Conference stringclasses 6 values | Year int64 1.99k 2.03k | Title stringlengths 8 187 | DOI stringlengths 16 32 | Abstract stringlengths 128 7.15k ⌀ | Accessible bool 2 classes | Early bool 2 classes | AuthorNames-Deduped listlengths 1 24 | Award listlengths 0 2 | Resources listlengths 0 5 | ResourceLinks listlengths 0 10 |
|---|---|---|---|---|---|---|---|---|---|---|
InfoVis | 2,018 | Comparing Similarity Perception in Time Series Visualizations | 10.1109/TVCG.2018.2865077 | A common challenge faced by many domain experts working with time series data is how to identify and compare similar patterns. This operation is fundamental in high-level tasks, such as detecting recurring phenomena or creating clusters of similar temporal sequences. While automatic measures exist to compute time series similarity, human intervention is often required to visually inspect these automatically generated results. The visualization literature has examined similarity perception and its relation to automatic similarity measures for line charts, but has not yet considered if alternative visual representations, such as horizon graphs and colorfields, alter this perception. Motivated by how neuroscientists evaluate epileptiform patterns, we conducted two experiments that study how these three visualization techniques affect similarity perception in EEG signals. We seek to understand if the time series results returned from automatic similarity measures are perceived in a similar manner, irrespective of the visualization technique; and if what people perceive as similar with each visualization aligns with different automatic measures and their similarity constraints. Our findings indicate that horizon graphs align with similarity measures that allow local variations in temporal position or speed (i.e., dynamic time warping) more than the two other techniques. On the other hand, horizon graphs do not align with measures that are insensitive to amplitude and y-offset scaling (i.e., measures based on z-normalization), but the inverse seems to be the case for line charts and colorfields. Overall, our work indicates that the choice of visualization affects what temporal patterns we consider as similar, i.e., the notion of similarity in time series is not visualization independent. | false | false | [
"Anna Gogolou",
"Theophanis Tsandilas",
"Themis Palpanas",
"Anastasia Bezerianos"
] | [] | [] | [] |
InfoVis | 2,018 | Design Exposition with Literate Visualization | 10.1109/TVCG.2018.2864836 | We propose a new approach to the visualization design and communication process, literate visualization, based upon and extending, Donald Knuth's idea of literate programming. It integrates the process of writing data visualization code with description of the design choices that led to the implementation (design exposition). We develop a model of design exposition characterised by four visualization designer architypes: the evaluator, the autonomist, the didacticist and the rationalist. The model is used to justify the key characteristics of literate visualization: `notebook' documents that integrate live coding input, rendered output and textual narrative; low cost of authoring textual narrative; guidelines to encourage structured visualization design and its documentation. We propose narrative schemas for structuring and validating a wide range of visualization design approaches and models, and branching narratives for capturing alternative designs and design views. We describe a new open source literate visualization environment, litvis, based on a declarative interface to Vega and Vega-Lite through the functional programming language Elm combined with markdown for formatted narrative. We informally assess the approach, its implementation and potential by considering three examples spanning a range of design abstractions: new visualization idioms; validation though visualization algebra; and feminist data visualization. We argue that the rich documentation of the design process provided by literate visualization offers the potential to improve the validity of visualization design and so benefit both academic visualization and visualization practice. | false | false | [
"Jo Wood",
"Alexander Kachkaev",
"Jason Dykes"
] | [
"HM"
] | [] | [] |
InfoVis | 2,018 | DimReader: Axis lines that explain non-linear projections | 10.1109/TVCG.2018.2865194 | Non-linear dimensionality reduction (NDR) methods such as LLE and t-SNE are popular with visualization researchers and experienced data analysts, but present serious problems of interpretation. In this paper, we present DimReader, a technique that recovers readable axes from such techniques. DimReader is based on analyzing infinitesimal perturbations of the dataset with respect to variables of interest. The perturbations define exactly how we want to change each point in the original dataset and we measure the effect that these changes have on the projection. The recovered axes are in direct analogy with the axis lines (grid lines) of traditional scatterplots. We also present methods for discovering perturbations on the input data that change the projection the most. The calculation of the perturbations is efficient and easily integrated into programs written in modern programming languages. We present results of DimReader on a variety of NDR methods and datasets both synthetic and real-life, and show how it can be used to compare different NDR methods. Finally, we discuss limitations of our proposal and situations where further research is needed. | false | false | [
"Rebecca Faust",
"David Glickenstein",
"Carlos Scheidegger"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1710.00992v2",
"icon": "paper"
}
] |
InfoVis | 2,018 | DXR: A Toolkit for Building Immersive Data Visualizations | 10.1109/TVCG.2018.2865152 | This paper presents DXR, a toolkit for building immersive data visualizations based on the Unity development platform. Over the past years, immersive data visualizations in augmented and virtual reality (AR, VR) have been emerging as a promising medium for data sense-making beyond the desktop. However, creating immersive visualizations remains challenging, and often require complex low-level programming and tedious manual encoding of data attributes to geometric and visual properties. These can hinder the iterative idea-to-prototype process, especially for developers without experience in 3D graphics, AR, and VR programming. With DXR, developers can efficiently specify visualization designs using a concise declarative visualization grammar inspired by Vega-Lite. DXR further provides a GUI for easy and quick edits and previews of visualization designs in-situ, i.e., while immersed in the virtual world. DXR also provides reusable templates and customizable graphical marks, enabling unique and engaging visualizations. We demonstrate the flexibility of DXR through several examples spanning a wide range of applications. | false | false | [
"Ronell Sicat",
"Jiabao Li",
"Junyoung Choi",
"Maxime Cordeil",
"Won-Ki Jeong",
"Benjamin Bach",
"Hanspeter Pfister"
] | [] | [] | [] |
InfoVis | 2,018 | Dynamic Composite Data Physicalization Using Wheeled Micro-Robots | 10.1109/TVCG.2018.2865159 | This paper introduces dynamic composite physicalizations, a new class of physical visualizations that use collections of self-propelled objects to represent data. Dynamic composite physicalizations can be used both to give physical form to well-known interactive visualization techniques, and to explore new visualizations and interaction paradigms. We first propose a design space characterizing composite physicalizations based on previous work in the fields of Information Visualization and Human Computer Interaction. We illustrate dynamic composite physicalizations in two scenarios demonstrating potential benefits for collaboration and decision making, as well as new opportunities for physical interaction. We then describe our implementation using wheeled micro-robots capable of locating themselves and sensing user input, before discussing limitations and opportunities for future work. | false | false | [
"Mathieu Le Goc",
"Charles Perin",
"Sean Follmer",
"Jean-Daniel Fekete",
"Pierre Dragicevic"
] | [] | [] | [] |
InfoVis | 2,018 | Elastic Documents: Coupling Text and Tables through Contextual Visualizations for Enhanced Document Reading | 10.1109/TVCG.2018.2865119 | Today's data-rich documents are often complex datasets in themselves, consisting of information in different formats such as text, figures, and data tables. These additional media augment the textual narrative in the document. However, the static layout of a traditional for-print document often impedes deep understanding of its content because of the need to navigate to access content scattered throughout the text. In this paper, we seek to facilitate enhanced comprehension of such documents through a contextual visualization technique that couples text content with data tables contained in the document. We parse the text content and data tables, cross-link the components using a keyword-based matching algorithm, and generate on-demand visualizations based on the reader's current focus within a document. We evaluate this technique in a user study comparing our approach to a traditional reading experience. Results from our study show that (1) participants comprehend the content better with tighter coupling of text and data, (2) the contextual visualizations enable participants to develop better summaries that capture the main data-rich insights within the document, and (3) overall, our method enables participants to develop a more detailed understanding of the document content. | false | false | [
"Sriram Karthik Badam",
"Zhicheng Liu",
"Niklas Elmqvist"
] | [] | [] | [] |
InfoVis | 2,018 | Embedded Merge & Split: Visual Adjustment of Data Grouping | 10.1109/TVCG.2018.2865075 | Data grouping is among the most frequently used operations in data visualization. It is the process through which relevant information is gathered, simplified, and expressed in summary form. Many popular visualization tools support automatic grouping of data (e.g., dividing up a numerical variable into bins). Although grouping plays a pivotal role in supporting data exploration, further adjustment and customization of auto-generated grouping criteria is non-trivial. Such adjustments are currently performed either programmatically or through menus and dialogues which require specific parameter adjustments over several steps. In response, we introduce Embedded Merge & Split (EMS), a new interaction technique for direct adjustment of data grouping criteria. We demonstrate how the EMS technique can be designed to directly manipulate width and position in bar charts and histograms, as a means for adjustment of data grouping criteria. We also offer a set of design guidelines for supporting EMS. Finally, we present the results of two user studies, providing initial evidence that EMS can significantly reduce interaction time compared to WIMP-based technique and was subjectively preferred by participants. | false | false | [
"Ali Sarvghad",
"Bahador Saket",
"Alex Endert",
"Nadir Weibel"
] | [] | [] | [] |
InfoVis | 2,018 | Evaluating ‘Graphical Perception’ with CNNs | 10.1109/TVCG.2018.2865138 | Convolutional neural networks can successfully perform many computer vision tasks on images. For visualization, how do CNNs perform when applied to graphical perception tasks? We investigate this question by reproducing Cleveland and McGill's seminal 1984 experiments, which measured human perception efficiency of different visual encodings and defined elementary perceptual tasks for visualization. We measure the graphical perceptual capabilities of four network architectures on five different visualization tasks and compare to existing and new human performance baselines. While under limited circumstances CNNs are able to meet or outperform human task performance, we find that CNNs are not currently a good model for human graphical perception. We present the results of these experiments to foster the understanding of how CNNs succeed and fail when applied to data visualizations. | false | false | [
"Daniel Haehn",
"James Tompkin 0001",
"Hanspeter Pfister"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "https://osf.io/8b9xs",
"icon": "paper"
}
] |
InfoVis | 2,018 | Face to Face: Evaluating Visual Comparison | 10.1109/TVCG.2018.2864884 | Data are often viewed as a single set of values, but those values frequently must be compared with another set. The existing evaluations of designs that facilitate these comparisons tend to be based on intuitive reasoning, rather than quantifiable measures. We build on this work with a series of crowdsourced experiments that use low-level perceptual comparison tasks that arise frequently in comparisons within data visualizations (e.g., which value changes the most between the two sets of data?). Participants completed these tasks across a variety of layouts: overlaid, two arrangements of juxtaposed small multiples, mirror-symmetric small multiples, and animated transitions. A staircase procedure sought the difficulty level (e.g., value change delta) that led to equivalent accuracy for each layout. Confirming prior intuition, we observe high levels of performance for overlaid versus standard small multiples. However, we also find performance improvements for both mirror symmetric small multiples and animated transitions. While some results are incongruent with common wisdom in data visualization, they align with previous work in perceptual psychology, and thus have potentially strong implications for visual comparison designs. | false | false | [
"Brian D. Ondov",
"Nicole Jardine",
"Niklas Elmqvist",
"Steven Franconeri"
] | [] | [] | [] |
InfoVis | 2,018 | FiberClay: Sculpting Three Dimensional Trajectories to Reveal Structural Insights | 10.1109/TVCG.2018.2865191 | Visualizing 3D trajectories to extract insights about their similarities and spatial configuration is a critical task in several domains. Air traffic controllers for example deal with large quantities of aircrafts routes to optimize safety in airspace and neuroscientists attempt to understand neuronal pathways in the human brain by visualizing bundles of fibers from DTI images. Extracting insights from masses of 3D trajectories is challenging as the multiple three dimensional lines have complex geometries, may overlap, cross or even merge with each other, making it impossible to follow individual ones in dense areas. As trajectories are inherently spatial and three dimensional, we propose FiberClay: a system to display and interact with 3D trajectories in immersive environments. FiberClay renders a large quantity of trajectories in real time using GP-GPU techniques. FiberClay also introduces a new set of interactive techniques for composing complex queries in 3D space leveraging immersive environment controllers and user position. These techniques enable an analyst to select and compare sets of trajectories with specific geometries and data properties. We conclude by discussing insights found using FiberClay with domain experts in air traffic control and neurology. | false | false | [
"Christophe Hurter",
"Nathalie Henry Riche",
"Steven Mark Drucker",
"Maxime Cordeil",
"Richard Alligier",
"Romain Vuillemot"
] | [] | [] | [] |
InfoVis | 2,018 | Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco | 10.1109/TVCG.2018.2865240 | There exists a gap between visualization design guidelines and their application in visualization tools. While empirical studies can provide design guidance, we lack a formal framework for representing design knowledge, integrating results across studies, and applying this knowledge in automated design tools that promote effective encodings and facilitate visual exploration. We propose modeling visualization design knowledge as a collection of constraints, in conjunction with a method to learn weights for soft constraints from experimental data. Using constraints, we can take theoretical design knowledge and express it in a concrete, extensible, and testable form: the resulting models can recommend visualization designs and can easily be augmented with additional constraints or updated weights. We implement our approach in Draco, a constraint-based system based on Answer Set Programming (ASP). We demonstrate how to construct increasingly sophisticated automated visualization design systems, including systems based on weights learned directly from the results of graphical perception experiments. | false | false | [
"Dominik Moritz",
"Chenglong Wang",
"Greg L. Nelson",
"Halden Lin",
"Adam M. Smith 0001",
"Bill Howe",
"Jeffrey Heer"
] | [
"BP"
] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "https://osf.io/3eg9c",
"icon": "paper"
}
] |
InfoVis | 2,018 | Glanceable Visualization: Studies of Data Comparison Performance on Smartwatches | 10.1109/TVCG.2018.2865142 | We present the results of two perception studies to assess how quickly people can perform a simple data comparison task for small-scale visualizations on a smartwatch. The main goal of these studies is to extend our understanding of design constraints for smartwatch visualizations. Previous work has shown that a vast majority of smartwatch interactions last under 5 s. It is still unknown what people can actually perceive from visualizations during such short glances, in particular with such a limited display space of smartwatches. To shed light on this question, we conducted two perception studies that assessed the lower bounds of task time for a simple data comparison task. We tested three chart types common on smartwatches: bar charts, donut charts, and radial bar charts with three different data sizes: 7, 12, and 24 data values. In our first study, we controlled the differences of the two target bars to be compared, while the second study varied the difference randomly. For both studies, we found that participants performed the task on average in <;300 ms for the bar chart, <;220 ms for the donut chart, and in <; 1780 ms for the radial bar chart. Thresholds in the second study per chart type were on average 1.14-1.35× higher than in the first study. Our results show that bar and donut charts should be preferred on smartwatch displays when quick data comparisons are necessary. | false | false | [
"Tanja Blascheck",
"Lonni Besançon",
"Anastasia Bezerianos",
"Bongshin Lee",
"Petra Isenberg"
] | [] | [] | [] |
InfoVis | 2,018 | Graphicle: Exploring Units, Networks, and Context in a Blended Visualization Approach | 10.1109/TVCG.2018.2865151 | Many real-world datasets are large, multivariate, and relational in nature and relevant associated decisions frequently require a simultaneous consideration of both attributes and connections. Existing visualization systems and approaches, however, often make an explicit trade-off between either affording rich exploration of individual data units and their attributes or exploration of the underlying network structure. In doing so, important analysis opportunities and insights are potentially missed. In this study, we aim to address this gap by (1) considering visualizations and interaction techniques that blend the spectrum between unit and network visualizations, (2) discussing the nature of different forms of contexts and the challenges in implementing them, and (3) demonstrating the value of our approach for visual exploration of multivariate, relational data for a real-world use case. Specifically, we demonstrate through a system called Graphicle how network structure can be layered on top of unit visualization techniques to create new opportunities for visual exploration of physician characteristics and referral data. We report on the design, implementation, and evaluation of the system and effectiveness of our blended approach. | false | false | [
