EuroVisShort2020

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https://diglib.eg.org/handle/10.2312/2632897

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ARGUS: Interactive Visual Analytics Framework for the Discovery of Disruptions in Bio-Behavioral Rhythms
(The Eurographics Association, 2020) Mansoor, Hamid; Gerych, Walter; Buquicchio, Luke; Alajaji, Abdulaziz; Chandrasekaran, Kavin; Agu, Emmanuel; Rundensteiner, Elke; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Human Bio-Behavioral Rhythms (HBRs) such as sleep-wake cycles and their regularity have important health ramifications. Smartphones can sense HBRs by gathering and analyzing data from built-in sensors, which provide behavioral clues. The multichannel nature (multiple sensor streams) of such data makes it challenging to pin-point the causes of disruptions in HBRs. Prior work has utilized machine learning for HBR classification but has not facilitated deeper understanding or reasoning about the potential disruption causes. In this paper, we propose ARGUS, an interactive visual analytics framework to discover and understand HBR disruptions and causes. The foundation of ARGUS is a Rhythm Deviation Score (RDS) that extracts a user's underlying 24-hour rhythm from their smartphone sensor data and quantifies its irregularity. ARGUS then visualizes the RDS using a glyph to easily recognize disruptions in HBRs, along with multiple linked panes that overlay sensor information and user-provided or smartphone-inferred ground truth as supporting context. This framework visually captures a comprehensive picture of HBRs and their disruptions. ARGUS was designed by an expert lead goal-and-task analysis. To demonstrate its generalizability, two different smartphone-sensed datasets were visualized using ARGUS in conjunction with expert feedback.
Characterizing Exploratory Behaviors on a Personal Visualization Interface Using Interaction Logs
(The Eurographics Association, 2020) Sukumar, Poorna Talkad; Martinez, Gonzalo J.; Grover, Ted; Mark, Gloria; D'Mello, Sidney K.; Chawla, Nitesh V.; Mattingly, Stephen M.; Striegel, Aaron D.; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Personal visualizations present a separate class of visualizations where users interact with their own data to draw inferences about themselves. In this paper, we study how a realistic understanding of personal visualizations can be gained from analyzing user interactions. We designed an interface presenting visualizations of the personal data gathered in a prior study and logged interactions from 369 participants as they each explored their own data. We found that the participants spent different amounts of time in exploring their data and used a variety of physical devices which could have affected their engagement with the visualizations. Our findings also suggest that the participants made more comparisons between their data instances than with the provided baselines and certain interface design choices, such as the ordering of options, influenced their exploratory behaviors.
Comprehensive Visualization of Longitudinal Patient Data for the Dermatological Oncological Tumor Board
(The Eurographics Association, 2020) Steinhauer, Nastasja; Hörbrugger, Marc; Braun, Andreas Dominik; Tüting, Thomas; Oeltze-Jafra, Steffen; Müller, Juliane; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
In multidisciplinary oncological team meetings for patient-specific treatment decision-making, so-called tumor boards, usually one physician introduces a patient case verbally and proposes an initial therapy recommendation. This is followed by a short collaborative discussion of the recommendation's suitability. While patient-related image data, such as CT and MR scans, are displayed during the discussion, clinical patient data must be memorized from the introduction or repeatedly inquired by the participating domain experts. To support physicians in this concern, we propose a comprehensive visualization of longitudinal patient-specific information entities during case introduction and discussion. Our visual approach advances over existing work by simultaneously providing an overview of the current patient status as well as of previous therapy measures and their effects on the status. The latter assists in relating the currently proposed recommendation to the previous treatment measures and the related patient status. The visualization has been designed in close collaboration with dermatologists and oncologists aiming at a comprehensive yet easily comprehensible presentation of relevant patient-data and minimal user interaction. The usability and clinical relevance of the prototypical implementation of our visual approach have been evaluated in a qualitative user study with five domain experts based on real anonymized data of melanoma patients.
Configuration Finder: A Tidy Visual Interface for Effective Faceted Search
(The Eurographics Association, 2020) Riehmann, Patrick; Schädler, Andreas; Harder, Jannis; Herpel, Jakob; Froehlich, Bernd; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
We present an interactive visualization aiding users in making informed decisions about large product data sets consisting of quantitative and categorical attributes. Our approach tries to overcome common problems between parallel attribute axes, for instance limited horizontal space or clutter, by introducing novel visual concepts such as proxy axes, fusion axes, and hybrids of set-based and individual axis connections. A proxy axis represents a group of semantically related attributes, which can be interactively explored and seamlessly integrated into the display. Fusion axes allow users to reduce the number of axes by merging categorical+categorical or categorical+quantitative attribute axes. Set-based or individual connections between axis pairs are chosen according to the involved attribute types. The pilot study and expert reviews showed that these novel concepts are understood, considered to be very useful and favored over up-to-date webshop interfaces.
