38-Issue 3

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https://diglib.eg.org/handle/10.2312/2632780

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Examining Implicit Discretization in Spectral Schemes
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Quinan, P. Samuel; Padilla, Lace M. K.; Creem-Regehr, Sarah H.; Meyer, Miriah; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Two of the primary reasons rainbow color maps are considered ineffective trace back to the idea that they implicitly discretize encoded data into hue-based bands, yet no research addresses what this discretization looks like or how consistent it is across individuals. This paper presents an exploratory study designed to empirically investigate the implicit discretization of common spectral schemes and explore whether the phenomenon can be modeled by variations in lightness, chroma, and hue. Our results suggest that three commonly used rainbow color maps are implicitly discretized with consistency across individuals. The results also indicate, however, that this implicit discretization varies across different datasets, in a way that suggests the visualization community's understanding of both rainbow color maps, and more generally effective color usage, remains incomplete.
Visualization Support for Developing a Matrix Calculus Algorithm: A Case Study
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Giesen, Joachim; Klaus, Julien; Laue, Sören; Schreck, Ferdinand; Gleicher, Michael and Viola, Ivan and Leitte, Heike
The development of custom interactive visualization tools for specific domains and applications has been made much simpler recently by a surge of visualization tools, libraries and frameworks. Most of these tools are developed for classical data science applications, where a user is supported in analyzing measured or simulated data. But recently, there has also been an increasing interest in visual support for understanding machine learning algorithms and frameworks, especially for deep learning. Many, if not most, of the visualization support for (deep) learning addresses the developer of the learning system and not the end user (data scientist). Here we show on a specific example, namely the development of a matrix calculus algorithm, that supporting visualizations can also greatly benefit the development of algorithms in classical domains like in our case computer algebra. The idea is similar to visually supporting the understanding of learning algorithms, namely provide the developer with an interactive, visual tool that provides insights into the workings and, importantly, also into the failures of the algorithm under development. Developing visualization support for matrix calculus development went similar as the development of more traditional visual support systems for data analysts. First, we had to acquaint ourselves with the problem, its language and challenges by talking to the core developer of the matrix calculus algorithm. Once we understood the challenge, it was fairly easy to develop visual support that streamlined the development of the matrix calculus algorithm significantly.
Augmenting Tactile 3D Data Navigation With Pressure Sensing
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Wang, Xiyao; Besançon, Lonni; Ammi, Mehdi; Isenberg, Tobias; Gleicher, Michael and Viola, Ivan and Leitte, Heike
We present a pressure-augmented tactile 3D data navigation technique, specifically designed for small devices, motivated by the need to support the interactive visualization beyond traditional workstations. While touch input has been studied extensively on large screens, current techniques do not scale to small and portable devices. We use phone-based pressure sensing with a binary mapping to separate interaction degrees of freedom (DOF) and thus allow users to easily select different manipulation schemes (e. g., users first perform only rotation and then with a simple pressure input to switch to translation). We compare our technique to traditional 3D-RST (rotation, scaling, translation) using a docking task in a controlled experiment. The results show that our technique increases the accuracy of interaction, with limited impact on speed. We discuss the implications for 3D interaction design and verify that our results extend to older devices with pseudo pressure and are valid in realistic phone usage scenarios.
