept that enables users to explore such data and, specifically, to learn about important items and features that are unknown or overlooked, based on the items and features that are already known. The visualization consists of two juxtaposed tables: an IF-Table, showing all items with a selection of features; and an FI-Table, showing all features with a selection of items. This enables the user to limit the number of visible items and features to those needed for the exploration. The interaction is kept simple: each selection of items and features results in a complete overview of similar and relevant items and features.
Faceted Views of Varying Emphasis (FaVVEs): a Framework for Visualising Multi-perspective Small Multiples
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Beecham, Roger; Rooney, Chris; Meier, Sebastian; Dykes, Jason; Slingsby, Aidan; Turkay, Cagatay; Wood, Jo; Wong, B. L. William; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
Many datasets have multiple perspectives - for example space, time and description - and often analysts are required to study these multiple perspectives concurrently. This concurrent analysis becomes difficult when data are grouped and split into small multiples for comparison. A design challenge is thus to provide representations that enable multiple perspectives, split into small multiples, to be viewed simultaneously in ways that neither clutter nor overload. We present a design framework that allows us to do this. We claim that multi-perspective comparison across small multiples may be possible by superimposing perspectives on one another rather than juxtaposing those perspectives side-by-side. This approach defies conventional wisdom and likely results in visual and informational clutter. For this reason we propose designs at three levels of abstraction for each perspective. By flexibly varying the abstraction level, certain perspectives can be brought into, or out of, focus. We evaluate our framework through laboratory-style user tests. We find that superimposing, rather than juxtaposing, perspective views has little effect on performance of a low-level comparison task. We reflect on the user study and its design to further identify analysis situations for which our framework may be desirable. Although the user study findings were insufficiently discriminating, we believe our framework opens up a new design space for multi-perspective visual analysis.
From Visual Exploration to Storytelling and Back Again
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Gratzl, Samuel; Lex, Alexander; Gehlenborg, Nils; Cosgrove, Nicola; Streit, Marc; Kwan-Liu Ma and Giuseppe Santucci and Jarke van Wijk
The primary goal of visual data exploration tools is to enable the discovery of new insights. To justify and reproduce insights, the discovery process needs to be documented and communicated. A common approach to documenting and presenting findings is to capture visualizations as images or videos. Images, however, are insufficient for telling the story of a visual discovery, as they lack full provenance information and context. Videos are difficult to produce and edit, particularly due to the non-linear nature of the exploratory process. Most importantly, however, neither approach provides the opportunity to return to any point in the exploration in order to review the state of the visualization in detail or to conduct additional analyses. In this paper we present CLUE (Capture, Label, Understand, Explain), a model that tightly integrates data exploration and presentation of discoveries. Based on provenance data captured during the exploration process, users can extract key steps, add annotations, and author ''Vistories'', visual stories based on the history of the exploration. These Vistories can be shared for others to view, but also to retrace and extend the original analysis. We discuss how the CLUE approach can be integrated into visualization tools and provide a prototype implementation. Finally, we demonstrate the general applicability of the model in two usage scenarios: a Gapminder-inspired visualization to explore public health data and an example from molecular biology that illustrates how Vistories could be used in scientific journals.

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