"Timothy Major",
"Rahul C. Basole"
] | [] | [] | [] |
InfoVis | 2,018 | Hypothetical Outcome Plots Help Untrained Observers Judge Trends in Ambiguous Data | 10.1109/TVCG.2018.2864909 | Animated representations of outcomes drawn from distributions (hypothetical outcome plots, or HOPs) are used in the media and other public venues to communicate uncertainty. HOPs greatly improve multivariate probability estimation over conventional static uncertainty visualizations and leverage the ability of the visual system to quickly, accurately, and automatically process the summary statistical properties of ensembles. However, it is unclear how well HOPs support applied tasks resembling real world judgments posed in uncertainty communication. We identify and motivate an appropriate task to investigate realistic judgments of uncertainty in the public domain through a qualitative analysis of uncertainty visualizations in the news. We contribute two crowdsourced experiments comparing the effectiveness of HOPs, error bars, and line ensembles for supporting perceptual decision-making from visualized uncertainty. Participants infer which of two possible underlying trends is more likely to have produced a sample of time series data by referencing uncertainty visualizations which depict the two trends with variability due to sampling error. By modeling each participant's accuracy as a function of the level of evidence presented over many repeated judgments, we find that observers are able to correctly infer the underlying trend in samples conveying a lower level of evidence when using HOPs rather than static aggregate uncertainty visualizations as a decision aid. Modeling approaches like ours contribute theoretically grounded and richly descriptive accounts of user perceptions to visualization evaluation. | false | false | [
"Alex Kale",
"Francis Nguyen",
"Matthew Kay 0001",
"Jessica Hullman"
] | [] | [] | [] |
InfoVis | 2,018 | IDMVis: Temporal Event Sequence Visualization for Type 1 Diabetes Treatment Decision Support | 10.1109/TVCG.2018.2865076 | Type 1 diabetes is a chronic, incurable autoimmune disease affecting millions of Americans in which the body stops producing insulin and blood glucose levels rise. The goal of intensive diabetes management is to lower average blood glucose through frequent adjustments to insulin protocol, diet, and behavior. Manual logs and medical device data are collected by patients, but these multiple sources are presented in disparate visualization designs to the clinician-making temporal inference difficult. We conducted a design study over 18 months with clinicians performing intensive diabetes management. We present a data abstraction and novel hierarchical task abstraction for this domain. We also contribute IDMVis: a visualization tool for temporal event sequences with multidimensional, interrelated data. IDMVis includes a novel technique for folding and aligning records by dual sentinel events and scaling the intermediate timeline. We validate our design decisions based on our domain abstractions, best practices, and through a qualitative evaluation with six clinicians. The results of this study indicate that IDMVis accurately reflects the workflow of clinicians. Using IDMVis, clinicians are able to identify issues of data quality such as missing or conflicting data, reconstruct patient records when data is missing, differentiate between days with different patterns, and promote educational interventions after identifying discrepancies. | false | false | [
"Yixuan Zhang",
"Kartik Chanana",
"Cody Dunne"
] | [] | [] | [] |
InfoVis | 2,018 | Image-Based Aspect Ratio Selection | 10.1109/TVCG.2018.2865266 | Selecting a good aspect ratio is crucial for effective 2D diagrams. There are several aspect ratio selection methods for function plots and line charts, but only few can handle general, discrete diagrams such as 2D scatter plots. However, these methods either lack a perceptual foundation or heavily rely on intermediate isoline representations, which depend on choosing the right isovalues and are time-consuming to compute. This paper introduces a general image-based approach for selecting aspect ratios for a wide variety of 2D diagrams, ranging from scatter plots and density function plots to line charts. Our approach is derived from Federer's co-area formula and a line integral representation that enable us to directly construct image-based versions of existing selection methods using density fields. In contrast to previous methods, our approach bypasses isoline computation, so it is faster to compute, while following the perceptual foundation to select aspect ratios. Furthermore, this approach is complemented by an anisotropic kernel density estimation to construct density fields, allowing us to more faithfully characterize data patterns, such as the subgroups in scatterplots or dense regions in time series. We demonstrate the effectiveness of our approach by quantitatively comparing to previous methods and revisiting a prior user study. Finally, we present extensions for ROI banking, multi-scale banking, and the application to image data. | false | false | [
"Yunhai Wang",
"Zeyu Wang 0005",
"Chi-Wing Fu",
"Hansjörg Schmauder",
"Oliver Deussen",
"Daniel Weiskopf"
] | [] | [] | [] |
InfoVis | 2,018 | In Pursuit of Error: A Survey of Uncertainty Visualization Evaluation | 10.1109/TVCG.2018.2864889 | Understanding and accounting for uncertainty is critical to effectively reasoning about visualized data. However, evaluating the impact of an uncertainty visualization is complex due to the difficulties that people have interpreting uncertainty and the challenge of defining correct behavior with uncertainty information. Currently, evaluators of uncertainty visualization must rely on general purpose visualization evaluation frameworks which can be ill-equipped to provide guidance with the unique difficulties of assessing judgments under uncertainty. To help evaluators navigate these complexities, we present a taxonomy for characterizing decisions made in designing an evaluation of an uncertainty visualization. Our taxonomy differentiates six levels of decisions that comprise an uncertainty visualization evaluation: the behavioral targets of the study, expected effects from an uncertainty visualization, evaluation goals, measures, elicitation techniques, and analysis approaches. Applying our taxonomy to 86 user studies of uncertainty visualizations, we find that existing evaluation practice, particularly in visualization research, focuses on Performance and Satisfaction-based measures that assume more predictable and statistically-driven judgment behavior than is suggested by research on human judgment and decision making. We reflect on common themes in evaluation practice concerning the interpretation and semantics of uncertainty, the use of confidence reporting, and a bias toward evaluating performance as accuracy rather than decision quality. We conclude with a concrete set of recommendations for evaluators designed to reduce the mismatch between the conceptualization of uncertainty in visualization versus other fields. | false | false | [
"Jessica Hullman",
"Xiaoli Qiao",
"Michael Correll",
"Alex Kale",
"Matthew Kay 0001"
] | [] | [] | [] |
InfoVis | 2,018 | Information Olfactation: Harnessing Scent to Convey Data | 10.1109/TVCG.2018.2865237 | Olfactory feedback for analytical tasks is a virtually unexplored area in spite of the advantages it offers for information recall, feature identification, and location detection. Here we introduce the concept of information olfactation as the fragrant sibling of information visualization, and discuss how scent can be used to convey data. Building on a review of the human olfactory system and mirroring common visualization practice, we propose olfactory marks, the substrate in which they exist, and their olfactory channels that are available to designers. To exemplify this idea, we present viScent: A six-scent stereo olfactory display capable of conveying olfactory glyphs of varying temperature and direction, as well as a corresponding software system that integrates the display with a traditional visualization display. Finally, we present three applications that make use of the viScent system: A 2D graph visualization, a 2D line and point chart, and an immersive analytics graph visualization in 3D virtual reality. We close the paper with a review of possible extensions of viScent and applications of information olfactation for general visualization beyond the examples in this paper. | false | false | [
"Biswaksen Patnaik",
"Andrea Batch",
"Niklas Elmqvist"
] | [] | [] | [] |
InfoVis | 2,018 | iStoryline: Effective Convergence to Hand-drawn Storylines | 10.1109/TVCG.2018.2864899 | Storyline visualization techniques have progressed significantly to generate illustrations of complex stories automatically. However, the visual layouts of storylines are not enhanced accordingly despite the improvement in the performance and extension of its application area. Existing methods attempt to achieve several shared optimization goals, such as reducing empty space and minimizing line crossings and wiggles. However, these goals do not always produce optimal results when compared to hand-drawn storylines. We conducted a preliminary study to learn how users translate a narrative into a hand-drawn storyline and check whether the visual elements in hand-drawn illustrations can be mapped back to appropriate narrative contexts. We also compared the hand-drawn storylines with storylines generated by the state-of-the-art methods and found they have significant differences. Our findings led to a design space that summarizes (1) how artists utilize narrative elements and (2) the sequence of actions artists follow to portray expressive and attractive storylines. We developed iStoryline, an authoring tool for integrating high-level user interactions into optimization algorithms and achieving a balance between hand-drawn storylines and automatic layouts. iStoryline allows users to create novel storyline visualizations easily according to their preferences by modifying the automatically generated layouts. The effectiveness and usability of iStoryline are studied with qualitative evaluations. | false | false | [
"Tan Tang",
"Sadia Rubab",
"Jiewen Lai",
"Weiwei Cui",
"Lingyun Yu 0001",
"Yingcai Wu"
] | [] | [] | [] |
InfoVis | 2,018 | Juniper: A Tree+Table Approach to Multivariate Graph Visualization | 10.1109/TVCG.2018.2865149 | Analyzing large, multivariate graphs is an important problem in many domains, yet such graphs are challenging to visualize. In this paper, we introduce a novel, scalable, tree-table multivariate graph visualization technique, which makes many tasks related to multivariate graph analysis easier to achieve. The core principle we follow is to selectively query for nodes or subgraphs of interest and visualize these subgraphs as a spanning tree of the graph. The tree is laid out linearly, which enables us to juxtapose the nodes with a table visualization where diverse attributes can be shown. We also use this table as an adjacency matrix, so that the resulting technique is a hybrid node-link/adjacency matrix technique. We implement this concept in Juniper and complement it with a set of interaction techniques that enable analysts to dynamically grow, restructure, and aggregate the tree, as well as change the layout or show paths between nodes. We demonstrate the utility of our tool in usage scenarios for different multivariate networks: a bipartite network of scholars, papers, and citation metrics and a multitype network of story characters, places, books, etc. | false | false | [
"Carolina Nobre",
"Marc Streit",
"Alexander Lex"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1804.03261v2",
"icon": "paper"
}
] |
InfoVis | 2,018 | Looks Good To Me: Visualizations As Sanity Checks | 10.1109/TVCG.2018.2864907 | Famous examples such as Anscombe's Quartet highlight that one of the core benefits of visualizations is allowing people to discover visual patterns that might otherwise be hidden by summary statistics. This visual inspection is particularly important in exploratory data analysis, where analysts can use visualizations such as histograms and dot plots to identify data quality issues. Yet, these visualizations are driven by parameters such as histogram bin size or mark opacity that have a great deal of impact on the final visual appearance of the chart, but are rarely optimized to make important features visible. In this paper, we show that data flaws have varying impact on the visual features of visualizations, and that the adversarial or merely uncritical setting of design parameters of visualizations can obscure the visual signatures of these flaws. Drawing on the framework of Algebraic Visualization Design, we present the results of a crowdsourced study showing that common visualization types can appear to reasonably summarize distributional data while hiding large and important flaws such as missing data and extraneous modes. We make use of these results to propose additional best practices for visualizations of distributions for data quality tasks. | false | false | [
"Michael Correll",
"Mingwei Li",
"Gordon L. Kindlmann",
"Carlos Scheidegger"
] | [] | [] | [] |
InfoVis | 2,018 | Mapping Color to Meaning in Colormap Data Visualizations | 10.1109/TVCG.2018.2865147 | To interpret data visualizations, people must determine how visual features map onto concepts. For example, to interpret colormaps, people must determine how dimensions of color (e.g., lightness, hue) map onto quantities of a given measure (e.g., brain activity, correlation magnitude). This process is easier when the encoded mappings in the visualization match people's predictions of how visual features will map onto concepts, their inferred mappings. To harness this principle in visualization design, it is necessary to understand what factors determine people's inferred mappings. In this study, we investigated how inferred color-quantity mappings for colormap data visualizations were influenced by the background color. Prior literature presents seemingly conflicting accounts of how the background color affects inferred color-quantity mappings. The present results help resolve those conflicts, demonstrating that sometimes the background has an effect and sometimes it does not, depending on whether the colormap appears to vary in opacity. When there is no apparent variation in opacity, participants infer that darker colors map to larger quantities (dark-is-more bias). As apparent variation in opacity increases, participants become biased toward inferring that more opaque colors map to larger quantities (opaque-is-more bias). These biases work together on light backgrounds and conflict on dark backgrounds. Under such conflicts, the opaque-is-more bias can negate, or even supersede the dark-is-more bias. The results suggest that if a design goal is to produce colormaps that match people's inferred mappings and are robust to changes in background color, it is beneficial to use colormaps that will not appear to vary in opacity on any background color, and to encode larger quantities in darker colors. | false | false | [
"Karen B. Schloss",
"Connor Gramazio",
"Allison T. Silverman",
"Madeline L. Parker",
"Audrey S. Wang"
] | [
"HM"
] | [] | [] |
InfoVis | 2,018 | Mitigating the Attraction Effect with Visualizations | 10.1109/TVCG.2018.2865233 | Human decisions are prone to biases, and this is no less true for decisions made within data visualizations. Bias mitigation strategies often focus on the person, by educating people about their biases, typically with little success. We focus instead on the system, presenting the first evidence that altering the design of an interactive visualization tool can mitigate a strong bias - the attraction effect. Participants viewed 2D scatterplots where choices between superior alternatives were affected by the placement of other suboptimal points. We found that highlighting the superior alternatives weakened the bias, but did not eliminate it. We then tested an interactive approach where participants completely removed locally dominated points from the view, inspired by the elimination by aspects strategy in the decision-making literature. This approach strongly decreased the bias, leading to a counterintuitive suggestion: tools that allow removing inappropriately salient or distracting data from a view may help lead users to make more rational decisions. | false | false | [
"Evanthia Dimara",
"Gilles Bailly",
"Anastasia Bezerianos",
"Steven Franconeri"
] | [] | [] | [] |
InfoVis | 2,018 | Multiple Coordinated Views at Large Displays for Multiple Users: Empirical Findings on User Behavior, Movements, and Distances | 10.1109/TVCG.2018.2865235 | Interactive wall-sized displays benefit data visualization. Due to their sheer display size, they make it possible to show large amounts of data in multiple coordinated views (MCV) and facilitate collaborative data analysis. In this work, we propose a set of important design considerations and contribute a fundamental input vocabulary and interaction mapping for MCV functionality. We also developed a fully functional application with more than 45 coordinated views visualizing a real-world, multivariate data set of crime activities, which we used in a comprehensive qualitative user study investigating how pairs of users behave. Most importantly, we found that flexible movement is essential and-depending on user goals-is connected to collaboration, perception, and interaction. Therefore, we argue that for future systems interaction from the distance is required and needs good support. We show that our consistent design for both direct touch at the large display and distant interaction using mobile phones enables the seamless exploration of large-scale MCV at wall-sized displays. Our MCV application builds on design aspects such as simplicity, flexibility, and visual consistency and, therefore, supports realistic workflows. We believe that in the future, many visual data analysis scenarios will benefit from wall-sized displays presenting numerous coordinated visualizations, for which our findings provide a valuable foundation. | false | false | [
"Ricardo Langner",
"Ulrike Kister",
"Raimund Dachselt"
] | [] | [] | [] |
