EuroVis19: Eurographics Conference on Visualization

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https://diglib.eg.org/handle/10.2312/3607290

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Follow The Clicks: Learning and Anticipating Mouse Interactions During Exploratory Data Analysis
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Ottley, Alvitta; Garnett, Roman; Wan, Ran; Gleicher, Michael and Viola, Ivan and Leitte, Heike
The goal of visual analytics is to create a symbiosis between human and computer by leveraging their unique strengths. While this model has demonstrated immense success, we are yet to realize the full potential of such a human-computer partnership. In a perfect collaborative mixed-initiative system, the computer must possess skills for learning and anticipating the users' needs. Addressing this gap, we propose a framework for inferring attention from passive observations of the user's click, thereby allowing accurate predictions of future events. We demonstrate this technique with a crime map and found that users' clicks can appear in our prediction set 92% - 97% of the time. Further analysis shows that we can achieve high prediction accuracy typically after three clicks. Altogether, we show that passive observations of interaction data can reveal valuable information that will allow the system to learn and anticipate future events.
Visualizing for the Non-Visual: Enabling the Visually Impaired to Use Visualization
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Choi, Jinho; Jung, Sanghun; Park, Deok Gun; Choo, Jaegul; Elmqvist, Niklas; Gleicher, Michael and Viola, Ivan and Leitte, Heike
The majority of visualizations on the web are still stored as raster images, making them inaccessible to visually impaired users. We propose a deep-neural-network-based approach that automatically recognizes key elements in a visualization, including a visualization type, graphical elements, labels, legends, and most importantly, the original data conveyed in the visualization. We leverage such extracted information to provide visually impaired people with the reading of the extracted information. Based on interviews with visually impaired users, we built a Google Chrome extension designed to work with screen reader software to automatically decode charts on a webpage using our pipeline. We compared the performance of the back-end algorithm with existing methods and evaluated the utility using qualitative feedback from visually impaired users.
Scalable Ray Tracing Using the Distributed FrameBuffer
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Usher, Will; Wald, Ingo; Amstutz, Jefferson; Günther, Johannes; Brownlee, Carson; Pascucci, Valerio; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Image- and data-parallel rendering across multiple nodes on high-performance computing systems is widely used in visualization to provide higher frame rates, support large data sets, and render data in situ. Specifically for in situ visualization, reducing bottlenecks incurred by the visualization and compositing is of key concern to reduce the overall simulation runtime. Moreover, prior algorithms have been designed to support either image- or data-parallel rendering and impose restrictions on the data distribution, requiring different implementations for each configuration. In this paper, we introduce the Distributed FrameBuffer, an asynchronous image-processing framework for multi-node rendering. We demonstrate that our approach achieves performance superior to the state of the art for common use cases, while providing the flexibility to support a wide range of parallel rendering algorithms and data distributions. By building on this framework, we extend the open-source ray tracing library OSPRay with a data-distributed API, enabling its use in data-distributed and in situ visualization applications.
Topic Tomographies (TopTom): a Visual Approach to Distill Information From Media Streams
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Gobbo, Beatrice; Balsamo, Duilio; Mauri, Michele; Bajardi, Paolo; Panisson, André; CIUCCARELLI, PAOLO; Gleicher, Michael and Viola, Ivan and Leitte, Heike
In this paper we present TopTom, a digital platform whose goal is to provide analytical and visual solutions for the exploration of a dynamic corpus of user-generated messages and media articles, with the aim of i) distilling the information from thousands of documents in a low-dimensional space of explainable topics, ii) cluster them in a hierarchical fashion while allowing to drill down to details and stories as constituents of the topics, iii) spotting trends and anomalies. TopTom implements a batch processing pipeline able to run both in near-real time with time stamped data from streaming sources and on historical data with a temporal dimension in a cold start mode. The resulting output unfolds along three main axes: time, volume and semantic similarity (i.e. topic hierarchical aggregation). To allow the browsing of data in a multiscale fashion and the identification of anomalous behaviors, three visual metaphors were adopted from biological and medical fields to design visualizations, i.e. the flowing of particles in a coherent stream, tomographic cross sectioning and contrast-like analysis of biological tissues. The platform interface is composed by three main visualizations with coherent and smooth navigation interactions: calendar view, flow view, and temporal cut view. The integration of these three visual models with the multiscale analytic pipeline proposes a novel system for the identification and exploration of topics from unstructured texts. We evaluated the system using a collection of documents about the emerging opioid epidemics in the United States.
