EuroVisShort2020

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

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Width-Scale Bar Charts for Data with Large Value Range
(The Eurographics Association, 2020) Höhn, Markus; Wunderlich, Marcel; Ballweg, Kathrin; Landesberger, Tatiana von; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Data sets with large value range are difficult to visualize with traditional linear bar charts. Usually, a logarithmic scale is used in these cases. However, the logarithmic scale suffers from non-linearity. Recently, scale-stack bar charts and magnitude markers, improve the readability of values. However, they have other disadvantages such as various scales or several objects for visualizing one value. We propose the width-scale bar chart that uses width, height and color to cover a large value range within one linear scale. A quantitative user study shows advantages of our design - especially for reading values.
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.
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.
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.
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.
MODELAR: A MODular and EvaLuative framework to improve surgical Augmented Reality visualization
(The Eurographics Association, 2020) Hattab, Georges; Meyer, Felix; Albrecht, Remke Dirk; Speidel, Stefanie; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
The use of Augmented Reality (AR) for the visualization of 3D biomedical image data is possible thanks to a growing number of hardware and software solutions. Considerable efforts are made during surgery, where the visual information of the target structures can either be highlighted or dulled. However, as technical challenges and barriers to development decrease, it's increasingly important to take into account the specific capacities and constraints of the surgeon's perceptual and cognitive systems. To address this legitimate problem, we present a practical framework that evaluates the importance of visual encodings and renderings for surgical AR. By conducting a task-specific user study we observed a set of emerging visualization strategies. The given task is to make the kidney boundary visually salient and make the tumor and calyx distinguishable. After having recruited 23 participants, we found two preferred presets to tackle this task. With both presets, the usage of color, depth, and opacity improved the display of the organ bounds while contrasting the tumor and calyx. 19 participants successfully completed the task using MODELAR. Their preference was to either find a good preset where the organ bounds were visible then adjust the color of target objects or vice versa. MODELAR helped us better identify effective visualization that best fit the task requirements. Our evaluation results and the modular framework MODELAR is freely available and open source at https://github.com/ghattab/MODELAR.
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.
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.
TopoLines: Topological Smoothing for Line Charts
(The Eurographics Association, 2020) Rosen, Paul; Suh, Ashley; Salgado, Christopher; Hajij, Mustafa; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Line charts are commonly used to visualize a series of data values. When the data are noisy, smoothing is applied to make the signal more apparent. Conventional methods used to smooth line charts, e.g., using subsampling or filters, such as median, Gaussian, or low-pass, each optimize for different properties of the data. The properties generally do not include retaining peaks (i.e., local minima and maxima) in the data, which is an important feature for certain visual analytics tasks. We present TopoLines, a method for smoothing line charts using techniques from Topological Data Analysis. The design goal of TopoLines is to maintain prominent peaks in the data while minimizing any residual error. We evaluate TopoLines for 2 visual analytics tasks by comparing to 5 popular line smoothing methods with data from 4 application domains.
SAMBAVis: Design Study of a Visual Analytics Tool for the Music Industry Powered by YouTube Comments
(The Eurographics Association, 2020) Oliveira, Victor Adriel de Jesus; Stoiber, Christina; Grüblbauer, Johanna; Musik, Christoph; Ringot, Alexis; Gebesmair, Andreas; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Data from comments on social media platforms offer valuable information about trends and market changes. Aiming at the music industry, we propose SAMBAVis: a visual analytics tool to handle user-generated content from comments left on YouTube music videos. SAMBAVis displays main key performance indexes, video lifecycle, and engagement with comments. It also performs sentiment analysis and extracts the main keywords from the comments, expanding YouTube capabilities. In this paper, we contribute with a design study, explaining the development of SAMBAVis and the rationale of our design. We present a usage scenario and reflect on our methods and results when creating a visualization tool for experts in the music business.
Sketchy Rendering to Aid the Recollection of Regular Visualizations