InfoVis | 2,018 | Narvis: Authoring Narrative Slideshows for Introducing Data Visualization Designs | 10.1109/TVCG.2018.2865232 | Visual designs can be complex in modern data visualization systems, which poses special challenges for explaining them to the non-experts. However, few if any presentation tools are tailored for this purpose. In this study, we present Narvis, a slideshow authoring tool designed for introducing data visualizations to non-experts. Narvis targets two types of end users: teachers, experts in data visualization who produce tutorials for explaining a data visualization, and students, non-experts who try to understand visualization designs through tutorials. We present an analysis of requirements through close discussions with the two types of end users. The resulting considerations guide the design and implementation of Narvis. Additionally, to help teachers better organize their introduction slideshows, we specify a data visualization as a hierarchical combination of components, which are automatically detected and extracted by Narvis. The teachers craft an introduction slideshow through first organizing these components, and then explaining them sequentially. A series of templates are provided for adding annotations and animations to improve efficiency during the authoring process. We evaluate Narvis through a qualitative analysis of the authoring experience, and a preliminary evaluation of the generated slideshows. | false | false | [
"Qianwen Wang",
"Zhen Li 0044",
"Siwei Fu",
"Weiwei Cui",
"Huamin Qu"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1907.05609v1",
"icon": "paper"
}
] |
InfoVis | 2,018 | NLIZE: A Perturbation-Driven Visual Interrogation Tool for Analyzing and Interpreting Natural Language Inference Models | 10.1109/TVCG.2018.2865230 | With the recent advances in deep learning, neural network models have obtained state-of-the-art performances for many linguistic tasks in natural language processing. However, this rapid progress also brings enormous challenges. The opaque nature of a neural network model leads to hard-to-debug-systems and difficult-to-interpret mechanisms. Here, we introduce a visualization system that, through a tight yet flexible integration between visualization elements and the underlying model, allows a user to interrogate the model by perturbing the input, internal state, and prediction while observing changes in other parts of the pipeline. We use the natural language inference problem as an example to illustrate how a perturbation-driven paradigm can help domain experts assess the potential limitation of a model, probe its inner states, and interpret and form hypotheses about fundamental model mechanisms such as attention. | false | false | [
"Shusen Liu",
"Zhimin Li",
"Tao Li 0039",
"Vivek Srikumar",
"Valerio Pascucci",
"Peer-Timo Bremer"
] | [] | [] | [] |
InfoVis | 2,018 | Optimizing Color Assignment for Perception of Class Separability in Multiclass Scatterplots | 10.1109/TVCG.2018.2864912 | Appropriate choice of colors significantly aids viewers in understanding the structures in multiclass scatterplots and becomes more important with a growing number of data points and groups. An appropriate color mapping is also an important parameter for the creation of an aesthetically pleasing scatterplot. Currently, users of visualization software routinely rely on color mappings that have been pre-defined by the software. A default color mapping, however, cannot ensure an optimal perceptual separability between groups, and sometimes may even lead to a misinterpretation of the data. In this paper, we present an effective approach for color assignment based on a set of given colors that is designed to optimize the perception of scatterplots. Our approach takes into account the spatial relationships, density, degree of overlap between point clusters, and also the background color. For this purpose, we use a genetic algorithm that is able to efficiently find good color assignments. We implemented an interactive color assignment system with three extensions of the basic method that incorporates top K suggestions, user-defined color subsets, and classes of interest for the optimization. To demonstrate the effectiveness of our assignment technique, we conducted a numerical study and a controlled user study to compare our approach with default color assignments; our findings were verified by two expert studies. The results show that our approach is able to support users in distinguishing cluster numbers faster and more precisely than default assignment methods. | false | false | [
"Yunhai Wang",
"Xin Chen",
"Tong Ge",
"Chen Bao",
"Michael Sedlmair",
"Chi-Wing Fu",
"Oliver Deussen",
"Baoquan Chen"
] | [] | [] | [] |
InfoVis | 2,018 | Origin-Destination Flow Maps in Immersive Environments | 10.1109/TVCG.2018.2865192 | Immersive virtual- and augmented-reality headsets can overlay a flat image against any surface or hang virtual objects in the space around the user. The technology is rapidly improving and may, in the long term, replace traditional flat panel displays in many situations. When displays are no longer intrinsically flat, how should we use the space around the user for abstract data visualisation? In this paper, we ask this question with respect to origin-destination flow data in a global geographic context. We report on the findings of three studies exploring different spatial encodings for flow maps. The first experiment focuses on different 2D and 3D encodings for flows on flat maps. We find that participants are significantly more accurate with raised flow paths whose height is proportional to flow distance but fastest with traditional straight line 2D flows. In our second and third experiment we compared flat maps, 3D globes and a novel interactive design we callMapsLink, involving a pair of linked flat maps. We find that participants took significantly more time with MapsLink than other flow maps while the 3D globe with raised flows was the fastest, most accurate, and most preferred method. Our work suggests thatcarefuluse of the third spatial dimension can resolve visual clutter in complex flow maps. | false | false | [
"Yalong Yang 0001",
"Tim Dwyer",
"Bernhard Jenny",
"Kim Marriott",
"Maxime Cordeil",
"Haohui Chen"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1908.02089v1",
"icon": "paper"
}
] |
InfoVis | 2,018 | Patterns and Pace: Quantifying Diverse Exploration Behavior with Visualizations on the Web | 10.1109/TVCG.2018.2865117 | The diverse and vibrant ecosystem of interactive visualizations on the web presents an opportunity for researchers and practitioners to observe and analyze how everyday people interact with data visualizations. However, existing metrics of visualization interaction behavior used in research do not fully reveal the breadth of peoples' open-ended explorations with visualizations. One possible way to address this challenge is to determine high-level goals for visualization interaction metrics, and infer corresponding features from user interaction data that characterize different aspects of peoples' explorations of visualizations. In this paper, we identify needs for visualization behavior measurement, and develop corresponding candidate features that can be inferred from users' interaction data. We then propose metrics that capture novel aspects of peoples' open-ended explorations, including exploration uniqueness and exploration pacing. We evaluate these metrics along with four other metrics recently proposed in visualization literature by applying them to interaction data from prior visualization studies. The results of these evaluations suggest that these new metrics 1) reveal new characteristics of peoples' use of visualizations, 2) can be used to evaluate statistical differences between visualization designs, and 3) are statistically independent of prior metrics used in visualization research. We discuss implications of these results for future studies, including the potential for applying these metrics in visualization interaction analysis, as well as emerging challenges in developing and selecting metrics depicting visualization explorations. | false | false | [
"Mi Feng",
"Evan M. Peck",
"Lane Harrison"
] | [] | [] | [] |
InfoVis | 2,018 | Shape-preserving Star Coordinates | 10.1109/TVCG.2018.2865118 | Dimensionality reduction is commonly applied to multidimensional data to reduce the complexity of their analysis. In visual analysis systems, projections embed multidimensional data into 2D or 3D spaces for graphical representation. To facilitate a robust and accurate analysis, essential characteristics of the multidimensional data shall be preserved when projecting. Orthographic star coordinates is a state-of-the-art linear projection method that avoids distortion of multidimensional clusters by restricting interactive exploration to orthographic projections. However, existing numerical methods for computing orthographic star coordinates have a number of limitations when putting them into practice. We overcome these limitations by proposing the novel concept of shape-preserving star coordinates where shape preservation is assured using a superset of orthographic projections. Our scheme is explicit, exact, simple, fast, parameter-free, and stable. To maintain a valid shape-preserving star-coordinates configuration during user interaction with one of the star-coordinates axes, we derive an algorithm that only requires us to modify the configuration of one additional compensatory axis. Different design goals can be targeted by using different strategies for selecting the compensatory axis. We propose and discuss four strategies including a strategy that approximates orthographic star coordinates very well and a data-driven strategy. We further present shape-preserving morphing strategies between two shape-preserving configurations, which can be adapted for the generation of data tours. We apply our concept to multiple data analysis scenarios to document its applicability and validate its desired properties. | false | false | [
"Vladimir Molchanov",
"Lars Linsen"
] | [] | [] | [] |
InfoVis | 2,018 | SmartCues: A Multitouch Query Approach for Details-on-Demand through Dynamically Computed Overlays | 10.1109/TVCG.2018.2865231 | Details-on-demand is a crucial feature in the visual information-seeking process but is often only implemented in highly constrained settings. The most common solution, hover queries (i.e., tooltips), are fast and expressive but are usually limited to single mark (e.g., a bar in a bar chart). `Queries' to retrieve details for more complex sets of objects (e.g., comparisons between pairs of elements, averages across multiple items, trend lines, etc.) are difficult for end-users to invoke explicitly. Further, the output of these queries require complex annotations and overlays which need to be displayed and dismissed on demand to avoid clutter. In this work we introduce SmartCues, a library to support details-on-demand through dynamically computed overlays. For end-users, SmartCues provides multitouch interactions to construct complex queries for a variety of details. For designers, SmartCues offers an interaction library that can be used out-of-the-box, and can be extended for new charts and detail types. We demonstrate how SmartCues can be implemented across a wide array of visualization types and, through a lab study, show that end users can effectively use SmartCues. | false | false | [
"Hariharan Subramonyam",
"Eytan Adar"
] | [] | [] | [] |
InfoVis | 2,018 | SRVis: Towards Better Spatial Integration in Ranking Visualization | 10.1109/TVCG.2018.2865126 | Interactive ranking techniques have substantially promoted analysts' ability in making judicious and informed decisions effectively based on multiple criteria. However, the existing techniques cannot satisfactorily support the analysis tasks involved in ranking large-scale spatial alternatives, such as selecting optimal locations for chain stores, where the complex spatial contexts involved are essential to the decision-making process. Limitations observed in the prior attempts of integrating rankings with spatial contexts motivate us to develop a context-integrated visual ranking technique. Based on a set of generic design requirements we summarized by collaborating with domain experts, we propose SRVis, a novel spatial ranking visualization technique that supports efficient spatial multi-criteria decision-making processes by addressing three major challenges in the aforementioned context integration, namely, a) the presentation of spatial rankings and contexts, b) the scalability of rankings' visual representations, and c) the analysis of context-integrated spatial rankings. Specifically, we encode massive rankings and their cause with scalable matrix-based visualizations and stacked bar charts based on a novel two-phase optimization framework that minimizes the information loss, and the flexible spatial filtering and intuitive comparative analysis are adopted to enable the in-depth evaluation of the rankings and assist users in selecting the best spatial alternative. The effectiveness of the proposed technique has been evaluated and demonstrated with an empirical study of optimization methods, two case studies, and expert interviews. | false | false | [
"Di Weng",
"Ran Chen",
"Zikun Deng",
"Feiran Wu",
"Jingmin Chen",
"Yingcai Wu"
] | [] | [] | [] |
InfoVis | 2,018 | Structure-aware Fisheye Views for Efficient Large Graph Exploration | 10.1109/TVCG.2018.2864911 | Traditional fisheye views for exploring large graphs introduce substantial distortions that often lead to a decreased readability of paths and other interesting structures. To overcome these problems, we propose a framework for structure-aware fisheye views. Using edge orientations as constraints for graph layout optimization allows us not only to reduce spatial and temporal distortions during fisheye zooms, but also to improve the readability of the graph structure. Furthermore, the framework enables us to optimize fisheye lenses towards specific tasks and design a family of new lenses: polyfocal, cluster, and path lenses. A GPU implementation lets us process large graphs with up to 15,000 nodes at interactive rates. A comprehensive evaluation, a user study, and two case studies demonstrate that our structure-aware fisheye views improve layout readability and user performance. | false | false | [
"Yunhai Wang",
"Yanyan Wang",
"Haifeng Zhang",
"Yinqi Sun",
"Chi-Wing Fu",
"Michael Sedlmair",
"Baoquan Chen",
"Oliver Deussen"
] | [] | [] | [] |
InfoVis | 2,018 | Structure-Based Suggestive Exploration: A New Approach for Effective Exploration of Large Networks | 10.1109/TVCG.2018.2865139 | When analyzing a visualized network, users need to explore different sections of the network to gain insight. However, effective exploration of large networks is often a challenge. While various tools are available for users to explore the global and local features of a network, these tools usually require significant interaction activities, such as repetitive navigation actions to follow network nodes and edges. In this paper, we propose a structure-based suggestive exploration approach to support effective exploration of large networks by suggesting appropriate structures upon user request. Encoding nodes with vectorized representations by transforming information of surrounding structures of nodes into a high dimensional space, our approach can identify similar structures within a large network, enable user interaction with multiple similar structures simultaneously, and guide the exploration of unexplored structures. We develop a web-based visual exploration system to incorporate this suggestive exploration approach and compare performances of our approach under different vectorizing methods and networks. We also present the usability and effectiveness of our approach through a controlled user study with two datasets. | false | false | [
"Wei Chen 0001",
"Fangzhou Guo",
"Dongming Han",
"Jacheng Pan",
"Xiaotao Nie",
"Jiazhi Xia",
"Xiaolong Zhang 0001"
] | [] | [] | [] |
InfoVis | 2,018 | Temporal Treemaps: Static Visualization of Evolving Trees | 10.1109/TVCG.2018.2865265 | We consider temporally evolving trees with changing topology and data: tree nodes may persist for a time range, merge or split, and the associated data may change. Essentially, one can think of this as a time series of trees with a node correspondence per hierarchy level between consecutive time steps. Existing visualization approaches for such data include animated 2D treemaps, where the dynamically changing layout makes it difficult to observe the data in its entirety. We present a method to visualize this dynamic data in a static, nested, and space-filling visualization. This is based on two major contributions: First, the layout constitutes a graph drawing problem. We approach it for the entire time span at once using a combination of a heuristic and simulated annealing. Second, we propose a rendering that emphasizes the hierarchy through an adaption of the classic cushion treemaps. We showcase the wide range of applicability using data from feature tracking in time-dependent scalar fields, evolution of file system hierarchies, and world population. | false | false | [
"Wiebke Köpp",
"Tino Weinkauf"
] | [] | [] | [] |
InfoVis | 2,018 | Vistrates: A Component Model for Ubiquitous Analytics | 10.1109/TVCG.2018.2865144 | Visualization tools are often specialized for specific tasks, which turns the user's analytical workflow into a fragmented process performed across many tools. In this paper, we present a component model design for data visualization to promote modular designs of visualization tools that enhance their analytical scope. Rather than fragmenting tasks across tools, the component model supports unification, where components-the building blocks of this model-can be assembled to support a wide range of tasks. Furthermore, the model also provides additional key properties, such as support for collaboration, sharing across multiple devices, and adaptive usage depending on expertise, from creating visualizations using dropdown menus, through instantiating components, to actually modifying components or creating entirely new ones from scratch using JavaScript or Python source code. To realize our model, we introduce Vistrates, a literate computing platform for developing, assembling, and sharing visualization components. From a visualization perspective, Vistrates features cross-cutting components for visual representations, interaction, collaboration, and device responsiveness maintained in a component repository. From a development perspective, Vistrates offers a collaborative programming environment where novices and experts alike can compose component pipelines for specific analytical activities. Finally, we present several Vistrates use cases that span the full range of the classic “anytime” and “anywhere” motto for ubiquitous analysis: from mobile and on-the-go usage, through office settings, to collaborative smart environments covering a variety of tasks and devices.. | false | false | [
"Sriram Karthik Badam",
"Andreas Mathisen",
"Roman Rädle",
"Clemens Nylandsted Klokmose",
"Niklas Elmqvist"
] | [] | [] | [] |