Bird's-Eye - Large-Scale Visual Analytics of City Dynamics using Social Location Data
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Krueger, Robert; Han, Qi; Ivanov, Nikolay; Mahtal, Sanae; Thom, Dennis; Pfister, Hanspeter; Ertl, Thomas; Gleicher, Michael and Viola, Ivan and Leitte, Heike
The analysis of behavioral city dynamics, such as temporal patterns of visited places and citizens' mobility routines, is an essential task for urban and transportation planning. Social media applications such as Foursquare and Twitter provide access to large-scale and up-to-date dynamic movement data that not only help to understand the social life and pulse of a city but also to maintain and improve urban infrastructure. However, the fast growth rate of this data poses challenges for conventional methods to provide up-to-date, flexible analysis. Therefore, planning authorities barely consider it. We present a system and design study to leverage social media data that assist urban and transportation planners to achieve better monitoring and analysis of city dynamics such as visited places and mobility patterns in large metropolitan areas. We conducted a goal-and-task analysis with urban planning experts. To address these goals, we designed a system with a scalable data monitoring back-end and an interactive visual analytics interface. The monitoring component uses intelligent pre-aggregation to allow dynamic queries in near real-time. The visual analytics interface leverages unsupervised learning to reveal clusters, routines, and unusual behavior in massive data, allowing to understand patterns in time and space. We evaluated our approach based on a qualitative user study with urban planning experts which demonstrates that intuitive integration of advanced analytical tools with visual interfaces is pivotal in making behavioral city dynamics accessible to practitioners. Our interviews also revealed areas for future research.
An Exploratory User Study of Visual Causality Analysis
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Yen, Chi-Hsien Eric; Parameswaran, Aditya; Fu, Wai-Tat; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Interactive visualization tools are being used by an increasing number of members of the general public; however, little is known about how, and how well, people use visualizations to infer causality. Adapted from the mediation causal model, we designed an analytic framework to systematically evaluate human performance, strategies, and pitfalls in a visual causal reasoning task. We recruited 24 participants and asked them to identify the mediators in a fictitious dataset using bar charts and scatter plots within our visualization interface. The results showed that the accuracy of their responses as to whether a variable is a mediator significantly decreased when a confounding variable directly influenced the variable being analyzed. Further analysis demonstrated how individual visualization exploration strategies and interfaces might influence reasoning performance. We also identified common strategies and pitfalls in their causal reasoning processes. Design implications for how future visual analytics tools can be designed to better support causal inference are discussed.
Hybrid Touch/Tangible Spatial 3D Data Selection
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Besançon, Lonni; Sereno, Mickael; Yu, Lingyun; Ammi, Mehdi; Isenberg, Tobias; Gleicher, Michael and Viola, Ivan and Leitte, Heike
We discuss spatial selection techniques for three-dimensional datasets. Such 3D spatial selection is fundamental to exploratory data analysis. While 2D selection is efficient for datasets with explicit shapes and structures, it is less efficient for data without such properties. We first propose a new taxonomy of 3D selection techniques, focusing on the amount of control the user has to define the selection volume. We then describe the 3D spatial selection technique Tangible Brush, which gives manual control over the final selection volume. It combines 2D touch with 6-DOF 3D tangible input to allow users to perform 3D selections in volumetric data. We use touch input to draw a 2D lasso, extruding it to a 3D selection volume based on the motion of a tangible, spatially-aware tablet. We describe our approach and present its quantitative and qualitative comparison to state-of-the-art structure-dependent selection. Our results show that, in addition to being dataset-independent, Tangible Brush is more accurate than existing dataset-dependent techniques, thus providing a trade-off between precision and effort.
Designing Animated Transitions to Convey Aggregate Operations
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Kim, Younghoon; Correll, Michael; Heer, Jeffrey; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Data can be aggregated in many ways before being visualized in charts, profoundly affecting what a chart conveys. Despite this importance, the type of aggregation is often communicated only via axis titles. In this paper, we investigate the use of animation to disambiguate different types of aggregation and communicate the meaning of aggregate operations. We present design rationales for animated transitions depicting aggregate operations and present the results of an experiment assessing the impact of these different transitions on identification tasks. We find that judiciously staged animated transitions can improve subjects' accuracy at identifying the aggregation performed, though sometimes with longer response times than with static transitions. Through an analysis of participants' rankings and qualitative responses, we find a consistent preference for animation over static transitions and highlight visual features subjects report relying on to make their judgments. We conclude by extending our animation designs to more complex charts of aggregated data such as box plots and bootstrapped confidence intervals.