Investigating the Manual View Specification and Visualization by Demonstration Paradigms for Visualization Construction
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Saket, Bahador; Endert, Alex; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Abstract Interactivity plays an important role in data visualization. Therefore, understanding how people create visualizations given different interaction paradigms provides empirical evidence to inform interaction design. We present a two-phase study comparing people's visualization construction processes using two visualization tools: one implementing the manual view specification paradigm (Polestar) and another implementing visualization by demonstration (VisExemplar). Findings of our study indicate that the choice of interaction paradigm influences the visualization construction in terms of: 1) the overall effectiveness, 2) how participants phrase their goals, and 3) their perceived control and engagement. Based on our findings, we discuss trade-offs and open challenges with these interaction paradigms.
A Geometric Optimization Approach for the Detection and Segmentation of Multiple Aneurysms
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Lawonn, Kai; Meuschke, Monique; Wickenhöfer, Ralph; Preim, Bernhard; Hildebrandt, Klaus; Gleicher, Michael and Viola, Ivan and Leitte, Heike
We present a method for detecting and segmenting aneurysms in blood vessels that facilitates the assessment of risks associated with the aneurysms. The detection and analysis of aneurysms is important for medical diagnosis as aneurysms bear the risk of rupture with fatal consequences for the patient. For risk assessment and treatment planning, morphological descriptors, such as the height and width of the aneurysm, are used. Our system enables the fast detection, segmentation and analysis of single and multiple aneurysms. The method proceeds in two stages plus an optional third stage in which the user interacts with the system. First, a set of aneurysm candidate regions is created by segmenting regions of the vessels. Second, the aneurysms are detected by a classification of the candidates. The third stage allows users to adjust and correct the result of the previous stages using a brushing interface. When the segmentation of the aneurysm is complete, the corresponding ostium curves and morphological descriptors are computed and a report including the results of the analysis and renderings of the aneurysms is generated. The novelty of our approach lies in combining an analytic characterization of aneurysms and vessels to generate a list of candidate regions with a classifier trained on data to identify the aneurysms in the candidate list. The candidate generation is modeled as a global combinatorial optimization problem that is based on a local geometric characterization of aneurysms and vessels and can be efficiently solved using a graph cut algorithm. For the aneurysm classification scheme, we identified four suitable features and modeled appropriate training data. An important aspect of our approach is that the resulting system is fast enough to allow for user interaction with the global optimization by specifying additional constraints via a brushing interface.
CV3: Visual Exploration, Assessment, and Comparison of CVs
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Filipov, Velitchko; Arleo, Alessio; Federico, Paolo; Miksch, Silvia; Gleicher, Michael and Viola, Ivan and Leitte, Heike
The Curriculum Vitae (CV, also referred to as ''résumé'') is an established representation of a person's academic and professional history. A typical CV is comprised of multiple sections associated with spatio-temporal, nominal, hierarchical, and ordinal data. The main task of a recruiter is, given a job application with specific requirements, to compare and assess CVs in order to build a short list of promising candidates to interview. Commonly, this is done by viewing CVs in a side-by-side fashion. This becomes challenging when comparing more than two CVs, because the reader is required to switch attention between them. Furthermore, there is no guarantee that the CVs are structured similarly, thus making the overview cluttered and significantly slowing down the comparison process. In order to address these challenges, in this paper we propose ''CV3'', an interactive exploration environment offering users a new way to explore, assess, and compare multiple CVs, to suggest suitable candidates for specific job requirements. We validate our system by means of domain expert feedback whose results highlight both the efficacy of our approach and its limitations. We learned that CV3 eases the overall burden of recruiters thereby assisting them in the selection process.
Capture & Analysis of Active Reading Behaviors for Interactive Articles on the Web
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Conlen, Matthew; Kale, Alex; Heer, Jeffrey; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Journalists, educators, and technical writers are increasingly publishing interactive content on the web. However, popular analytics tools provide only coarse information about how readers interact with individual pages, and laboratory studies often fail to capture the variability of a real-world audience. We contribute extensions to the Idyll markup language to automate the detailed instrumentation of interactive articles and corresponding visual analysis tools for inspecting reader behavior at both micro- and macro-levels. We present three case studies of interactive articles that were instrumented, posted online, and promoted via social media to reach broad audiences, and share data from over 50,000 reader sessions. We demonstrate the use of our tools to characterize article-specific interaction patterns, compare behavior across desktop and mobile devices, and reveal reading patterns common across articles. Our contributed findings, tools, and corpus of behavioral data can help advance and inform more comprehensive studies of narrative visualization.