InfoVis | 2,018 | Visualizing Ranges over Time on Mobile Phones: A Task-Based Crowdsourced Evaluation | 10.1109/TVCG.2018.2865234 | In the first crowdsourced visualization experiment conducted exclusively on mobile phones, we compare approaches to visualizing ranges over time on small displays. People routinely consume such data via a mobile phone, from temperatures in weather forecasting apps to sleep and blood pressure readings in personal health apps. However, we lack guidance on how to effectively visualize ranges on small displays in the context of different value retrieval and comparison tasks, or with respect to different data characteristics such as periodicity, seasonality, or the cardinality of ranges. Central to our experiment is a comparison between two ways to lay out ranges: a more conventional linear layout strikes a balance between quantitative and chronological scale resolution, while a less conventional radial layout emphasizes the cyclicality of time and may prioritize discrimination between values at its periphery. With results from 87 crowd workers, we found that while participants completed tasks more quickly with linear layouts than with radial ones, there were few differences in terms of error rate between layout conditions. We also found that participants performed similarly with both layouts in tasks that involved comparing superimposed observed and average ranges. | false | false | [
"Matthew Brehmer",
"Bongshin Lee",
"Petra Isenberg",
"Eun Kyoung Choe"
] | [] | [] | [] |
InfoVis | 2,018 | Visualizing Uncertain Tropical Cyclone Predictions using Representative Samples from Ensembles of Forecast Tracks | 10.1109/TVCG.2018.2865193 | A common approach to sampling the space of a prediction is the generation of an ensemble of potential outcomes, where the ensemble's distribution reveals the statistical structure of the prediction space. For example, the US National Hurricane Center generates multiple day predictions for a storm's path, size, and wind speed, and then uses a Monte Carlo approach to sample this prediction into a large ensemble of potential storm outcomes. Various forms of summary visualizations are generated from such an ensemble, often using spatial spread to indicate its statistical characteristics. However, studies have shown that changes in the size of such summary glyphs, representing changes in the uncertainty of the prediction, are frequently confounded with other attributes of the phenomenon, such as its size or strength. In addition, simulation ensembles typically encode multivariate information, which can be difficult or confusing to include in a summary display. This problem can be overcome by directly displaying the ensemble as a set of annotated trajectories, however this solution will not be effective if ensembles are densely overdrawn or structurally disorganized. We propose to overcome these difficulties by selectively sampling the original ensemble, constructing a smaller representative and spatially well organized ensemble. This can be drawn directly as a set of paths that implicitly reveals the underlying spatial uncertainty distribution of the prediction. Since this approach does not use a visual channel to encode uncertainty, additional information can more easily be encoded in the display without leading to visual confusion. To demonstrate our argument, we describe the development of a visualization for ensembles of tropical cyclone forecast tracks, explaining how their spatial and temporal predictions, as well as other crucial storm characteristics such as size and intensity, can be clearly revealed. We verify the effectiveness of this visualization approach through a cognitive study exploring how storm damage estimates are affected by the density of tracks drawn, and by the presence or absence of annotating information on storm size and intensity. | false | false | [
"Le Liu 0007",
"Lace M. K. Padilla",
"Sarah H. Creem-Regehr",
"Donald H. House"
] | [] | [] | [] |
InfoVis | 2,018 | What Do We Talk About When We Talk About Dashboards? | 10.1109/TVCG.2018.2864903 | Dashboards are one of the most common use cases for data visualization, and their design and contexts of use are considerably different from exploratory visualization tools. In this paper, we look at the broad scope of how dashboards are used in practice through an analysis of dashboard examples and documentation about their use. We systematically review the literature surrounding dashboard use, construct a design space for dashboards, and identify major dashboard types. We characterize dashboards by their design goals, levels of interaction, and the practices around them. Our framework and literature review suggest a number of fruitful research directions to better support dashboard design, implementation and use. | false | false | [
"Alper Sarikaya",
"Michael Correll",
"Lyn Bartram",
"Melanie Tory",
"Danyel Fisher"
] | [] | [] | [] |
InfoVis | 2,018 | Where's My Data? Evaluating Visualizations with Missing Data | 10.1109/TVCG.2018.2864914 | Many real-world datasets are incomplete due to factors such as data collection failures or misalignments between fused datasets. Visualizations of incomplete datasets should allow analysts to draw conclusions from their data while effectively reasoning about the quality of the data and resulting conclusions. We conducted a pair of crowdsourced studies to measure how the methods used to impute and visualize missing data may influence analysts' perceptions of data quality and their confidence in their conclusions. Our experiments used different design choices for line graphs and bar charts to estimate averages and trends in incomplete time series datasets. Our results provide preliminary guidance for visualization designers to consider when working with incomplete data in different domains and scenarios. | false | false | [
"Hayeong Song",
"Danielle Albers Szafir"
] | [] | [] | [] |
EuroVis | 2,018 | A General Illumination Model for Molecular Visualization | 10.1111/cgf.13426 | Several visual representations have been developed over the years to visualize molecular structures, and to enable a better understanding of their underlying chemical processes. Today, the most frequently used atom‐based representations are the Space‐filling, the Solvent Excluded Surface, the Balls‐and‐Sticks, and the Licorice models. While each of these representations has its individual benefits, when applied to large‐scale models spatial arrangements can be difficult to interpret when employing current visualization techniques. In the past it has been shown that global illumination techniques improve the perception of molecular visualizations; unfortunately existing approaches are tailored towards a single visual representation. We propose a general illumination model for molecular visualization that is valid for different representations. With our illumination model, it becomes possible, for the first time, to achieve consistent illumination among all atom‐based molecular representations. The proposed model can be further evaluated in real‐time, as it employs an analytical solution to simulate diffuse light interactions between objects. To be able to derive such a solution for the rather complicated and diverse visual representations, we propose the use of regression analysis together with adapted parameter sampling strategies as well as shape parametrization guided sampling, which are applied to the geometric building blocks of the targeted visual representations. We will discuss the proposed sampling strategies, the derived illumination model, and demonstrate its capabilities when visualizing several dynamic molecules. | false | false | [
"Pedro Hermosilla",
"Pere-Pau Vázquez",
"Àlvar Vinacua",
"Timo Ropinski"
] | [] | [] | [] |
EuroVis | 2,018 | A Survey of Flattening-Based Medical Visualization Techniques | 10.1111/cgf.13445 | In many areas of medicine, visualization research can help with task simplification, abstraction or complexity reduction. A common visualization approach is to facilitate parameterization techniques which flatten a usually 3D object into a 2D plane. Within this state of the art report (STAR), we review such techniques used in medical visualization and investigate how they can be classified with respect to the handled data and the underlying tasks. Many of these techniques are inspired by mesh parameterization algorithms which help to project a triangulation in ℝ3 to a simpler domain in ℝ2. It is often claimed that this makes complex structures easier to understand and compare by humans and machines. Within this STAR we review such flattening techniques which have been developed for the analysis of the following medical entities: the circulation system, the colon, the brain, tumors, and bones. For each of these five application scenarios, we have analyzed the tasks and requirements, and classified the reviewed techniques with respect to a developed coding system. Furthermore, we present guidelines for the future development of flattening techniques in these areas. | false | false | [
"Julian Kreiser",
"Monique Meuschke",
"Gabriel Mistelbauer",
"Bernhard Preim",
"Timo Ropinski"
] | [] | [] | [] |
EuroVis | 2,018 | An Approximate Parallel Vectors Operator for Multiple Vector Fields | 10.1111/cgf.13422 | The Parallel Vectors (PV) Operator extracts the locations of points where two vector fields are parallel. In general, these features are line structures. The PV operator has been used successfully for a variety of problems, which include finding vortex‐core lines or extremum lines. We present a new generic feature extraction method for multiple 3D vector fields: The Approximate Parallel Vectors (APV) Operator extracts lines where all fields are approximately parallel. The definition of the APV operator is based on the application of PV for two vector fields that are derived from the given set of fields. The APV operator enables the direct visualization of features of vector field ensembles without processing fields individually and without causing visual clutter. We give a theoretical analysis of the APV operator and demonstrate its utility for a number of ensemble data. | false | false | [
"Tim Gerrits",
"Christian Rössl",
"Holger Theisel"
] | [] | [] | [] |
EuroVis | 2,018 | Analyzing Residue Surface Proximity to Interpret Molecular Dynamics | 10.1111/cgf.13427 | The surface of a molecule holds important information about the interaction behavior with other molecules. In dynamic folding or docking processes, residues of amino acids with different properties change their position within the molecule over time. The atoms of the residues that are accessible to the solvent can directly contribute to binding interactions, while residues buried within the molecular structure contribute to the stability of the molecule. Understanding patterns and causality of structural changes is important for experts in the pharmaceutical domain, e.g., in the process of drug design. We apply an iterative computation of the Solvent Accessible Surface in order to extract virtual layers of a molecule. The extraction allows to track the movement of residues in the body of the molecule, with respect to the distance of the residue to the surface or the core during dynamics simulations. We visualize the obtained layer information for the complete time span of the molecular dynamics simulation as a 2D‐map and for individual time‐steps as a 3D‐representation of the molecule. The data acquisition has been implemented alongside with further analysis functionality in a prototypical application, which is available to the public domain. We underline the feasibility of our approach with a study from the pharmaceutical domain, where our approach has been used for novel insights into the folding behavior of μ‐conotoxins. | false | false | [
"Nils Lichtenberg",
"Raphael Menges",
"V. Ageev",
"Ajay Abisheck Paul George",
"P. Heimer",
"Diana Imhof",
"Kai Lawonn"
] | [] | [] | [] |
EuroVis | 2,018 | Assessing Effects of Task and Data Distribution on the Effectiveness of Visual Encodings | 10.1111/cgf.13409 | In addition to the choice of visual encodings, the effectiveness of a data visualization may vary with the analytical task being performed and the distribution of data values. To better assess these effects and create refined rankings of visual encodings, we conduct an experiment measuring subject performance across task types (e.g., comparing individual versus aggregate values) and data distributions (e.g., with varied cardinalities and entropies). We compare performance across 12 encoding specifications of trivariate data involving 1 categorical and 2 quantitative fields, including the use of x, y, color, size, and spatial subdivision (i.e., faceting). Our results extend existing models of encoding effectiveness and suggest improved approaches for automated design. For example, we find that colored scatterplots (with positionally‐coded quantities and color‐coded categories) perform well for comparing individual points, but perform poorly for summary tasks as the number of categories increases. | false | false | [
"Younghoon Kim",
"Jeffrey Heer"
] | [] | [] | [] |
EuroVis | 2,018 | Baseball Timeline: Summarizing Baseball Plays Into a Static Visualization | 10.1111/cgf.13436 | In sports, Play Diagrams are the standard way to represent and convey information. They are widely used by coaches, managers, journalists and fans in general. There are situations where diagrams may be hard to understand, for example, when several actions are packed in a certain region of the field or there are just too many actions to be transformed in a clear depiction of the play. The representation of how actions develop through time, in particular, may be hardly achieved on such diagrams. The time, and the relationship among the actions of the players through time, is critical on the depiction of complex plays. In this context, we present a study on how player actions may be clearly depicted on 2D diagrams. The study is focused on Baseball plays, a sport where diagrams are heavily used to summarize the actions of the players. We propose a new and simple approach to represent spatiotemporal information in the form of a timeline. We designed our visualization with a requirement driven approach, conducting interviews and fulfilling the needs of baseball experts and expert‐fans. We validate our approach by presenting a detailed analysis of baseball plays and conducting interviews with four domain experts. | false | false | [
"Jorge Piazentin Ono",
"Carlos A. Dietrich",
"Cláudio T. Silva"
] | [
"HM"
] | [] | [] |
EuroVis | 2,018 | Bladder Runner: Visual Analytics for the Exploration of RT-Induced Bladder Toxicity in a Cohort Study | 10.1111/cgf.13413 | We present the Bladder Runner, a novel tool to enable detailed visual exploration and analysis of the impact of bladder shape variation on the accuracy of dose delivery, during the course of prostate cancer radiotherapy (RT). Our tool enables the investigation of individual patients and cohorts through the entire treatment process, and it can give indications of RT‐induced complications for the patient. In prostate cancer RT treatment, despite the design of an initial plan prior to dose administration, bladder toxicity remains very common. The main reason is that the dose is delivered in multiple fractions over a period of weeks, during which, the anatomical variation of the bladder – due to differences in urinary filling – causes deviations between planned and delivered doses. Clinical researchers want to correlate bladder shape variations to dose deviations and toxicity risk through cohort studies, to understand which specific bladder shape characteristics are more prone to side effects. This is currently done with Dose‐Volume Histograms (DVHs), which provide limited, qualitative insight. The effect of bladder variation on dose delivery and the resulting toxicity cannot be currently examined with the DVHs. To address this need, we designed and implemented the Bladder Runner, which incorporates visualization strategies in a highly interactive environment with multiple linked views. Individual patients can be explored and analyzed through the entire treatment period, while inter‐patient and temporal exploration, analysis and comparison are also supported. We demonstrate the applicability of our presented tool with a usage scenario, employing a dataset of 29 patients followed through the course of the treatment, across 13 time points. We conducted an evaluation with three clinical researchers working on the investigation of RT‐induced bladder toxicity. All participants agreed that Bladder Runner provides better understanding and new opportunities for the exploration and analysis of the involved cohort data. | false | false | [
"Renata G. Raidou",
"Oscar Casares-Magaz",
"Artem Amirkhanov",
"Vitali Moiseenko",
"Ludvig P. Muren",
"John P. Einck",
"Anna Vilanova",
"M. Eduard Gröller"
] | [] | [] | [] |
EuroVis | 2,018 | CFGExplorer: Designing a Visual Control Flow Analytics System around Basic Program Analysis Operations | 10.1111/cgf.13433 | To develop new compilation and optimization techniques, computer scientists frequently Consult program analysis artifacts such as Control flow graphs (CFGs) and traces of executed instructions. A CFG is a directed graph representing possible execution paths in a program. CFGs are commonly visualized as node‐link diagrams while traces are commonly viewed in raw text format. Visualizing and exploring CFGs and traces is challenging because of the complexity and specificity of the operations researchers perform. We present a design study where we collaborate with computer scientists researching dynamic binary analysis and compilation techniques. The research group primarily employs CFGs and traces to reason about and develop new algorithms for program optimization and parallelization. Through questionnaires, interviews, and a year‐long observation, we analyzed their use of visualization, noting that the tasks they perform match common subroutines they employ in their techniques. Based on this task analysis, we designed CFGExplorer, a visual analytics system that supports computer scientists with interactions that are integrated with the program structure. We developed a domain‐specific graph modification to generate graph layouts that reflect program structure. CFGExplorer incorporates structures such as functions and loops, and uses the correspondence between CFGs and traces to support navigation. We further augment the system to highlight the output of program analysis techniques, facilitating exploration at a higher level. We evaluate the tool through guided sessions and semi‐structured interviews as well as deployment. Our collaborators have integrated CFGExplorer into their workflow and use it to reason about programs, develop and debug new algorithms, and share their findings. | false | false | [
"Sabin Devkota",
"Katherine E. Isaacs"
] | [] | [] | [] |