(The Eurographics Association, 2020) Larsen, Michael Reidun Engelbrecht; Han, Wenkai; Schulz, Hans-Jörg; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Some visualizations have a more regular visual appearance than others. For example, while stream graphs or force-directed network layouts feature a unique, almost organic 'look and feel', matrices or unit treemaps can become rather bland, grid-like visualizations in which one data item is hard to tell apart from the next. In this paper, we investigate the use of sketchy rendering for such grid-like visualizations to give them a slightly more unique 'look and feel' themselves. We evaluate our approach in a lab study (N = 16) where participants were asked to re-find a given grid cell in regular and sketchy grids. We find that users who make conscious use of the sketchy features can benefit from certain forms of sketchy rendering in terms of task completion times.
Investigating the Role of Locus of Control in Moderating Complex Analytic Workflows
(The Eurographics Association, 2020) Crouser, R. Jordan; Ottley, Alvitta; Swanson, Kendra; Montoly, Ananda; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Throughout the last decade, researchers have shown that the effectiveness of a visualization tool depends on the experience, personality, and cognitive abilities of the user. This work has also demonstrated that these individual traits can have significant implications for tools that support reasoning and decision-making with data. However, most studies in this area to date have involved only short-duration tasks performed by lay users. This short paper presents a preliminary analysis of a series of exercises with 22 trained intelligence analysts that seeks to deepen our understanding of how individual differences modulate expert behavior in complex analysis tasks.
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.
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.
RankBooster: Visual Analysis of Ranking Predictions
(The Eurographics Association, 2020) Puri, Abishek; Ku, Bon Kyung; Wang, Yong; Qu, Huamin; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Ranking is a natural and ubiquitous way to facilitate decision-making in various applications. However, different rankings are often used for the same set of entities, with each ranking method placing emphasis on different factors. These factors can also be multi-dimensional in nature, compounding the problem. This complexity can make it challenging for an entity which is being ranked to understand what they can do to improve their rankings, and to analyze the effect of changes in various factors to their overall rank. In this paper, we present RankBooster, a novel visual analytics system to help users conveniently investigate ranking predictions.We take university rankings as an example and focus on helping universities to better explore their rankings, where they can compare themselves to their rivals in key areas as well as overall. Novel visualizations are proposed to enable efficient analysis of rankings, including a Scenario Analysis View to show a high-level summary of different ranking scenarios, a Relationship View to visualize the influence of each attribute on different indicators and a Rival View to compare the ranking of a university and those of its rivals. A case study demonstrates the usefulness and effectiveness of RankBooster in facilitating the visual analysis of ranking predictions and helping users better understand their current situation.
Visualising Collocation for Close Writing
(The Eurographics Association, 2020) Roberts, Jonathan C.; Butcher, Peter W. S.; Lew, Robert; Rees, Geraint Paul; Sharma, Nirwan; Frankenberg-Garcia, Ana; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
We present how we have developed a visualisation tool and text editor to display collocations for the purpose of close writing. Collocations are words that combine together in a natural way. Our design study approach brought together a collaboration of experts in lexicography, language learning, and visualisation, starting with low-fidelity prototypes before developing fuller functional systems. We studied the challenge of how to visualise collocations, such to help language learners write more effectively. We have co-created (i) an expert-curated dataset of over 30,000 collocations, (ii) developed a text-editor which performs word analysis, and recommends collocations, and (iii) created several in-situ visualisations linked to the editor, to help users visualise and lookup collocations, and view example sentences. Every stage of development has been evaluated with language learners and other potential users, which has positively improved its design and functionality.
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.
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.
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.
Task-based Colormap Design Supporting Visual Comprehension in Process Tomography
(The Eurographics Association, 2020) Zhang, Yuchong; Fjeld, Morten; Said, Alan; Fratarcangeli, Marco; Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta
Color coding is a fundamental technique for mapping data to visual representations, allowing people to carry out comprehension-based tasks. Process tomography is a rapidly developing non-invasive imaging technique used in various fields of science due to its effective flow monitoring and data acquisition [KLS*19]. To study how well colormaps can support visual comprehension of tomographic data, we conduct a feasibility evaluation of 11 widely-used color schemes. We employ the same segmentation tasks characterized by Microwave Tomography (MWT) on each individual chosen colormap, and then conduct a quantitative assessment of those schemes. Based on the insight gained, we conclude that autumn, viridis, and parula colormaps yield the best segmentation results. According to our findings, we propose a colormap design guideline for practitioners and researchers in the field of process tomography.

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