Analysis of Decadal Climate Predictions with User-guided Hierarchical Ensemble Clustering
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Kappe, Christopher; Böttinger, Michael; Leitte, Heike; Gleicher, Michael and Viola, Ivan and Leitte, Heike
In order to gain probabilistic results, ensemble simulation techniques are increasingly applied in the weather and climate sciences (as well as in various other scientific disciplines). In many cases, however, only mean results or other abstracted quantities such as percentiles are used for further analyses and dissemination of the data. In this work, we aim at a more detailed visualization of the temporal development of the whole ensemble that takes the variability of all single members into account. We propose a visual analytics tool that allows an effective analysis process based on a hierarchical clustering of the time-dependent scalar fields. The system includes a flow chart that shows the ensemble members' cluster affiliation over time, reflecting the whole cluster hierarchy. The latter one can be dynamically explored using a visualization derived from a dendrogram. As an aid in linking the different views, we have developed an adaptive coloring scheme that takes into account cluster similarity and the containment relationships. Finally, standard visualizations of the involved field data (cluster means, ground truth data, etc.) are also incorporated. We include results of our work on real-world datasets to showcase the utility of our approach.
Visualization of Equivalence in 2D Bivariate Fields
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Zheng, Boyan; Rieck, Bastian; Leitte, Heike; Sadlo, Filip; Gleicher, Michael and Viola, Ivan and Leitte, Heike
In this paper, we show how the equivalence property leads to the novel concept of equivalent regions in mappings from Rn to Rn. We present a technique for obtaining these regions both in the domain and the codomain of such a mapping, and determine their correspondence. This enables effective investigation of variation equivalence within mappings, and between mappings in terms of comparative visualization. We implement our approach for n = 2, and demonstrate its utility using different examples.
Toward Understanding Representation Methods in Visualization Recommendations through Scatterplot Construction Tasks
(The Eurographics Association and John Wiley & Sons Ltd., 2019) L'Yi, Sehi; Chang, Youli; Shin, DongHwa; Seo, Jinwook; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Most visualization recommendation systems predominantly rely on graphical previews to describe alternative visual encodings. However, since InfoVis novices are not familiar with visual representations (e.g., interpretation barriers [GTS10]), novices might have difficulty understanding and choosing recommended visual encodings. As an initial step toward understanding effective representation methods for visualization recommendations, we investigate the effectiveness of three representation methods (i.e., previews, animated transitions, and textual descriptions) under scatterplot construction tasks. Our results show how different representations individually and cooperatively help users understand and choose recommended visualizations, for example, by supporting their expect-and-confirm process. Based on our study results, we discuss design implications for visualization recommendation interfaces.
Towards Glyphs for Uncertain Symmetric Second-Order Tensors
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Gerrits, Tim; Rössl, Christian; Theisel, Holger; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Measured data often incorporates some amount of uncertainty, which is generally modeled as a distribution of possible samples. In this paper, we consider second-order symmetric tensors with uncertainty. In the 3D case, this means the tensor data consists of 6 coefficients - uncertainty, however, is encoded by 21 coefficients assuming a multivariate Gaussian distribution as model. The high dimension makes the direct visualization of tensor data with uncertainty a difficult problem, which was until now unsolved. The contribution of this paper consists in the design of glyphs for uncertain second-order symmetric tensors in 2D and 3D. The construction consists of a standard glyph for the mean tensor that is augmented by a scalar field that represents uncertainty. We show that this scalar field and therefore the displayed glyph encode the uncertainty comprehensively, i.e., there exists a bijective map between the glyph and the parameters of the distribution. Our approach can extend several classes of existing glyphs for symmetric tensors to additionally encode uncertainty and therefore provides a possible foundation for further uncertain tensor glyph design. For demonstration, we choose the well-known superquadric glyphs, and we show that the uncertainty visualization satisfies all their design constraints.