EuroVis | 2,018 | ChangeCatcher: Increasing Inter-author Awareness for Visualization Development | 10.1111/cgf.13400 | We introduce an approach for explicitly revealing changes between versions of a visualization workbook to support version comparison tasks. Visualization authors may need to understand version changes for a variety of reasons, analogous to document editing. An author who has been away for a while may need to catch up on the changes made by their co‐author, or a person responsible for formatting compliance may need to check formatting changes that occurred since the last time they reviewed the work. We introduce ChangeCatcher, a prototype tool to help people find and understand changes in a visualization workbook, specifically, a Tableau workbook. Our design is based on interviews we conducted with experts to investigate user needs and practices around version comparison. ChangeCatcher provides an overview of changes across six categories, and employs a multi‐level details‐on‐demand approach to progressively reveal details. Our qualitative study showed that ChangeCatcher's methods for explicitly revealing and categorizing version changes were helpful in version comparison tasks. | false | false | [
"Mona Hosseinkhani Loorak",
"Melanie Tory",
"Sheelagh Carpendale"
] | [] | [] | [] |
EuroVis | 2,018 | Chart Constellations: Effective Chart Summarization for Collaborative and Multi-User Analyses | 10.1111/cgf.13402 | Many data problems in the real world are complex and require multiple analysts working together to uncover embedded insights by creating chart‐driven data stories. How, as a subsequent analysis step, do we interpret and learn from these collections of charts? We present Chart Constellations, a system to interactively support a single analyst in the review and analysis of data stories created by other collaborative analysts. Instead of iterating through the individual charts for each data story, the analyst can project, cluster, filter, and connect results from all users in a meta‐visualization approach. Constellations supports deriving summary insights about prior investigations and supports the exploration of new, unexplored regions in the dataset. To evaluate our system, we conduct a user study comparing it against data science notebooks. Results suggest that Constellations promotes the discovery of both broad and high‐level insights, including theme and trend analysis, subjective evaluation, and hypothesis generation. | false | false | [
"Shenyu Xu",
"Chris Bryan",
"Jianping Kelvin Li",
"Jian Zhao 0010",
"Kwan-Liu Ma"
] | [] | [] | [] |
EuroVis | 2,018 | ConcaveCubes: Supporting Cluster-based Geographical Visualization in Large Data Scale | 10.1111/cgf.13414 | In this paper we study the problem of supporting effective and scalable visualization for the rapidly increasing volumes of urban data. From an extensive literature study, we find that the existing solutions suffer from at least one of the drawbacks below: (i) loss of interesting structures/outliers due to sampling; (ii) supporting heatmaps only, which provides limited information; and (iii) no notion of real‐world geography semantics (e.g., country, state, city) is captured in the visualization result as well as the underlying index. Therefore, we propose ConcaveCubes, a cluster‐based data cube to support interactive visualization of large‐scale multidimensional urban data. Specifically, we devise an appropriate visualization abstraction and visualization design based on clusters. We propose a novel concave hull construction method to support boundary based cluster map visualization, where real‐world geographical semantics are preserved without any information loss. Instead of calculating the clusters on demand, ConcaveCubes (re)utilizes existing calculation and visualization results to efficiently support different kinds of user interactions. We conduct extensive experiments using real‐world datasets and show the efficiency and effectiveness of ConcaveCubes by comparing with the state‐of‐the‐art cube‐based solutions. | false | false | [
"Mingzhao Li 0001",
"Farhana Murtaza Choudhury",
"Zhifeng Bao",
"Hanan Samet",
"Timos Sellis"
] | [] | [] | [] |
EuroVis | 2,018 | Core Lines in 3D Second-Order Tensor Fields | 10.1111/cgf.13423 | Vortices are important features in vector fields that show a swirling behavior around a common core. The concept of a vortex core line describes the center of this swirling behavior. In this work, we examine the extension of this concept to 3D second‐order tensor fields. Here, a behavior similar to vortices in vector fields can be observed for trajectories of the eigenvectors. Vortex core lines in vector fields were defined by Sujudi and Haimes to be the locations where stream lines are parallel to an eigenvector of the Jacobian. We show that a similar criterion applied to the eigenvector trajectories of a tensor field yields structurally stable lines that we call tensor core lines. We provide a formal definition of these structures and examine their mathematical properties. We also present a numerical algorithm for extracting tensor core lines in piecewise linear tensor fields. We find all intersections of tensor core lines with the faces of a dataset using a simple and robust root finding algorithm. Applying this algorithm to tensor fields obtained from structural mechanics simulations shows that it is able to effectively detect and visualize regions of rotational or hyperbolic behavior of eigenvector trajectories. | false | false | [
"Timo Oster",
"Christian Rössl",
"Holger Theisel"
] | [] | [] | [] |
EuroVis | 2,018 | Cosine-Weighted B-Spline Interpolation on the Face-Centered Cubic Lattice | 10.1111/cgf.13437 | Cosine‐Weighted B‐spline (CWB) interpolation [Csé13] has been originally proposed for volumetric data sampled on the Body‐Centered Cubic (BCC) lattice. The BCC lattice is well known to be optimal for sampling isotropically band‐limited signals above the Nyquist limit. However, the Face‐Centered Cubic (FCC) lattice has been recently proven to be optimal for low‐rate sampling. The CWB interpolation is a state‐of‐the‐art technique on the BCC lattice, which outperforms, for example, the previously proposed box‐spline interpolation in terms of both efficiency and visual quality. In this paper, we show that CWB interpolation can be adapted to the FCC lattice as well, and results in similarly isotropic signal reconstructions as on the BCC lattice. | false | false | [
"Gergely Rácz",
"Balázs Csébfalvi"
] | [] | [] | [] |
EuroVis | 2,018 | Design Factors for Summary Visualization in Visual Analytics | 10.1111/cgf.13408 | Data summarization allows analysts to explore datasets that may be too complex or too large to visualize in detail. Designers face a number of design and implementation choices when using summarization in visual analytics systems. While these choices influence the utility of the resulting system, there are no clear guidelines for the use of these summarization techniques. In this paper, we codify summarization use in existing systems to identify key factors in the design of summary visualizations. We use quantitative content analysis to systematically survey examples of visual analytics systems and enumerate the use of these design factors in data summarization. Through this analysis, we expose the relationship between design considerations, strategies for data summarization in visualization systems, and how different summarization methods influence the analyses supported by systems. We use these results to synthesize common patterns in real‐world use of summary visualizations and highlight open challenges and opportunities that these patterns offer for designing effective systems. This work provides a more principled understanding of design practices for summary visualization and offers insight into underutilized approaches. | false | false | [
"Alper Sarikaya",
"Michael Gleicher",
"Danielle Albers Szafir"
] | [] | [] | [] |
EuroVis | 2,018 | DimSUM: Dimension and Scale Unifying Map for Visual Abstraction of DNA Origami Structures | 10.1111/cgf.13429 | We present a novel visualization concept for DNA origami structures that integrates a multitude of representations into a Dimension and Scale Unifying Map (DimSUM). This novel abstraction map provides means to analyze, smoothly transition between, and interact with many visual representations of the DNA origami structures in an effective way that was not possible before. DNA origami structures are nanoscale objects, which are challenging to model in silico. In our holistic approach we seamlessly combine three‐dimensional realistic shape models, two‐dimensional diagrammatic representations, and ordered alignments in one‐dimensional arrangements, with semantic transitions across many scales. To navigate through this large, two‐dimensional abstraction map we highlight locations that users frequently visit for certain tasks and datasets. Particularly interesting viewpoints can be explicitly saved to optimize the workflow. We have developed DimSUM together with domain scientists specialized in DNA nanotechnology. In the paper we discuss our design decisions for both the visualization and the interaction techniques. We demonstrate two practical use cases in which our approach increases the specialists’ understanding and improves their effectiveness in the analysis. Finally, we discuss the implications of our concept for the use of controlled abstraction in visualization in general. | false | false | [
"Haichao Miao",
"Elisa De Llano",
"Tobias Isenberg 0001",
"M. Eduard Gröller",
"Ivan Barisic",
"Ivan Viola"
] | [] | [] | [] |
EuroVis | 2,018 | Explorative Blood Flow Visualization using Dynamic Line Filtering based on Surface Features | 10.1111/cgf.13411 | Rupture risk assessment is a key to devise patient‐specific treatment plans of cerebral aneurysms. To understand and predict the development of aneurysms and other vascular diseases over time, both hemodynamic flow patterns and their effect on the vessel surface need to be analyzed. Flow structures close to the vessel wall often correlate directly with local changes in surface parameters, such as pressure or wall shear stress. Yet, in many existing applications, the analyses of flow and surface features are either somewhat detached from one another or only globally available. Especially for the identification of specific blood flow characteristics that cause local startling parameters on the vessel surface, like elevated pressure values, an interactive analysis tool is missing.The explorative visualization of flow data is challenging due to the complexity of the underlying data. In order to find meaningful structures in the entirety of the flow, the data has to be filtered based on the respective explorative aim. In this paper, we present a combination of visualization, filtering and interaction techniques for explorative analysis of blood flow with a focus on the relation of local surface parameters and underlying flow structures. Coherent bundles of pathlines can be interactively selected based on their relation to features of the vessel wall and further refined based on their own hemodynamic features. This allows the user to interactively select and explore flow structures locally affecting a certain region on the vessel wall and therefore to understand the cause and effect relationship between these entities. Additionally, multiple selected flow structures can be compared with respect to their quantitative parameters, such as flow speed. We confirmed the usefulness of our approach by conducting an informal interview with two expert neuroradiologists and an expert in flow simulation. In addition, we recorded several insights the neuroradiologists were able to gain with the help of our tool. | false | false | [
"Benjamin Behrendt",
"Philipp Berg",
"Oliver Beuing",
"Bernhard Preim",
"Sylvia Saalfeld"
] | [] | [] | [] |
EuroVis | 2,018 | Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections | 10.1111/cgf.13416 | Two‐dimensional embeddings remain the dominant approach to visualize high dimensional data. The choice of embeddings ranges from highly non‐linear ones, which can capture complex relationships but are difficult to interpret quantitatively, to axis‐aligned projections, which are easy to interpret but are limited to bivariate relationships. Linear project can be considered as a compromise between complexity and interpretability, as they allow explicit axes labels, yet provide significantly more degrees of freedom compared to axis‐aligned projections. Nevertheless, interpreting the axes directions, which are often linear combinations of many non‐trivial components, remains difficult. To address this problem we introduce a structure aware decomposition of (multiple) linear projections into sparse sets of axis‐aligned projections, which jointly capture all information of the original linear ones. In particular, we use tools from Dempster‐Shafer theory to formally define how relevant a given axis‐aligned project is to explain the neighborhood relations displayed in some linear projection. Furthermore, we introduce a new approach to discover a diverse set of high quality linear projections and show that in practice the information of k linear projections is often jointly encoded in ∼ k axis‐aligned plots. We have integrated these ideas into an interactive visualization system that allows users to jointly browse both linear projections and their axis‐aligned representatives. Using a number of case studies we show how the resulting plots lead to more intuitive visualizations and new insights. | false | false | [
"Jayaraman J. Thiagarajan",
"Shusen Liu 0001",
"Karthikeyan Natesan Ramamurthy",
"Peer-Timo Bremer"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1712.07106v2",
"icon": "paper"
}
] |
EuroVis | 2,018 | Exploring the Visualization Design Space with Repertory Grids | 10.1111/cgf.13407 | There is an ongoing discussion in the visualization community about the relevant factors that render a visualization effective, expressive, memorable, aesthetically pleasing, etc. These factors lead to a large design space for visualizations. To explore this design space, qualitative research methods based on observations and interviews are often necessary. We describe an interview method that allows us to systematically acquire and assess important factors from subjective answers by interviewees. To this end, we adopt the repertory grid methodology in the context of visualization. It is based on the personal construct theory: each personality interprets a topic based on a set of personal, basic constructs expressed as contrasts. For the individual interpretation of visualizations, this means that these personal terms can be very different, depending on numerous influences, such as the prior experiences of the interviewed person. We present an interviewing process, visual interface, and qualitative and quantitative analysis procedures that are specifically devised to fit the needs of visualization applications. A showcase interview with 15 typical static information visualizations and 10 participants demonstrates that our approach is effective in identifying common constructs as well as individual differences. In particular, we investigate differences between expert and nonexpert interviewees. Finally, we discuss the differences to other qualitative methods and how the repertory grid can be embedded in existing theoretical frameworks of visualization research for the design process. | false | false | [
"Kuno Kurzhals",
"Daniel Weiskopf"
] | [
"HM"
] | [] | [] |
EuroVis | 2,018 | Fast and Accurate CNN-based Brushing in Scatterplots | 10.1111/cgf.13405 | Brushing plays a central role in most modern visual analytics solutions and effective and efficient techniques for data selection are key to establishing a successful human‐computer dialogue. With this paper, we address the need for brushing techniques that are both fast, enabling a fluid interaction in visual data exploration and analysis, and also accurate, i.e., enabling the user to effectively select specific data subsets, even when their geometric delimination is non‐trivial. We present a new solution for a near‐perfect sketch‐based brushing technique, where we exploit a convolutional neural network (CNN) for estimating the intended data selection from a fast and simple click‐and‐drag interaction and from the data distribution in the visualization. Our key contributions include a drastically reduced error rate—now below 3%, i.e., less than half of the so far best accuracy—and an extension to a larger variety of selected data subsets, going beyond previous limitations due to linear estimation models. | false | false | [
"Chaoran Fan",
"Helwig Hauser"
] | [] | [] | [] |
EuroVis | 2,018 | Hierarchical Correlation Clustering in Multiple 2D Scalar Fields | 10.1111/cgf.13396 | Sets of multiple scalar fields can be used to model many types of variation in data, such as uncertainty in measurements and simulations or time‐dependent behavior of scalar quantities. Many structural properties of such fields can be explained by dependencies between different points in the scalar field. Although these dependencies can be of arbitrary complexity, correlation, i.e., the linear dependency, already provides significant structural information. Existing methods for correlation analysis are usually limited to positive correlation, handle only local dependencies, or use combinatorial approximations to this continuous problem. We present a new approach for computing and visualizing correlated regions in sets of 2‐dimensional scalar fields. This paper describes the following three main contributions: (i) An algorithm for hierarchical correlation clustering resulting in a dendrogram, (ii) a generalization of topological landscapes for dendrogram visualization, and (iii) a new method for incorporating negative correlation values in the clustering and visualization. All steps are designed to preserve the special properties of correlation coefficients. The results are visualized in two linked views, one showing the cluster hierarchy as 2D landscape and the other providing a spatial context in the scalar field's domain. Different coloring and texturing schemes coupled with interactive selection support an exploratory data analysis. | false | false | [
"Tom Liebmann",
"Gunther H. Weber",
"Gerik Scheuermann"
] | [] | [] | [] |
EuroVis | 2,018 | Hunting High and Low: Visualising Shifting Correlations in Financial Markets | 10.1111/cgf.13435 | The analysis of financial assets’ correlations is fundamental to many aspects of finance theory and practice, especially modern portfolio theory and the study of risk. In order to manage investment risk, in‐depth analysis of changing correlations is needed, with both high and low correlations between financial assets (and groups thereof) important to identify. In this paper, we propose a visual analytics framework for the interactive analysis of relations and structures in dynamic, high‐dimensional correlation data. We conduct a series of interviews and review the financial correlation analysis literature to guide our design. Our solution combines concepts from multi‐dimensional scaling, weighted complete graphs and threshold networks to present interactive, animated displays which use proximity as a visual metaphor for correlation and animation stability to encode correlation stability. We devise interaction techniques coupled with context‐sensitive auxiliary views to support the analysis of subsets of correlation networks. As part of our contribution, we also present behaviour profiles to help guide future users of our approach. We evaluate our approach by checking the validity of the layouts produced, presenting a number of analysis stories, and through a user study. We observe that our solutions help unravel complex behaviours and resonate well with study participants in addressing their needs in the context of correlation analysis in finance. | false | false | [