Visual-Interactive Preprocessing of Multivariate Time Series Data
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Bernard, Jürgen; Hutter, Marco; Reinemuth, Heiko; Pfeifer, Hendrik; Bors, Christian; Kohlhammer, Jörn; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Pre-processing is a prerequisite to conduct effective and efficient downstream data analysis. Pre-processing pipelines often require multiple routines to address data quality challenges and to bring the data into a usable form. For both the construction and the refinement of pre-processing pipelines, human-in-the-loop approaches are highly beneficial. This particularly applies to multivariate time series, a complex data type with multiple values developing over time. Due to the high specificity of this domain, it has not been subject to in-depth research in visual analytics. We present a visual-interactive approach for preprocessing multivariate time series data with the following aspects. Our approach supports analysts to carry out six core analysis tasks related to pre-processing of multivariate time series. To support these tasks, we identify requirements to baseline toolkits that may help practitioners in their choice. We characterize the space of visualization designs for uncertainty-aware pre-processing and justify our decisions. Two usage scenarios demonstrate applicability of our approach, design choices, and uncertainty visualizations for the six analysis tasks. This work is one step towards strengthening the visual analytics support for data pre-processing in general and for uncertainty-aware pre-processing of multivariate time series in particular.
Analysis of Decadal Climate Predictions with User-guided Hierarchical Ensemble Clustering
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Kappe, Christopher; Böttinger, Michael; Leitte, Heike; Gleicher, Michael and Viola, Ivan and Leitte, Heike
In order to gain probabilistic results, ensemble simulation techniques are increasingly applied in the weather and climate sciences (as well as in various other scientific disciplines). In many cases, however, only mean results or other abstracted quantities such as percentiles are used for further analyses and dissemination of the data. In this work, we aim at a more detailed visualization of the temporal development of the whole ensemble that takes the variability of all single members into account. We propose a visual analytics tool that allows an effective analysis process based on a hierarchical clustering of the time-dependent scalar fields. The system includes a flow chart that shows the ensemble members' cluster affiliation over time, reflecting the whole cluster hierarchy. The latter one can be dynamically explored using a visualization derived from a dendrogram. As an aid in linking the different views, we have developed an adaptive coloring scheme that takes into account cluster similarity and the containment relationships. Finally, standard visualizations of the involved field data (cluster means, ground truth data, etc.) are also incorporated. We include results of our work on real-world datasets to showcase the utility of our approach.
IGM-Vis: Analyzing Intergalactic and Circumgalactic Medium Absorption Using Quasar Sightlines in a Cosmic Web Context
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Burchett, Joseph N.; Abramov, David; Otto, Jasmine Tan; Artanegara, Cassia; Prochaska, Jason Xavier; Forbes, Angus G.; Gleicher, Michael and Viola, Ivan and Leitte, Heike
We introduce IGM-Vis, a novel astrophysics visualization and data analysis application for investigating galaxies and the gas that surrounds them in context with their larger scale environment, the Cosmic Web. Environment is an important factor in the evolution of galaxies from actively forming stars to quiescent states with little, if any, discernible star formation activity. The gaseous halos of galaxies (the circumgalactic medium, or CGM) play a critical role in their evolution, because the gas necessary to fuel star formation and any gas expelled from widely observed galactic winds must encounter this interface region between galaxies and the intergalactic medium (IGM). We present a taxonomy of tasks typically employed in IGM/CGM studies informed by a survey of astrophysicists at various career levels, and demonstrate how these tasks are facilitated via the use of our visualization software. Finally, we evaluate the effectiveness of IGM-Vis through two in-depth use cases that depict real-world analysis sessions that use IGM/CGM data.
The Dependent Vectors Operator
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Hofmann, Lutz; Sadlo, Filip; Gleicher, Michael and Viola, Ivan and Leitte, Heike
In this paper, we generalize the parallel vectors operator due to Peikert and Roth to arbitrary dimension, i.e., to four-dimensional fields and beyond. Whereas the original operator tested for parallelism of two (derived) 2D or 3D vector fields, we reformulate the concept in terms of linear dependency of sets of vector fields, and propose a generic technique to extract and filter the solution manifolds.We exemplify our approach for vortex cores, bifurcations, and ridges as well as valleys in higher dimensions.