An Interactive Visualization System for Large Sets of Phase Space Trajectories
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Neuroth, Tyson; Sauer, Franz; Ma, Kwan-Liu; Gleicher, Michael and Viola, Ivan and Leitte, Heike
We introduce a visual analysis system with GPU acceleration techniques for large sets of trajectories from complex dynamical systems. The approach is based on an interactive Boolean combination of subsets into a Focus+Context phase-space visualization. We achieve high performance through efficient bitwise algorithms utilizing runtime generated GPU shaders and kernels. This enables a higher level of interactivity for visualizing the large multivariate trajectory data. We explain how our design meets a set of carefully considered analysis requirements, provide performance results, and demonstrate utility through case studies with many-particle simulation data from two application areas.
Investigating the Manual View Specification and Visualization by Demonstration Paradigms for Visualization Construction
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Saket, Bahador; Endert, Alex; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Abstract Interactivity plays an important role in data visualization. Therefore, understanding how people create visualizations given different interaction paradigms provides empirical evidence to inform interaction design. We present a two-phase study comparing people's visualization construction processes using two visualization tools: one implementing the manual view specification paradigm (Polestar) and another implementing visualization by demonstration (VisExemplar). Findings of our study indicate that the choice of interaction paradigm influences the visualization construction in terms of: 1) the overall effectiveness, 2) how participants phrase their goals, and 3) their perceived control and engagement. Based on our findings, we discuss trade-offs and open challenges with these interaction paradigms.
Bridging the Data Analysis Communication Gap Utilizing a Three-Component Summarized Line Graph
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Yau, Calvin; Karimzadeh, Morteza; Surakitbanharn, Chittayong; Elmqvist, Niklas; Ebert, David; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Communication-minded visualizations are designed to provide their audience-managers, decision-makers, and the public-with new knowledge. Authoring such visualizations effectively is challenging because the audience often lacks the expertise, context, and time that professional analysts have at their disposal to explore and understand datasets. We present a novel summarized line graph visualization technique designed specifically for data analysts to communicate data to decision-makers more effectively and efficiently. Our summarized line graph reduces a large and detailed dataset of multiple quantitative time-series into (1) representative data that provides a quick takeaway of the full dataset; (2) analytical highlights that distinguish specific insights of interest; and (3) a data envelope that summarizes the remaining aggregated data. Our summarized line graph achieved the best overall results when evaluated against line graphs, band graphs, stream graphs, and horizon graphs on four representative tasks.
ChronoCorrelator: Enriching Events with Time Series
(The Eurographics Association and John Wiley & Sons Ltd., 2019) van Dortmont, Martijn; Elzen, Stef van den; Wijk, Jarke J. van; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Event sequences and time series are widely recorded in many application domains; examples are stock market prices, electronic health records, server operation and performance logs. Common goals for recording are monitoring, root cause analysis and predictive analytics. Current analysis methods generally focus on the exploration of either event sequences or time series. However, deeper insights are gained by combining both. We present a visual analytics approach where users can explore both time series and event data simultaneously, combining visualization, automated methods and human interaction. We enable users to iteratively refine the visualization. Correlations between event sequences and time series can be found by means of an interactive algorithm, which also computes the presence of monotonic effects. We illustrate the effectiveness of our method by applying it to real world and synthetic data sets.
Interactive Volumetric Visual Analysis of Glycogen-derived Energy Absorption in Nanometric Brain Structures
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Agus, Marco; Calì, Corrado; Al-Awami, Ali K.; Gobbetti, Enrico; Magistretti, Pierre J.; Hadwiger, Markus; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Digital acquisition and processing techniques are changing the way neuroscience investigation is carried out. Emerging applications range from statistical analysis on image stacks to complex connectomics visual analysis tools targeted to develop and test hypotheses of brain development and activity. In this work, we focus on neuroenergetics, a field where neuroscientists analyze nanoscale brain morphology and relate energy consumption to glucose storage in form of glycogen granules. In order to facilitate the understanding of neuroenergetic mechanisms, we propose a novel customized pipeline for the visual analysis of nanometric-level reconstructions based on electron microscopy image data. Our framework supports analysis tasks by combining i) a scalable volume visualization architecture able to selectively render image stacks and corresponding labelled data, ii) a method for highlighting distance-based energy absorption probabilities in form of glow maps, and iii) a hybrid connectivitybased and absorption-based interactive layout representation able to support queries for selective analysis of areas of interest and potential activity within the segmented datasets. This working pipeline is currently used in a variety of studies in the neuroenergetics domain. Here, we discuss a test case in which the framework was successfully used by domain scientists for the analysis of aging effects on glycogen metabolism, extracting knowledge from a series of nanoscale brain stacks of rodents somatosensory cortex.