"P. M. Simon",
"Cagatay Turkay"
] | [] | [] | [] |
EuroVis | 2,018 | Hypersliceplorer: Interactive visualization of shapes in multiple dimensions | 10.1111/cgf.13415 | In this paper we present Hypersliceplorer, an algorithm for generating 2D slices of multi‐dimensional shapes defined by a simplical mesh. Often, slices are generated by using a parametric form and then constraining parameters to view the slice. In our case, we developed an algorithm to slice a simplical mesh of any number of dimensions with a two‐dimensional slice. In order to get a global appreciation of the multi‐dimensional object, we show multiple slices by sampling a number of different slicing points and projecting the slices into a single view per dimension pair. These slices are shown in an interactive viewer which can switch between a global view (all slices) and a local view (single slice). We show how this method can be used to study regular polytopes, differences between spaces of polynomials, and multi‐objective optimization surfaces. | false | false | [
"Thomas Torsney-Weir",
"Torsten Möller",
"Michael Sedlmair",
"Robert M. Kirby"
] | [] | [] | [] |
EuroVis | 2,018 | Illustrative Multivariate Visualization for Geological Modelling | 10.1111/cgf.13434 | In this paper, we present a novel illustrative multivariate visualization for geological modelling to assist geologists and reservoir engineers in visualizing multivariate datasets in superimposed representations, in contrast to the single‐attribute visualizations supported by commercial software. Our approach extends the use of decals from a single surface to 3D irregular grids, using the layering concept to represent multiple attributes. We also build upon prior work to augment the design and implementation of different geological attributes (namely, rock type, porosity, and permeability). More specifically, we propose a new sampling strategy to generate decals for porosity on the geological grid, a hybrid visualization for permeability which combines 2D decals and 3D ellipsoid glyphs, and a perceptually‐based design that allows us to visualize additional attributes (e.g., oil saturation) while avoiding visual interference between layers. Furthermore, our visual design draws from traditional geological illustrations, facilitating the understanding and communication between interdisciplinary teams. An evaluation by domain experts highlights the potential of our approach for geological modelling and interpretation in this complex domain. | false | false | [
"Allan Rocha",
"Roberta C. Ramos Mota",
"Hamidreza Hamdi",
"Usman R. Alim",
"Mario Costa Sousa"
] | [] | [] | [] |
EuroVis | 2,018 | Information Visualization Evaluation Using Crowdsourcing | 10.1111/cgf.13444 | Visualization researchers have been increasingly leveraging crowdsourcing approaches to overcome a number of limitations of controlled laboratory experiments, including small participant sample sizes and narrow demographic backgrounds of study participants. However, as a community, we have little understanding on when, where, and how researchers use crowdsourcing approaches for visualization research. In this paper, we review the use of crowdsourcing for evaluation in visualization research. We analyzed 190 crowdsourcing experiments, reported in 82 papers that were published in major visualization conferences and journals between 2006 and 2017. We tagged each experiment along 36 dimensions that we identified for crowdsourcing experiments. We grouped our dimensions into six important aspects: study design & procedure, task type, participants, measures & metrics, quality assurance, and reproducibility. We report on the main findings of our review and discuss challenges and opportunities for improvements in conducting crowdsourcing studies for visualization research. | false | false | [
"Rita Borgo",
"Luana Micallef",
"Benjamin Bach",
"Fintan McGee",
"Bongshin Lee"
] | [] | [] | [] |
EuroVis | 2,018 | Interactive Analysis of Word Vector Embeddings | 10.1111/cgf.13417 | Word vector embeddings are an emerging tool for natural language processing. They have proven beneficial for a wide variety of language processing tasks. Their utility stems from the ability to encode word relationships within the vector space. Applications range from components in natural language processing systems to tools for linguistic analysis in the study of language and literature. In many of these applications, interpreting embeddings and understanding the encoded grammatical and semantic relations between words is useful, but challenging. Visualization can aid in such interpretation of embeddings. In this paper, we examine the role for visualization in working with word vector embeddings. We provide a literature survey to catalogue the range of tasks where the embeddings are employed across a broad range of applications. Based on this survey, we identify key tasks and their characteristics. Then, we present visual interactive designs that address many of these tasks. The designs integrate into an exploration and analysis environment for embeddings. Finally, we provide example use cases for them and discuss domain user feedback. | false | false | [
"Florian Heimerl",
"Michael Gleicher"
] | [] | [] | [] |
EuroVis | 2,018 | Interactive Investigation of Traffic Congestion on Fat-Tree Networks Using TreeScope | 10.1111/cgf.13442 | Parallel simulation codes often suffer from performance bottlenecks due to network congestion, leaving millions of dollars of investments underutilized. Given a network topology, it is critical to understand how different applications, job placements, routing schemes, etc., are affected by and contribute to network congestion, especially for large and complex networks. Understanding and optimizing communication on large‐scale networks is an active area of research. Domain experts often use exploratory tools to develop both intuitive and formal metrics for network health and performance. This paper presents TreeScope, an interactive, web‐based visualization tool for exploring network traffic on large‐scale fat‐tree networks. TreeScope encodes the network topology using a tailored matrix‐based representation and provides detailed visualization of all traffic in the network. We report on the design process of TreeScope, which has been received positively by network researchers as well as system administrators. Through case studies of real and simulated data, we demonstrate how TreeScope's visual design and interactive support for complex queries on network traffic can provide experts with new insights into the occurrences and causes of congestion in the network. | false | false | [
"Harsh Bhatia",
"Nikhil Jain",
"Abhinav Bhatele",
"Yarden Livnat",
"Jens Domke",
"Valerio Pascucci",
"Peer-Timo Bremer"
] | [] | [] | [] |
EuroVis | 2,018 | Interactive Visual Exploration of Local Patterns in Large Scatterplot Spaces | 10.1111/cgf.13404 | Analysts often use visualisation techniques like a scatterplot matrix (SPLOM) to explore multivariate datasets. The scatterplots of a SPLOM can help to identify and compare two‐dimensional global patterns. However, local patterns which might only exist within subsets of records are typically much harder to identify and may go unnoticed among larger sets of plots in a SPLOM. This paper explores the notion of local patterns and presents a novel approach to visually select, search for, and compare local patterns in a multivariate dataset. Model‐based and shape‐based pattern descriptors are used to automatically compare local regions in scatterplots to assist in the discovery of similar local patterns. Mechanisms are provided to assess the level of similarity between local patterns and to rank similar patterns effectively. Moreover, a relevance feedback module is used to suggest potentially relevant local patterns to the user. The approach has been implemented in an interactive tool and demonstrated with two real‐world datasets and use cases. It supports the discovery of potentially useful information such as clusters, functional dependencies between variables, and statistical relationships in subsets of data records and dimensions. | false | false | [
"Mohammad Chegini",
"Lin Shao 0001",
"Robert Gregor",
"Dirk J. Lehmann",
"Keith Andrews",
"Tobias Schreck"
] | [] | [] | [] |
EuroVis | 2,018 | Key Time Steps Selection for Large-Scale Time-Varying Volume Datasets Using an Information-Theoretic Storyboard | 10.1111/cgf.13399 | Key time steps selection is essential for effective and efficient scientific visualization of large‐scale time‐varying datasets. We present a novel approach that can decide the number of most representative time steps while selecting them to minimize the difference in the amount of information from the original data. We use linear interpolation to reconstruct the data of intermediate time steps between selected time steps. We propose an evaluation of selected time steps by computing the difference in the amount of information (called information difference) using variation of information (VI) from information theory, which compares the interpolated time steps against the original data. In the one‐time preprocessing phase, a dynamic programming is applied to extract the subset of time steps that minimize the information difference. In the run‐time phase, a novel chart is used to present the dynamic programming results, which serves as a storyboard of the data to guide the user to select the best time steps very efficiently. We extend our preprocessing approach to a novel out‐of‐core approximate algorithm to achieve optimal I/O cost, which also greatly reduces the in‐core computing time and exhibits a nice trade‐off between computing speed and accuracy. As shown in the experiments, our approximate method outperforms the previous globally optimal DTW approach [TLS12] on out‐of‐core data by significantly improving the running time while keeping similar qualities, and is our major contribution. | false | false | [
"Bo Zhou",
"Yi-Jen Chiang"
] | [] | [] | [] |
EuroVis | 2,018 | Landscaper: A Modeling System for 3D Printing Scale Models of Landscapes | 10.1111/cgf.13432 | Landscape models of geospatial regions provide an intuitive mechanism for exploring complex geospatial information. However, the methods currently used to create these scale models require a large amount of resources, which restricts the availability of these models to a limited number of popular public places, such as museums and airports. In this paper, we have proposed a system for creating these physical models using an affordable 3D printer in order to make the creation of these models more widely accessible. Our system retrieves GIS relevant to creating a physical model of a geospatial region and then addresses the two major limitations of affordable 3D printers, namely the limited number of materials and available printing volume. This is accomplished by separating features into distinct extruded layers and splitting large models into smaller pieces, allowing us to employ different methods for the visualization of different geospatial features, like vegetation and residential areas, in a 3D printing context. We confirm the functionality of our system by printing two large physical models of relatively complex landscape regions. | false | false | [
"K. Allahverdi",
"Hessam Djavaherpour",
"Ali Mahdavi-Amiri",
"Faramarz F. Samavati"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "https://osf.io/35evz",
"icon": "paper"
}
] |
EuroVis | 2,018 | Maps and Globes in Virtual Reality | 10.1111/cgf.13431 | This paper explores different ways to render world‐wide geographic maps in virtual reality (VR). We compare: (a) a 3D exocentric globe, where the user's viewpoint is outside the globe; (b) a flat map (rendered to a plane in VR); (c) an egocentric 3D globe, with the viewpoint inside the globe; and (d) a curved map, created by projecting the map onto a section of a sphere which curves around the user. In all four visualisations the geographic centre can be smoothly adjusted with a standard handheld VR controller and the user, through a head‐tracked headset, can physically move around the visualisation. For distance comparison exocentric globe is more accurate than egocentric globe and flat map. For area comparison more time is required with exocentric and egocentric globes than with flat and curved maps. For direction estimation, the exocentric globe is more accurate and faster than the other visual presentations. Our study participants had a weak preference for the exocentric globe. Generally the curved map had benefits over the flat map. In almost all cases the egocentric globe was found to be the least effective visualisation. Overall, our results provide support for the use of exocentric globes for geographic visualisation in mixed‐reality. | false | false | [
"Yalong Yang 0001",
"Bernhard Jenny",
"Tim Dwyer",
"Kim Marriott",
"Haohui Chen",
"Maxime Cordeil"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1908.02088v1",
"icon": "paper"
}
] |
EuroVis | 2,018 | Multiscale Visualization and Exploration of Large Bipartite Graphs | 10.1111/cgf.13441 | A bipartite graph is a powerful abstraction for modeling relationships between two collections. Visualizations of bipartite graphs allow users to understand the mutual relationships between the elements in the two collections, e.g., by identifying clusters of similarly connected elements. However, commonly‐used visual representations do not scale for the analysis of large bipartite graphs containing tens of millions of vertices, often resorting to an a‐priori clustering of the sets. To address this issue, we present the Who's‐Active‐On‐What‐Visualization (WAOW‐Vis) that allows for multiscale exploration of a bipartite social‐network without imposing an a‐priori clustering. To this end, we propose to treat a bipartite graph as a high‐dimensional space and we create the WAOW‐Vis adapting the multiscale dimensionality‐reduction technique HSNE. The application of HSNE for bipartite graph requires several modifications that form the contributions of this work. Given the nature of the problem, a set‐based similarity is proposed. For efficient and scalable computations, we use compressed bitmaps to represent sets and we present a novel space partitioning tree to efficiently compute similarities; the Sets Intersection Tree. Finally, we validate WAOW‐Vis on several datasets connecting Twitter‐users and ‐streams in different domains: news, computer science and politics. We show how WAOW‐Vis is particularly effective in identifying hierarchies of communities among social‐media users. | false | false | [
"Nicola Pezzotti",
"Jean-Daniel Fekete",
"Thomas Höllt",
"Boudewijn P. F. Lelieveldt",
"Elmar Eisemann",
"Anna Vilanova"
] | [] | [] | [] |
EuroVis | 2,018 | PixelSNE: Pixel-Aligned Stochastic Neighbor Embedding for Efficient 2D Visualization with Screen-Resolution Precision | 10.1111/cgf.13418 | Embedding and visualizing large‐scale high‐dimensional data in a two‐dimensional space is an important problem, because such visualization can reveal deep insights of complex data. However, most of the existing embedding approaches run on an excessively high precision, even when users want to obtain a brief insight from a visualization of large‐scale datasets, ignoring the fact that in the end, the outputs are embedded onto a fixed‐range pixel‐based screen space. Motivated by this observation and directly considering the properties of screen space in an embedding algorithm, we propose Pixel‐Aligned Stochastic Neighbor Embedding (PixelSNE), a highly efficient screen resolution‐driven 2D embedding method which accelerates Barnes‐Hut tree‐based t‐distributed stochastic neighbor embedding (BH‐SNE), which is known to be a state‐of‐the‐art 2D embedding method. Our experimental results show a significantly faster running time for PixelSNE compared to BH‐SNE for various datasets while maintaining comparable embedding quality. | false | false | [
"Minjeong Kim",
"Minsuk Choi",
"Sunwoong Lee",
"Jian Tang 0005",
"Haesun Park",
"Jaegul Choo"
] | [] | [] | [] |
EuroVis | 2,018 | Quality Metrics for Information Visualization | 10.1111/cgf.13446 | The visualization community has developed to date many intuitions and understandings of how to judge the quality of views in visualizing data. The computation of a visualization's quality and usefulness ranges from measuring clutter and overlap, up to the existence and perception of specific (visual) patterns. This survey attempts to report, categorize and unify the diverse understandings and aims to establish a common vocabulary that will enable a wide audience to understand their differences and subtleties. For this purpose, we present a commonly applicable quality metric formalization that should detail and relate all constituting parts of a quality metric. We organize our corpus of reviewed research papers along the data types established in the information visualization community: multi‐ and high‐dimensional, relational, sequential, geospatial and text data. For each data type, we select the visualization subdomains in which quality metrics are an active research field and report their findings, reason on the underlying concepts, describe goals and outline the constraints and requirements. One central goal of this survey is to provide guidance on future research opportunities for the field and outline how different visualization communities could benefit from each other by applying or transferring knowledge to their respective subdomain. Additionally, we aim to motivate the visualization community to compare computed measures to the perception of humans. | false | false | [
"Michael Behrisch 0001",
"Michael Blumenschein",
"Nam Wook Kim",
"Lin Shao 0001",
"Mennatallah El-Assady",
"Johannes Fuchs 0001",
"Daniel Seebacher",
"Alexandra Diehl",
"Ulrik Brandes",
"Hanspeter Pfister",
"Tobias Schreck",
"Daniel Weiskopf",
"Daniel A. Keim"
] | [] | [] | [] |
EuroVis | 2,018 | Rendering and Extracting Extremal Features in 3D Fields | 10.1111/cgf.13439 | Visualizing and extracting three‐dimensional features is important for many computational science applications, each with their own feature definitions and data types. While some are simple to state and implement (e.g. isosurfaces), others require more complicated mathematics (e.g. multiple derivatives, curvature, eigenvectors, etc.). Correctly implementing mathematical definitions is difficult, so experimenting with new features requires substantial investments. Furthermore, traditional interpolants rarely support the necessary derivatives, and approximations can reduce numerical stability. Our new approach directly translates mathematical notation into practical visualization and feature extraction, with minimal mental and implementation overhead. Using a mathematically expressive domain‐specific language, Diderot, we compute direct volume renderings and particle‐based feature samplings for a range of mathematical features. Non‐expert users can experiment with feature definitions without any exposure to meshes, interpolants, derivative computation, etc. We demonstrate high‐quality results on notoriously difficult features, such as ridges and vortex cores, using working code simple enough to be presented in its entirety. | false | false | [