Design of a Real Time Visual Analytics Support Tool for Conflict Detection and Resolution in Air Traffic Control
(The Eurographics Association, 2020) Zohrevandi, Elmira; Westin, Carl A. L.; Lundberg, Jonas; Ynnerman, Anders; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Air traffic control is a safety critical high-risk environment where operators need to analyse and interpret traffic dynamics of spatio-temporal data in real-time. To support the air traffic controller in safely separating traffic, earlier research has applied real-time visualisation techniques that explore the constraints and solution spaces of separation problems. Traditionally, situation displays for conflict detection and resolution have used visualisations that convey information about the relative horizontal position between aircraft. Although vertical solutions for solving conflicts are common, and often a preferred among controllers, visualisations typically provide limited information about the vertical relationship between aircraft. This paper presents a design study of an interactive conflict detection and resolution support tool and explores techniques for real-time visualisation of spatio-temporal data. The design evolution has incorporated several activities, including an initial work domain analysis, iterative rounds of programming, design, and evaluations with a domain expert, and an evaluation with eight active controllers. The heading-time-altitude visualisation system is developed based on formulating and solving aircraft movements in a relative coordinate system. A polar-graph visualisation technique is used to construct a view of conflicting aircraft vertical solution spaces in the temporal domain. Using composite glyphs, the final heading-time-altitude visualisation provides a graphical representation of both horizontal and vertical solution spaces for the traffic situation.
Designing Pairs of Colormaps for Visualizing Bivariate Scalar Fields
(The Eurographics Association, 2020) Ware, Colin; Samsel, Francesca; Rogers, David H.; Navratil, Paul; Mohammed, Ayat; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
In scientific visualization there is sometimes a requirement for two colormaps to be used to represent two co-registered scalar fields. One solution is to represent one of the fields as a continuous colormapped image, and the second field by means of a dense distribution of small glyphs overlaid on the background image and coded using a different colormap. This requires the design of pairs of colormaps which each can be easily read, but which minimally interfere with one another. Colormap pairs separated according to lightness, saturation and hue, were designed and evaluated using both a key accuracy task and a pattern identification task. The saturation separation pair (one colormap having high saturation and the other low saturation) was the best overall.
Dissecting Visual Analytics: Comparing Frameworks for Interpreting and Modelling Observed Visual Analytics Behavior
(The Eurographics Association, 2020) Brown, Vanessa; Turkay, Cagatay; Jianu, Radu; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
This paper provides an empirical, comparative exploration of the role of analytic frameworks in interpreting and modelling visual analytics behavior through data gathered in observational studies. The crucial research on understanding the complex and multi-faceted interplay between visual analytics tools and their users is often done through controlled or naturalistic observations of analysts engaging in the visual analytic process, followed by the interpretation of the observation data. The researchers in Human Computer Interaction and Cognitive Sciences have long used structured analytic frameworks for such analyses, where a guiding set of principles and questions direct attention to relevant aspects of the studied behavior, eventually leading to more complete and consistent analyses. Such frameworks are rarely applied in the visualization domain however, and information about how to apply them and their benefits is scarce. With this paper, we contribute a comparative account, grounded in empirical data collected in a user study with 10 participants using Tableau to analyze domain-specific data, of the types of insights we can glean from interpreting observational data using three different frameworks: Joint Action Theory, Distributed Cognition, and Situated Cognition.
The Effect of Graph Layout on the Perception of Graph Properties
(The Eurographics Association, 2020) Kypridemou, Elektra; Zito, Michele; Bertamini, Marco; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
The way in which a graph is described visually is crucial for the understanding and analysis of its structure. In this study we explore how different drawing layouts affect our perception of the graph's properties. We study the perception of connectedness, tree-ness and density using four different layouts: the Circular, Grid, Planar and Spring layouts. Results show that some layouts are better than others when we need to decide whether a graph is a tree or is connected. More sophisticated algorithms, like Planar and Spring, facilitate our perception, while Circular and Grid layouts lead to performance not better than chance. However, when perceiving the density of a graph, no layout was found to be better than the others.
Effective Visualization of Sparse Image-to-Image Correspondences
(The Eurographics Association, 2020) Andujar, Carlos; Chica, Antonio; Comino Trinidad, Marc; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Finding robust correspondences between images is a crucial step in photogrammetry applications. The traditional approach to visualize sparse matches between two images is to place them side-by-side and draw link segments connecting pixels with matching features. In this paper we present new visualization techniques for sparse correspondences between image pairs. Key ingredients of our techniques include (a) the clustering of consistent matches, (b) the optimization of the image layout to minimize occlusions due to the super-imposed links, (c) a color mapping to minimize color interference among links (d) a criterion for giving visibility priority to isolated links, (e) the bending of link segments to put apart nearby links, and (f) the use of glyphs to facilitate the identification of matching keypoints. We show that our technique substantially reduces the clutter in the final composite image and thus makes it easier to detect and inspect both inlier and outlier matches. Potential applications include the validation of image pairs in difficult setups and the visual comparison of feature detection / matching algorithms.