Kyrix: Interactive Pan/Zoom Visualizations at Scale
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Tao, Wenbo; Liu, Xiaoyu; Wang, Yedi; Battle, Leilani; Demiralp, Çagatay; Chang, Remco; Stonebraker, Michael; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Pan and zoom are basic yet powerful interaction techniques for exploring large datasets. However, existing zoomable UI toolkits such as Pad++ and ZVTM do not provide the backend database support and data-driven primitives that are necessary for creating large-scale visualizations. This limitation in existing general-purpose toolkits has led to many purpose-built solutions (e.g. Google Maps and ForeCache) that address the issue of scalability but cannot be easily extended to support visualizations beyond their intended data types and usage scenarios. In this paper, we introduce Kyrix to ease the process of creating general and large-scale web-based pan/zoom visualizations. Kyrix is an integrated system that provides the developer with a concise and expressive declarative language along with a backend support for performance optimization of large-scale data. To evaluate the scalability of Kyrix, we conducted a set of benchmarked experiments and show that Kyrix can support high interactivity (with an average latency of 100 ms or below) on pan/zoom visualizations of 100 million data points. We further demonstrate the accessibility of Kyrix through an observational study with 8 developers. Results indicate that developers can quickly learn Kyrix's underlying declarative model to create scalable pan/zoom visualizations. Finally, we provide a gallery of visualizations and show that Kyrix is expressive and flexible in that it can support the developer in creating a wide range of customized visualizations across different application domains and data types.
EuroVis 2019 CGF 38-3: Frontmatter
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Gleicher, Michael; Viola, Ivan; Leitte, Heike; Gleicher, Michael and Viola, Ivan and Leitte, Heike
VIAN: A Visual Annotation Tool for Film Analysis
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Halter, Gaudenz; Ballester-Ripoll, Rafael; Flueckiger, Barbara; Pajarola, Renato; Gleicher, Michael and Viola, Ivan and Leitte, Heike
While color plays a fundamental role in film design and production, existing solutions for film analysis in the digital humanities address perceptual and spatial color information only tangentially. We introduce VIAN, a visual film annotation system centered on the semantic aspects of film color analysis. The tool enables expert-assessed labeling, curation, visualization and classification of color features based on their perceived context and aesthetic quality. It is the first of its kind that incorporates foreground-background information made possible by modern deep learning segmentation methods. The proposed tool seamlessly integrates a multimedia data management system, so that films can undergo a full color-oriented analysis pipeline.
Linking and Layout: Exploring the Integration of Text and Visualization in Storytelling
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Zhi, Qiyu; Ottley, Alvitta; Metoyer, Ronald; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Modern web technologies are enabling authors to create various forms of text visualization integration for storytelling. This integration may shape the stories' flow and thereby affect the reading experience. In this paper, we seek to understand two text visualization integration forms: (i) different text and visualization spatial arrangements (layout), namely, vertical and slideshow; and (ii) interactive linking of text and visualization (linking). Here, linking refers to a bidirectional interaction mode that explicitly highlights the explanatory visualization element when selecting narrative text and vice versa. Through a crowdsourced study with 180 participants, we measured the effect of layout and linking on the degree to which users engage with the story (user engagement), their understanding of the story content (comprehension), and their ability to recall the story information (recall). We found that participants performed significantly better in comprehension tasks with the slideshow layout. Participant recall was better with the slideshow layout under conditions with linking versus no linking. We also found that linking significantly increased user engagement. Additionally, linking and the slideshow layout were preferred by the participants. We also explored user reading behaviors with different conditions.

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