"Gordon L. Kindlmann",
"Charisee Chiw",
"T. Huynh",
"Attila Gyulassy",
"John H. Reppy",
"Peer-Timo Bremer"
] | [
"BP"
] | [] | [] |
EuroVis | 2,018 | Representative Consensus from Limited-Size Ensembles | 10.1111/cgf.13397 | Characterizing the uncertainty and extracting reliable visual information from ensemble data have been persistent challenges in various disciplines, specifically in simulation sciences. Many ensemble analysis and visualization techniques take a probabilistic approach to this problem with the assumption that the ensemble size is large enough to extract reliable statistical or probabilistic summaries. However, many real‐life ensembles are rather limited in size, with only a handful of members, due to various restrictions such as storage, computational power, or sampling limitations. As a result, probabilistic inference is subject to imprecision and can potentially result in untrustworthy information in the presence of a limited sample‐size ensemble. In this case, a more reliable approach is to fuse the information present in an ensemble with a limited number of members with minimal assumptions. In this paper, we propose a technique to construct a representative consensus that is particularly suited for ensembles of a relatively small size. The proposed technique casts the problem as an ordering problem in which at each point in the domain, the ensemble members are ranked based on the local neighborhood. This local approach allows us to provide shape and irregularity sensitivity. The local order statistics will then be fused to construct a global consensus using a Bayesian approach to ensure spatial coherency of the local information. We demonstrate the utility of the proposed technique using a synthetic and two real‐life examples. | false | false | [
"Mahsa Mirzargar",
"Ross T. Whitaker"
] | [] | [] | [] |
EuroVis | 2,018 | SetCoLa: High-Level Constraints for Graph Layout | 10.1111/cgf.13440 | Constraints enable flexible graph layout by combining the ease of automatic layout with customizations for a particular domain. However, constraint‐based layout often requires many individual constraints defined over specific nodes and node pairs. In addition to the effort of writing and maintaining a large number of similar constraints, such constraints are specific to the particular graph and thus cannot generalize to other graphs in the same domain. To facilitate the specification of customized and generalizable constraint layouts, we contribute SetCoLa: a domain‐specific language for specifying high‐level constraints relative to properties of the backing data. Users identify node sets based on data or graph properties and apply high‐level constraints within each set. Applying constraints to node sets rather than individual nodes reduces specification effort and facilitates reapplication of customized layouts across distinct graphs. We demonstrate the conciseness, generalizability, and expressiveness of SetCoLa on a series of real‐world examples from ecological networks, biological systems, and social networks. | false | false | [
"Jane Hoffswell",
"Alan Borning",
"Jeffrey Heer"
] | [] | [] | [] |
EuroVis | 2,018 | Spatio-Temporal Contours from Deep Volume Raycasting | 10.1111/cgf.13438 | We visualize contours for spatio‐temporal processes to indicate where and when non‐continuous changes occur or spatial bounds are encountered. All time steps are comprised densely in one visualization, with contours allowing to efficiently analyze processes in the data even in case of spatial or temporal overlap. Contours are determined on the basis of deep raycasting that collects samples across time and depth along each ray. For each sample along a ray, its closest neighbors from adjacent rays are identified, considering time, depth, and value in the process. Large distances are represented as contours in image space, using color to indicate temporal occurrence. This contour representation can easily be combined with volume rendering‐based techniques, providing both full spatial detail for individual time steps and an outline of the whole time series in one view. Our view‐dependent technique supports efficient progressive computation, and requires no prior assumptions regarding the shape or nature of processes in the data. We discuss and demonstrate the performance and utility of our approach via a variety of data sets, comparison and combination with an alternative technique, and feedback by a domain scientist. | false | false | [
"Steffen Frey"
] | [] | [] | [] |
EuroVis | 2,018 | State of the Art of Sports Data Visualization | 10.1111/cgf.13447 | In this report, we organize and reflect on recent advances and challenges in the field of sports data visualization. The exponentially‐growing body of visualization research based on sports data is a prime indication of the importance and timeliness of this report. Sports data visualization research encompasses the breadth of visualization tasks and goals: exploring the design of new visualization techniques; adapting existing visualizations to a novel domain; and conducting design studies and evaluations in close collaboration with experts, including practitioners, enthusiasts, and journalists. Frequently this research has impact beyond sports in both academia and in industry because it is i) grounded in realistic, highly heterogeneous data, ii) applied to real‐world problems, and iii) designed in close collaboration with domain experts. In this report, we analyze current research contributions through the lens of three categories of sports data: box score data (data containing statistical summaries of a sport event such as a game), tracking data (data about in‐game actions and trajectories), and meta‐data (data about the sport and its participants but not necessarily a given game). We conclude this report with a high‐level discussion of sports visualization research informed by our analysis—identifying critical research gaps and valuable opportunities for the visualization community. More information is available at the STAR's website: https://sportsdataviz.github.io/. | false | false | [
"Charles Perin",
"Romain Vuillemot",
"Charles D. Stolper",
"John T. Stasko",
"Jo Wood",
"Sheelagh Carpendale"
] | [] | [] | [] |
EuroVis | 2,018 | The Perception of Graph Properties in Graph Layouts | 10.1111/cgf.13410 | When looking at drawings of graphs, questions about graph density, community structures, local clustering and other graph properties may be of critical importance for analysis. While graph layout algorithms have focused on minimizing edge crossing, symmetry, and other such layout properties, there is not much known about how these algorithms relate to a user's ability to perceive graph properties for a given graph layout. In this study, we apply previously established methodologies for perceptual analysis to identify which graph drawing layout will help the user best perceive a particular graph property. We conduct a large scale (n = 588) crowdsourced experiment to investigate whether the perception of two graph properties (graph density and average local clustering coefficient) can be modeled using Weber's law. We study three graph layout algorithms from three representative classes (Force Directed ‐ FD, Circular, and Multi‐Dimensional Scaling ‐ MDS), and the results of this experiment establish the precision of judgment for these graph layouts and properties. Our findings demonstrate that the perception of graph density can be modeled with Weber's law. Furthermore, the perception of the average clustering coefficient can be modeled as an inverse of Weber's law, and the MDS layout showed a significantly different precision of judgment than the FD layout. | false | false | [
"Utkarsh Soni",
"Yafeng Lu",
"Brett Hansen",
"Helen C. Purchase",
"Stephen G. Kobourov",
"Ross Maciejewski"
] | [] | [] | [] |
EuroVis | 2,018 | ThreadReconstructor: Modeling Reply-Chains to Untangle Conversational Text through Visual Analytics | 10.1111/cgf.13425 | We present ThreadReconstructor, a visual analytics approach for detecting and analyzing the implicit conversational structure of discussions, e.g., in political debates and forums. Our work is motivated by the need to reveal and understand single threads in massive online conversations and verbatim text transcripts. We combine supervised and unsupervised machine learning models to generate a basic structure that is enriched by user‐defined queries and rule‐based heuristics. Depending on the data and tasks, users can modify and create various reconstruction models that are presented and compared in the visualization interface. Our tool enables the exploration of the generated threaded structures and the analysis of the untangled reply‐chains, comparing different models and their agreement. To understand the inner‐workings of the models, we visualize their decision spaces, including all considered candidate relations. In addition to a quantitative evaluation, we report qualitative feedback from an expert user study with four forum moderators and one machine learning expert, showing the effectiveness of our approach. | false | false | [
"Mennatallah El-Assady",
"Rita Sevastjanova",
"Daniel A. Keim",
"Christopher Collins 0001"
] | [] | [] | [] |
EuroVis | 2,018 | Time Lattice: A Data Structure for the Interactive Visual Analysis of Large Time Series | 10.1111/cgf.13398 | Advances in technology coupled with the availability of low‐cost sensors have resulted in the continuous generation of large time series from several sources. In order to visually explore and compare these time series at different scales, analysts need to execute online analytical processing (OLAP) queries that include constraints and group‐by's at multiple temporal hierarchies. Effective visual analysis requires these queries to be interactive. However, while existing OLAP cube‐based structures can support interactive query rates, the exponential memory requirement to materialize the data cube is often unsuitable for large data sets. Moreover, none of the recent space‐efficient cube data structures allow for updates. Thus, the cube must be re‐computed whenever there is new data, making them impractical in a streaming scenario. We propose Time Lattice, a memory‐efficient data structure that makes use of the implicit temporal hierarchy to enable interactive OLAP queries over large time series. Time Lattice is a subset of a fully materialized cube and is designed to handle fast updates and streaming data. We perform an experimental evaluation which shows that the space efficiency of the data structure does not hamper its performance when compared to the state of the art. In collaboration with signal processing and acoustics research scientists, we use the Time Lattice data structure to design the Noise Profiler, a web‐based visualization framework that supports the analysis of noise from cities. We demonstrate the utility of Noise Profiler through a set of case studies. | false | false | [
"Fabio Miranda 0001",
"Marcos Lage",
"Harish Doraiswamy",
"Charlie Mydlarz",
"Justin Salamon",
"Yitzchak Lockerman",
"Juliana Freire",
"Cláudio T. Silva"
] | [] | [] | [] |
EuroVis | 2,018 | Towards Easy Comparison of Local Businesses Using Online Reviews | 10.1111/cgf.13401 | With the rapid development of e‐commerce, there is an increasing number of online review websites, such as Yelp, to help customers make better purchase decisions. Viewing online reviews, including the rating score and text comments by other customers, and conducting a comparison between different businesses are the key to making an optimal decision. However, due to the massive amount of online reviews, the potential difference of user rating standards, and the significant variance of review time, length, details and quality, it is difficult for customers to achieve a quick and comprehensive comparison. In this paper, we present E‐Comp, a carefully‐designed visual analytics system based on online reviews, to help customers compare local businesses at different levels of details. More specifically, intuitive glyphs overlaid on maps are designed for quick candidate selection. Grouped Sankey diagram visualizing the rating difference by common customers is chosen for more reliable comparison of two businesses. Augmented word cloud showing adjective‐noun word pairs, combined with a temporal view, is proposed to facilitate in‐depth comparison of businesses in terms of different time periods, rating scores and features. The effectiveness and usability of E‐Comp are demonstrated through a case study and in‐depth user interviews. | false | false | [
"Yong Wang 0021",
"Hammad Haleem",
"Conglei Shi",
"Yanhong Wu",
"Xun Zhao",
"Siwei Fu",
"Huamin Qu"
] | [] | [] | [] |
EuroVis | 2,018 | Towards User-Centered Active Learning Algorithms | 10.1111/cgf.13406 | The labeling of data sets is a time‐consuming task, which is, however, an important prerequisite for machine learning and visual analytics. Visual‐interactive labeling (VIAL) provides users an active role in the process of labeling, with the goal to combine the potentials of humans and machines to make labeling more efficient. Recent experiments showed that users apply different strategies when selecting instances for labeling with visual‐interactive interfaces. In this paper, we contribute a systematic quantitative analysis of such user strategies. We identify computational building blocks of user strategies, formalize them, and investigate their potentials for different machine learning tasks in systematic experiments. The core insights of our experiments are as follows. First, we identified that particular user strategies can be used to considerably mitigate the bootstrap (cold start) problem in early labeling phases. Second, we observed that they have the potential to outperform existing active learning strategies in later phases. Third, we analyzed the identified core building blocks, which can serve as the basis for novel selection strategies. Overall, we observed that data‐based user strategies (clusters, dense areas) work considerably well in early phases, while model‐based user strategies (e.g., class separation) perform better during later phases. The insights gained from this work can be applied to develop novel active learning approaches as well as to better guide users in visual interactive labeling. | false | false | [
"Jürgen Bernard",
"Matthias Zeppelzauer",
"Markus Lehmann",
"Martin Müller",
"Michael Sedlmair"
] | [] | [] | [] |
EuroVis | 2,018 | Track Xplorer: A System for Visual Analysis of Sensor-based Motor Activity Predictions | 10.1111/cgf.13424 | With the rapid commoditization of wearable sensors, detecting human movements from sensor datasets has become increasingly common over a wide range of applications. To detect activities, data scientists iteratively experiment with different classifiers before deciding which model to deploy. Effective reasoning about and comparison of alternative classifiers are crucial in successful model development. This is, however, inherently difficult in developing classifiers for sensor data, where the intricacy of long temporal sequences, high prediction frequency, and imprecise labeling make standard evaluation methods relatively ineffective and even misleading.We introduce Track Xplorer, an interactive visualization system to query, analyze, and compare the predictions of sensor‐data classifiers. Track Xplorer enables users to interactively explore and compare the results of different classifiers, and assess their accuracy with respect to the ground‐truth labels and video. Through integration with a version control system, Track Xplorer supports tracking of models and their parameters without additional workload on model developers. Track Xplorer also contributes an extensible algebra over track representations to filter, compose, and compare classification outputs, enabling users to reason effectively about classifier performance. We apply Track Xplorer in a collaborative project to develop classifiers to detect movements from multisensor data gathered from Parkinson's disease patients. We demonstrate how Track Xplorer helps identify early on possible systemic data errors, effectively track and compare the results of different classifiers, and reason about and pinpoint the causes of misclassifications. | false | false | [
"Marco Cavallo",
"Çagatay Demiralp"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1710.01832v2",
"icon": "paper"
}
] |
EuroVis | 2,018 | VirtualDesk: A Comfortable and Efficient Immersive Information Visualization Approach | 10.1111/cgf.13430 | 3D representations are potentially useful under many circumstances, but suffer from long known perception and interaction challenges. Current immersive technologies, which combine stereoscopic displays and natural interaction, are being progressively seen as an opportunity to tackle this issue, but new guidelines and studies are still needed, especially regarding information visualization. Many proposed approaches are impractical for actual usage, resulting in user discomfort or requiring too much time or space. In this work, we implement and evaluate an alternative data exploration metaphor where the user remains seated and viewpoint change is only realisable through physical movements. All manipulation is done directly by natural mid‐air gestures, with the data being rendered at arm's reach. The virtual reproduction of the analyst's desk aims to increase immersion and enable tangible interaction with controls and two dimensional associated information. A comparative user study was carried out against a desktop‐based equivalent, exploring a set of 9 perception and interaction tasks based on previous literature and a multidimensional projection use case. We demonstrate that our prototype setup, named VirtualDesk, presents excellent results regarding user comfort and immersion, and performs equally or better in all analytical tasks, while adding minimal or no time overhead and amplifying user subjective perceptions of efficiency and engagement. Results are also contrasted to a previous experiment employing artificial flying navigation, with significant observed improvements. | false | false | [
"Jorge A. Wagner Filho",
"Carla Maria Dal Sasso Freitas",
"Luciana P. Nedel"
] | [] | [] | [] |