Ray Tracing Generalized Tube Primitives: Method and Applications
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Han, Mengjiao; Wald, Ingo; Usher, Will; Wu, Qi; Wang, Feng; Pascucci, Valerio; Hansen, Charles D.; Johnson, Chris R.; Gleicher, Michael and Viola, Ivan and Leitte, Heike
We present a general high-performance technique for ray tracing generalized tube primitives. Our technique efficiently supports tube primitives with fixed and varying radii, general acyclic graph structures with bifurcations, and correct transparency with interior surface removal. Such tube primitives are widely used in scientific visualization to represent diffusion tensor imaging tractographies, neuron morphologies, and scalar or vector fields of 3D flow. We implement our approach within the OSPRay ray tracing framework, and evaluate it on a range of interactive visualization use cases of fixed- and varying-radius streamlines, pathlines, complex neuron morphologies, and brain tractographies. Our proposed approach provides interactive, high-quality rendering, with low memory overhead.
Bird's-Eye - Large-Scale Visual Analytics of City Dynamics using Social Location Data
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Krueger, Robert; Han, Qi; Ivanov, Nikolay; Mahtal, Sanae; Thom, Dennis; Pfister, Hanspeter; Ertl, Thomas; Gleicher, Michael and Viola, Ivan and Leitte, Heike
The analysis of behavioral city dynamics, such as temporal patterns of visited places and citizens' mobility routines, is an essential task for urban and transportation planning. Social media applications such as Foursquare and Twitter provide access to large-scale and up-to-date dynamic movement data that not only help to understand the social life and pulse of a city but also to maintain and improve urban infrastructure. However, the fast growth rate of this data poses challenges for conventional methods to provide up-to-date, flexible analysis. Therefore, planning authorities barely consider it. We present a system and design study to leverage social media data that assist urban and transportation planners to achieve better monitoring and analysis of city dynamics such as visited places and mobility patterns in large metropolitan areas. We conducted a goal-and-task analysis with urban planning experts. To address these goals, we designed a system with a scalable data monitoring back-end and an interactive visual analytics interface. The monitoring component uses intelligent pre-aggregation to allow dynamic queries in near real-time. The visual analytics interface leverages unsupervised learning to reveal clusters, routines, and unusual behavior in massive data, allowing to understand patterns in time and space. We evaluated our approach based on a qualitative user study with urban planning experts which demonstrates that intuitive integration of advanced analytical tools with visual interfaces is pivotal in making behavioral city dynamics accessible to practitioners. Our interviews also revealed areas for future research.
Optimizing Stepwise Animation in Dynamic Set Diagrams
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Mizuno, Kazuyo; WU, Hsiang-Yun; Takahashi, Shigeo; Igarashi, Takeo; Gleicher, Michael and Viola, Ivan and Leitte, Heike
A set diagram represents the membership relation among data elements. It is often visualized as secondary information on top of primary information, such as the spatial positions of elements on maps and charts. Visualizing the temporal evolution of such set diagrams as well as their primary features is quite important; however, conventional approaches have only focused on the temporal behavior of the primary features and do not provide an effective means to highlight notable transitions within the set relationships. This paper presents an approach for generating a stepwise animation between set diagrams by decomposing the entire transition into atomic changes associated with individual data elements. The key idea behind our approach is to optimize the ordering of the atomic changes such that the synthesized animation minimizes unwanted set occlusions by considering their depth ordering and reduces the gaze shift between two consecutive stepwise changes. Experimental results and a user study demonstrate that the proposed approach effectively facilitates the visual identification of the detailed transitions inherent in dynamic set diagrams.
Focus+Context Exploration of Hierarchical Embeddings
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Höllt, Thomas; Vilanova, Anna; Pezzotti, Nicola; Lelieveldt, Boudewijn P. F.; Hauser, Helwig; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Hierarchical embeddings, such as HSNE, address critical visual and computational scalability issues of traditional techniques for dimensionality reduction. The improved scalability comes at the cost of the need for increased user interaction for exploration. In this paper, we provide a solution for the interactive visual Focus+Context exploration of such embeddings. We explain how to integrate embedding parts from different levels of detail, corresponding to focus and context groups, in a joint visualization. We devise an according interaction model that relates typical semantic operations on a Focus+Context visualization with the according changes in the level-of-detail-hierarchy of the embedding, including also a mode for comparative Focus+Context exploration and extend HSNE to incorporate the presented interaction model. In order to demonstrate the effectiveness of our approach, we present a use case based on the visual exploration of multi-dimensional images.