EuroVis 2020 Short Papers: Frontmatter
(The Eurographics Association, 2020) Kerren, Andreas; Garth, Christoph; Marai, G. Elisabeta; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Evaluating Strategies of Exploratory Visual Data Analysis in Multi Device Environments
(The Eurographics Association, 2020) Alsaiari, Abeer; Aurisano, Jillian; Johnson, Andrew E.; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Supporting exploratory visual data analysis is essential when multiple analysts collaborate using multiple devices. Yet, we still have no full understanding of how the iterative process of analysis unfolds in complex settings. In this paper, we present the results from an exploratory study where six groups of three participants performed a collaborative visual data analysis task in a complex multi-user multi-device environment. We found that the course of the analysis happens at two levels. Within each level, we observed a set of exploration patterns. We present a categorization of the analysis structure in such a complex environment and discuss the implications of device affordances on this categorization. We also discuss this categorization in relation to the current structural assumptions of exploratory visual analysis.
Examining Design-Centric Test Participants in Graphical Perception Experiments
(The Eurographics Association, 2020) Guo, Grace; Dy, Bianchi; Ibrahim, Nazim; Joyce, Sam Conrad; Poorthuis, Ate; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
In this paper, we replicate a foundational study in graphical perception, and compare our findings from using design-centric participants with that of previous studies. We also assess the visual accuracy of two groups, students and professionals, both with design backgrounds, to identify the potential effects of participants' backgrounds on their ability to accurately read charts. Our findings demonstrate that results for reading accuracy for different chart types of previous empirical studies [CM84,HB10] are applicable to participants of design backgrounds. We also demonstrate that besides significant differences in response time, there are no significant differences in reading accuracy between the student and professional groups in our study. This indicates that, despite bias in research participants for visualization research, previous conclusions about graphical perception are likely applicable across different populations and possibly work fields.
Exploring Design Opportunities for Visually Congruent Proxemics in Information Visualization: A Design Space
(The Eurographics Association, 2020) Chulpongsatorn, Neil; Yu, Jackie; Knudsen, Søren; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
We explore design opportunities for varying visual complexity of information visualizations based on distance. Through considering visual congruency and proxemics interaction, we describe a design space that considers potential transitions between visualizations in relation to distance. Our design space is based on exploring prototyping and design possibilities. It describes three properties (boundedness, connectedness, and cardinality) and five design patterns (subdivision, particalization, peculiarization, multiplication, and nesting) that might be considered in design. We describe our design ideas and prototypes, as well as reflect on their usefulness. Finally, we discuss limitations and implications of our work.
Exploring Time Series Segmentations Using Uncertainty and Focus+Context Techniques
(The Eurographics Association, 2020) Bors, Christian; Eichner, Christian; Miksch, Silvia; Tominski, Christian; Schumann, Heidrun; Gschwandtner, Theresia; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Time series segmentation is employed in various domains and continues to be a relevant topic of research. A segmentation pipeline is composed of different steps involving several parameterizable algorithms. Existing Visual Analytics approaches can help experts determine appropriate parameterizations and corresponding segmentation results for a given dataset. However, the results may also be afflicted with different types of uncertainties. Hence, experts face the additional challenge of understanding the reliability of multiple alternative the segmentation results. So far, the influence of uncertainties in the context of time series segmentation could not be investigated. We present an uncertainty-aware exploration approach for analyzing large sets of multivariate time series segmentations. The approach features an overview of uncertainties and time series segmentations, while detailed exploration is facilitated by (1) a lens-based focus+context technique and (2) uncertainty-based re-arrangement. The suitability of our uncertainty-aware design was evaluated in a quantitative user study, which resulted in interesting findings of general validity.
Fast Design Space Rendering of Scatterplots
(The Eurographics Association, 2020) Santala, Simo; Oulasvirta, Antti; Weinkauf, Tino; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
The design space of scatterplots consists of a number of parameters such as marker size and shape, image width and aspect ratio, and opacity. Different parameters yield different visual impressions of the scatterplot. Perceptual optimization of scatterplots means finding the best design parameters to support a given visualization task. This requires rendering thousands of design variations. We describe an image-based method for rendering scatterplots, which is tailored to this scenario: it enables quick updates of the design by re-using previously calculated intermediate results, and is independent of the data set size. Our approach outperforms the classic method of rendering scatterplots, i.e., drawing each marker individually onto an image, and can therefore dramatically speed up the perceptual optimization of scatterplots. We provide an open-source implementation and an online service for our method.