EuroVis | 2,018 | Visual Analysis of protein-ligand interactions | 10.1111/cgf.13428 | The analysis of protein‐ligand interactions is complex because of the many factors at play. Most current methods for visual analysis provide this information in the form of simple 2D plots, which, besides being quite space hungry, often encode a low number of different properties. In this paper we present a system for compact 2D visualization of molecular simulations. It purposely omits most spatial information and presents physical information associated to single molecular components and their pairwise interactions through a set of 2D InfoVis tools with coordinated views, suitable interaction, and focus+context techniques to analyze large amounts of data. The system provides a wide range of motifs for elements such as protein secondary structures or hydrogen bond networks, and a set of tools for their interactive inspection, both for a single simulation and for comparing two different simulations. As a result, the analysis of protein‐ligand interactions of Molecular Simulation trajectories is greatly facilitated. | false | false | [
"Pere-Pau Vázquez",
"Pedro Hermosilla",
"Victor Guallar",
"Jorge Estrada",
"Àlvar Vinacua"
] | [] | [] | [] |
EuroVis | 2,018 | Visual and quantitative analysis of great arteries' blood flow jets in cardiac 4D PC-MRI data | 10.1111/cgf.13412 | Flow in the great arteries (aorta, pulmonary artery) is normally laminar with a parabolic velocity profile. Eccentric flow jets are linked to various diseases like aneurysms. Cardiac 4D PC‐MRI data provide spatio‐temporally resolved blood flow information for the whole cardiac cycle. In this work, we establish a time‐dependent visualization and quantification of flow jets. For this purpose, equidistant measuring planes are automatically placed along the vessel's centerline. The flow jet position and region with highest velocities are extracted for every plane in each time step. This is done during pre‐processing and without user‐defined parameters. We visualize the main flow jet as geometric tube. High‐velocity areas are depicted as a net around this tube. Both geometries are time‐dependent and can be animated. Quantitative values are provided during cross‐sectional measuring plane‐based evaluation. Moreover, we offer a plot visualization as summary of flow jet characteristics for the selected plane. Our physiologically plausible results are in accordance with medical findings. Our clinical collaborators appreciate the possibility to view the flow jet in the whole vessel at once, which normally requires repeated pathline filtering due to varying velocities along the vessel course. The overview plots are considered as valuable for documentation purposes. | false | false | [
"Benjamin Köhler 0001",
"Matthias Grothoff",
"Matthias Gutberlet",
"Bernhard Preim"
] | [] | [] | [] |
EuroVis | 2,018 | Visualization of 4D Vector Field Topology | 10.1111/cgf.13421 | In this paper, we present an approach to the topological analysis of four‐dimensional vector fields. In analogy to traditional 2D and 3D vector field topology, we provide a classification and visual representation of critical points, together with a technique for extracting their invariant manifolds. For effective exploration of the resulting four‐dimensional structures, we present a 4D camera that provides concise representation by exploiting projection degeneracies, and a 4D clipping approach that avoids self‐intersection in the 3D projection. We exemplify the properties and the utility of our approach using specific synthetic cases. | false | false | [
"Lutz Hofmann",
"Bastian Rieck",
"Filip Sadlo"
] | [] | [] | [] |
EuroVis | 2,018 | Visualizing Expanded Query Results | 10.1111/cgf.13403 | When performing queries in web search engines, users often face difficulties choosing appropriate query terms. Search engines therefore usually suggest a list of expanded versions of the user query to disambiguate it or to resolve potential term mismatches. However, it has been shown that users find it difficult to choose an expanded query from such a list. In this paper, we describe the adoption of set‐based text visualization techniques to visualize how query expansions enrich the result space of a given user query and how the result sets relate to each other. Our system uses a linguistic approach to expand queries and topic modeling to extract the most informative terms from the results of these queries. In a user study, we compare a common text list of query expansion suggestions to three set‐based text visualization techniques adopted for visualizing expanded query results – namely, Compact Euler Diagrams, Parallel Tag Clouds, and a List View – to resolve ambiguous queries using interactive query expansion. Our results show that text visualization techniques do not increase retrieval efficiency, precision, or recall. Overall, users rate Parallel Tag Clouds visualizing key terms of the expanded query space lowest. Based on the results, we derive recommendations for visualizations of query expansion results, text visualization techniques in general, and discuss alternative use cases of set‐based text visualization techniques in the context of web search. | false | false | [
"Michael Mazurek",
"Manuela Waldner"
] | [] | [] | [] |
EuroVis | 2,018 | Visualizing Multidimensional Data with Order Statistics | 10.1111/cgf.13419 | Multidimensional data sets are common in many domains, and dimensionality reduction methods that determine a lower dimensional embedding are widely used for visualizing such data sets. This paper presents a novel method to project data onto a lower dimensional space by taking into account the order statistics of the individual data points, which are quantified by their depth or centrality in the overall set. Thus, in addition to conveying relative distances in the data, the proposed method also preserves the order statistics, which are often lost or misrepresented by existing visualization methods. The proposed method entails a modification of the optimization objective of conventional multidimensional scaling (MDS) by introducing a term that penalizes discrepancies between centrality structures in the original space and the embedding. We also introduce two strategies for visualizing lower dimensional embeddings of multidimensional data that takes advantage of the coherent representation of centrality provided by the proposed projection method. We demonstrate the effectiveness of our visualization with comparisons on different kinds of multidimensional data, including categorical and multimodal, from a variety of domains such as botany and health care. | false | false | [
"Mukund Raj",
"Ross T. Whitaker"
] | [] | [] | [] |
EuroVis | 2,018 | Visualizing the Phase Space of Heterogeneous Inertial Particles in 2D Flows | 10.1111/cgf.13420 | In many scientific disciplines, the motion of finite‐sized objects in fluid flows plays an important role, such as in brownout engineering, sediment transport, oceanology or meteorology. These finite‐sized objects are called inertial particles and, in contrast to traditional tracer particles, their motion depends on their current position, their own particle velocity, the time and their size. Thus, the visualization of their motion becomes a high‐dimensional problem that entails computational and perceptual challenges. So far, no visualization explored and visualized the particle trajectories under variation of all seeding parameters. In this paper, we propose three coordinated views that visualize the different aspects of the high‐dimensional space in which the particles live. We visualize the evolution of particles over time, showing that particles travel different distances in the same time, depending on their size. The second view provides a clear illustration of the trajectories of different particle sizes and allows the user to easily identify differences due to particle size. Finally, we embed the trajectories in the space‐velocity domain and visualize their distance to an attracting manifold using ribbons. In all views, we support interactive linking and brushing, and provide abstraction through density volumes that are shown by direct volume rendering and isosurface slabs. Using our method, users gain deeper insights into the dynamics of inertial particles in 2D fluids, including size‐dependent separation, preferential clustering and attraction. We demonstrate the effectiveness of our method in multiple steady and unsteady 2D flows. | false | false | [
"Irene Baeza Rojo",
"Markus H. Gross",
"Tobias Günther"
] | [] | [] | [] |
CHI | 2,018 | A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration | 10.1145/3173574.3174209 | Dimensionality reduction is a common method for analyzing and visualizing high-dimensional data. However, reasoning dynamically about the results of a dimensionality reduction is difficult. Dimensionality-reduction algorithms use complex optimizations to reduce the number of dimensions of a dataset, but these new dimensions often lack a clear relation to the initial data dimensions, thus making them difficult to interpret. Here we propose a visual interaction framework to improve dimensionality-reduction based exploratory data analysis. We introduce two interaction techniques, forward projection and backward projection, for dynamically reasoning about dimensionally reduced data. We also contribute two visualization techniques, prolines and feasibility maps, to facilitate the effective use of the proposed interactions. We apply our framework to PCA and autoencoder-based dimensionality reductions. Through data-exploration examples, we demonstrate how our visual interactions can improve the use of dimensionality reduction in exploratory data analysis. | false | false | [
"Marco Cavallo",
"Çagatay Demiralp"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1811.12199v1",
"icon": "paper"
}
] |
CHI | 2,018 | An Eye For Design: Gaze Visualizations for Remote Collaborative Work | 10.1145/3173574.3173923 | In remote collaboration, gaze visualizations are designed to display where collaborators are looking in a shared visual space. This type of gaze-based intervention can improve coordination, however researchers have yet to fully explore different gaze visualization techniques and develop a deeper understanding of the ways in which features of visualizations may interact with task attributes to influence collaborative performance. There are many ways to visualize characteristics of eye movements, such as a path connecting fixation points or a heat map illustrating fixation duration and coverage. In this study, we designed and evaluated three unique gaze visualizations in a remote search task. Our results suggest that the design of gaze visualizations affects performance, coordination, searching behavior, and perceived utility. Additionally, the degree of task coupling further influences the effect of gaze visualizations on performance and coordination. We then reflect on the value of gaze visualizations for remote work and discuss implications for the design of gaze-based interventions. | false | false | [
"Sarah D'Angelo",
"Darren Gergle"
] | [] | [] | [] |
CHI | 2,018 | Animated Edge Textures in Node-Link Diagrams: a Design Space and Initial Evaluation | 10.1145/3173574.3173761 | Network edge data attributes are usually encoded using color, opacity, stroke thickness and stroke pattern, or some combination thereof. In addition to these static variables, it is also possible to animate dynamic particles flowing along the edges. This opens a larger design space of animated edge textures, featuring additional visual encodings that have potential not only in terms of visual mapping capacity but also playfulness and aesthetics. Such animated edge textures have been used in several commercial and design-oriented visualizations, but to our knowledge almost always in a relatively ad hoc manner. We introduce a design space and Web-based framework for generating animated edge textures, and report on an initial evaluation of particle properties - particle speed, pattern and frequency - in terms of visual perception. | false | false | [
"Hugo Romat",
"Caroline Appert",
"Benjamin Bach",
"Nathalie Henry Riche",
"Emmanuel Pietriga"
] | [] | [] | [] |
CHI | 2,018 | Augmenting Code with In Situ Visualizations to Aid Program Understanding | 10.1145/3173574.3174106 | Programmers must draw explicit connections between their code and runtime state to properly assess the correctness of their programs. However, debugging tools often decouple the program state from the source code and require explicitly invoked views to bridge the rift between program editing and program understanding. To unobtrusively reveal runtime behavior during both normal execution and debugging, we contribute techniques for visualizing program variables directly within the source code. We describe a design space and placement criteria for embedded visualizations. We evaluate our in situ visualizations in an editor for the Vega visualization grammar. Compared to a baseline development environment, novice Vega users improve their overall task grade by about 2 points when using the in situ visualizations and exhibit significant positive effects on their self-reported speed and accuracy. | false | false | [
"Jane Hoffswell",
"Arvind Satyanarayan",
"Jeffrey Heer"
] | [] | [] | [] |
CHI | 2,018 | Beagle: Automated Extraction and Interpretation of Visualizations from the Web | 10.1145/3173574.3174168 | "How common is interactive visualization on the web?" "What is the most popular visualization design?" "How prevalent are pie charts really?" These questions intimate the role of interactive visualization in the real (online) world. In this paper, we present our approach (and findings) to answering these questions. First, we introduce Beagle, which mines the web for SVG-based visualizations and automatically classifies them by type (i.e., bar, pie, etc.). With Beagle, we extract over 41,000 visualizations across five different tools and repositories, and classify them with 85% accuracy, across 24 visualization types. Given this visualization collection, we study usage across tools. We find that most visualizations fall under four types: bar charts, line charts, scatter charts, and geographic maps. Though controversial, pie charts are relatively rare for the visualization tools that were studied. Our findings also suggest that the total visualization types supported by a given tool could factor into its ease of use. However this effect appears to be mitigated by providing a variety of diverse expert visualization examples to users. | false | false | [
"Leilani Battle",
"Peitong Duan",
"Zachery Miranda",
"Dana Mukusheva",
"Remco Chang",
"Michael Stonebraker"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1711.05962v1",
"icon": "paper"
}
] |
CHI | 2,018 | c.light: A Tool for Exploring Light Properties in Early Design Stage | 10.1145/3173574.3174176 | Although a light becomes an important design element, there are little techniques available to explore shapes and light effects in early design stages. We present c.light, a design tool that consists of a set of modules and a mobile application for visualizing the light in a physical world. It allows designers to easily fabricate both tangible and intangible properties of a light without a technical barrier. We analyzed how c.light contributes to the ideation process of light design through a workshop. The results showed that c.light largely expands designers' capability to manipulate intangible properties of light and, by doing so, it facilitates collaborative and inverted ideation process in early design stages. It is expected that the results of this study could enhance our understanding of how designers manipulate light in a physical world in early design stages and could be a good stepping stone for future tool development. | false | false | [
"Kyeong-Ah Jeong",
"EunJin Kim",
"Taesu Kim",
"Hyeon-Jeong Suk"
] | [] | [] | [] |
CHI | 2,018 | Clusters, Trends, and Outliers: How Immersive Technologies Can Facilitate the Collaborative Analysis of Multidimensional Data | 10.1145/3173574.3173664 | Immersive technologies such as augmented reality devices are opening up a new design space for the visual analysis of data. This paper studies the potential of an augmented reality environment for the purpose of collaborative analysis of multidimensional, abstract data. We present ART, a collaborative analysis tool to visualize multidimensional data in augmented reality using an interactive, 3D parallel coordinates visualization. The visualization is anchored to a touch-sensitive tabletop, benefiting from well-established interaction techniques. The results of group-based, expert walkthroughs show that ART can facilitate immersion in the data, a fluid analysis process, and collaboration. Based on the results, we provide a set of guidelines and discuss future research areas to foster the development of immersive technologies as tools for the collaborative analysis of multidimensional data. | false | false | [
"Simon Butscher",
"Sebastian Hubenschmid",
"Jens Müller 0001",
"Johannes Fuchs 0001",
"Harald Reiterer"
] | [] | [] | [] |
CHI | 2,018 | Considering Agency and Data Granularity in the Design of Visualization Tools | 10.1145/3173574.3174212 | Previous research has identified trade-offs when it comes to designing visualization tools. While constructive "bottom-up' tools promote a hands-on, user-driven design process that enables a deep understanding and control of the visual mapping, automated tools are more efficient and allow people to rapidly explore complex alternative designs, often at the cost of transparency. We investigate how to design visualization tools that support a user-driven, transparent design process while enabling efficiency and automation, through a series of design workshops that looked at how both visualization experts and novices approach this problem. Participants produced a variety of solutions that range from example-based approaches expanding constructive visualization to solutions in which the visualization tool infers solutions on behalf of the designer, e.g., based on data attributes. On a higher level, these findings highlight agency and granularity as dimensions that can guide the design of visualization tools in this space. | false | false | [
"Gonzalo Gabriel Méndez",
"Miguel A. Nacenta",
"Uta Hinrichs"
] | [] | [] | [] |
CHI | 2,018 | CraftML: 3D Modeling is Web Programming | 10.1145/3173574.3174101 | We explore web programming as a new paradigm for programmatic 3D modeling. Most existing approaches subscribe to the imperative programming paradigm. While useful, there exists a gulf of evaluation between procedural steps and the intended structure. We present CraftML, a language providing a declarative syntax where the code is the structure. CraftML offers a rich set of programming features familiar to web developers of all skill levels, such as tags, hyperlinks, document object model, cascade style sheet, JQuery, string interpolation, template engine, data injection, and scalable vector graphics. We develop an online IDE to support CraftML development, with features such as live preview, search, module import, and parameterization. Using examples and case studies, we demonstrate that CraftML offers a low floor for beginners to make simple designs, a high ceiling for experts to build complex computational models, and wide walls to support many application domains such as education, data physicalization, tactile graphics, assistive devices, and mechanical components. | false | false | [
"Tom Yeh",
"Jeeeun Kim"
] | [] | [] | [] |
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