V-Awake: A Visual Analytics Approach for Correcting Sleep Predictions from Deep Learning Models
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Garcia Caballero, Humberto; Westenberg, Michel; Gebre, Binyam; Wijk, Jarke J. van; Gleicher, Michael and Viola, Ivan and Leitte, Heike
The usage of deep learning models for tagging input data has increased over the past years because of their accuracy and highperformance. A successful application is to score sleep stages. In this scenario, models are trained to predict the sleep stages of individuals. Although their predictive accuracy is high, there are still misclassifications that prevent doctors from properly diagnosing sleep-related disorders. This paper presents a system that allows users to explore the output of deep learning models in a real-life scenario to spot and analyze faulty predictions. These can be corrected by users to generate a sequence of sleep stages to be examined by doctors. Our approach addresses a real-life scenario with absence of ground truth. It differs from others in that our goal is not to improve the model itself, but to correct the predictions it provides. We demonstrate that our approach is effective in identifying faulty predictions and helping users to fix them in the proposed use case.
An Ontological Framework for Supporting the Design and Evaluation of Visual Analytics Systems
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Chen, Min; Ebert, David; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Designing, evaluating, and improving visual analytics (VA) systems is a primary area of activities in our discipline. In this paper, we present an ontological framework for recording and categorizing technical shortcomings to be addressed in a VA workflow, reasoning about the causes of such problems, identifying technical solutions, and anticipating secondary effects of the solutions. The methodology is built on the theoretical premise that designing a VA workflow is an optimization of the costbenefit ratio of the processes in the workflow. It makes uses three fundamental measures to group and connect ''symptoms'', ''causes'', ''remedies'', and ''side-effects'', and guide the search for potential solutions to the problems. In terms of requirement analysis and system design, the proposed methodology can enable system designers to explore the decision space in a structured manner. In terms of evaluation, the proposed methodology is time-efficient and complementary to various forms of empirical studies, such as user surveys, controlled experiments, observational studies, focus group discussions, and so on. In general, it reduces the amount of trial-and-error in the lifecycle of VA system development.
Examining Implicit Discretization in Spectral Schemes
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Quinan, P. Samuel; Padilla, Lace M. K.; Creem-Regehr, Sarah H.; Meyer, Miriah; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Two of the primary reasons rainbow color maps are considered ineffective trace back to the idea that they implicitly discretize encoded data into hue-based bands, yet no research addresses what this discretization looks like or how consistent it is across individuals. This paper presents an exploratory study designed to empirically investigate the implicit discretization of common spectral schemes and explore whether the phenomenon can be modeled by variations in lightness, chroma, and hue. Our results suggest that three commonly used rainbow color maps are implicitly discretized with consistency across individuals. The results also indicate, however, that this implicit discretization varies across different datasets, in a way that suggests the visualization community's understanding of both rainbow color maps, and more generally effective color usage, remains incomplete.
Investigating Effects of Visual Anchors on Decision-Making about Misinformation
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Wesslen, Ryan; Santhanam, Sashank; Karduni, Alireza; Cho, Isaac; Shaikh, Samira; Dou, Wenwen; Gleicher, Michael and Viola, Ivan and Leitte, Heike
Cognitive biases are systematic errors in judgment due to an over-reliance on rule-of-thumb heuristics. Recent research suggests that cognitive biases, like numerical anchoring, transfers to visual analytics in the form of visual anchoring. However, it is unclear how visualization users can be visually anchored and how the anchors affect decision-making. To investigate, we performed a between-subjects laboratory experiment with 94 participants to analyze the effects of visual anchors and strategy cues using a visual analytics system. The decision-making task was to identify misinformation from Twitter news accounts. Participants were randomly assigned to conditions that modified the scenario video (visual anchor) and/or strategy cues provided. Our findings suggest that such interventions affect user activity, speed, confidence, and, under certain circumstances, accuracy. We discuss implications of our results on the forking paths problem and raise concerns on how visualization researchers train users to avoid unintentionally anchoring users and affecting the end result.

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