A Force-Directed Power Diagram Approach for Interactive Voronoi Treemaps
(The Eurographics Association, 2020) Abuthawabeh, Ala; Aupetit, Michaël; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Voronoi treemaps represent weighted hierarchical data as nested Voronoi diagram partitions with cells' area proportional to the weights. Current techniques to compute them propose static visualizations which can be used for reporting, or dynamic one to capture data update. However, no ideal solution exists yet to interactively rearrange the treemap layout, for instance for a data journalist to tell a story, or for a scientist to create data categorization. We propose a new way to get an interactive Voronoi treemap, where a child cell can be moved by drag-and-drop within a parent cell attempting to preserve both stability (position) and weight (area) during the move. We use a force-directed approach applied to the dual circles of the Power cells to guide the computation of the Power diagram under the hood. Our preliminary quantitative experiments show the force-directed approach provides areas with 10% weighted average error, which is an order of magnitude higher than standard static approaches, but qualitative observations show that it gives a more predictable and smoother interaction, and a direct control over the stability of the remaining cells. Assuming the user would focus less on getting high accuracy of the areas than keeping a good and stable overview of the treemap while dragging a cell, the force-directed approach appears to be a valuable option to explore further. We also discovered a trade-off between stability and accuracy and the force-directed approach lets the user control it directly.
GaCoVi: a Correlation Visualization to Support Interpretability-Aware Feature Selection for Regression Models
(The Eurographics Association, 2020) Rojo, Diego; Htun, Nyi Nyi; Verbert, Katrien; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
The recent growth of interest in explainable artificial intelligence (XAI) has resulted in a large number of research efforts to provide accountable and transparent machine learning systems. Although a large volume of research has focused on algorithm transparency, there are other factors that influence the interpretability of a system, such as end-users' understanding of individual features and the total number of features. Thus, involving end-users in the feature selection process may be key to achieving interpretability. In addition, previous work has suggested that to obtain satisfactory interpretability and predictive performance, the feature selection process should look for a subset of features that are highly correlated with the response variable yet uncorrelated to each other. Taking this into account, in this paper, we present a work-in-progress design study of a novel system for correlation visualization, GaCoVi. GaCoVi is designed to put domain experts in the loop of feature selection for regression models in scenarios where transparency of the machine learning systems is crucial.
Glyph-Based Visualization of Affective States
(The Eurographics Association, 2020) Kovacevic, Nikola; Wampfler, Rafael; Solenthaler, Barbara; Gross, Markus; Günther, Tobias; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Decades of research in psychology on the formal measurement of emotions led to the concept of affective states. Visualizing the measured affective state can be useful in education, as it allows teachers to adapt lessons based on the affective state of students. In the entertainment industry, game mechanics can be adapted based on the boredom and frustration levels of a player. Visualizing the affective state can also increase emotional self-awareness of the user whose state is being measured, which can have an impact on well-being. However, graphical user interfaces seldom visualize the user's affective state, but rather focus on the purely objective interaction between the system and the user. This paper proposes two graphical user interface widgets that visualize the user's affective state, ensuring a compact and unobtrusive visualization. In a user study with 644 participants, the widgets were evaluated in relation to a baseline widget and were tested on intuitiveness and understandability. Particularly in terms of understandability, the baseline was outperformed by our two widgets.
Influence of Container Resolutions on the Layout Stability of Squarified and Slice-And-Dice Treemaps
(The Eurographics Association, 2020) Knauthe, Volker; Ballweg, Kathrin; Wunderlich, Marcel; Landesberger, Tatiana von; Guthe, Stefan; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
In this paper, we analyze the layout stability for the squarify and slice-and-dice treemap layout algorithms when changing the visualization containers resolution. We also explore how rescaling a finished layout to another resolution compares to a recalculated layout, i.e. fixed layout versus changing layout. For our evaluation, we examine a real world use-case and use a total of 240000 random data treemap visualizations. Rescaling slice-and-dice or squarify layouts affects the aspect ratios. Recalculating slice-and-dice layouts is equivalent to rescaling since the layout is not affected by changing the container resolution. Recalculating squarify layouts, on the other hand, yields stable aspect ratios but results in potentially huge layout changes. Finally, we provide guidelines for using rescaling, recalculation and the choice of algorithm.
Interactive Creation of Perceptually Uniform Color Maps
(The Eurographics Association, 2020) Lambers, Martin; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
A large number of design rules have been identified for color maps used in Scientific Visualization. One of the most important of these is perceptual uniformity, which at the same time is one of the hardest to guarantee when color maps are created from user input. In this paper, we propose parameterized color map models for a variety of application areas. To allow interactive creation of color maps, these models are based on few intuitive parameters, and at the same time guarantee approximate perceptual uniformity.

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