Browsing by Author "Beck, Fabian"

Now showing 1 - 11 of 11
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    Bombalytics: Visualization of Competition and Collaboration Strategies of Players in a Bomb Laying Game
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Agarwal, Shivam; Wallner, Günter; Beck, Fabian; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Competition and collaboration form complex interaction patterns between the agents and objects involved. Only by understanding these interaction patterns, we can reveal the strategies the participating parties applied. In this paper, we study such competition and collaboration behavior for a computer game. Serving as a testbed for artificial intelligence, the multiplayer bomb laying game Pommerman provides a rich source of advanced behavior of computer agents. We propose a visualization approach that shows an overview of multiple games, with a detailed timeline-based visualization for exploring the specifics of each game. Since an analyst can only fully understand the data when considering the direct and indirect interactions between agents, we suggest various visual encodings of these interactions. Based on feedback from expert users and an application example, we demonstrate that the approach helps identify central competition strategies and provides insights on collaboration.
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    CohExplore: Visually Supporting Students in Exploring Text Cohesion
    (The Eurographics Association, 2023) Liebers, Carina; Agarwal, Shivam; Beck, Fabian; Gillmann, Christina; Krone, Michael; Lenti, Simone
    A cohesive text allows readers to follow the described ideas and events. Exploring cohesion in text might aid students enhancing their academic writing. We introduce CohExplore, which promotes exploring and reflecting on cohesion of a given text by visualizing computed cohesion-related metrics on an overview and detailed level. Detected topics are color-coded, semantic similarity is shown via lines, while connectives and co-references in a paragraph are encoded using text decoration. Demonstrating the system, we share insights about a student-authored text.
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    Frontmatter: VMV 2018: Vision, Modeling, and Visualization
    (The Eurographics Association, 2018) Beck, Fabian; Dachsbacher, Carsten; Sadlo, Filip; Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip
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    Label Placement for Outliers in Scatterplots
    (The Eurographics Association, 2019) Mumtaz, Haris; Garderen, Mereke van; Beck, Fabian; Weiskopf, Daniel; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
    In many application scenarios, outliers can be associated with specific importance for various reasons. In such cases, labeling outliers is important to connect them to the actual semantics of the respective entity. In this paper, we present a cost-based greedy approach that places labels with outliers within scatterplots. The approach uses a search strategy to find the position that represents the least cost to place labels. Our approach can also produce different labeling outcomes by adjusting the weights of the criteria of the cost function. We demonstrate our approach with scatterplots produced from object-oriented software metrics, where outliers often relate to bad smells in the software.
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    Set Streams: Visual Exploration of Dynamic Overlapping Sets
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Agarwal, Shivam; Beck, Fabian; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    In many applications, membership of set elements changes over time. Since each element can be present in multiple sets, the sets also overlap. As a result, it becomes challenging to visualize the temporal change in set membership of elements across several timesteps while showing individual set intersections.We propose Set Streams, a visualization technique that represents changing set structures on a timeline as branching and merging streams. The streams encode the changing membership of elements with set intersections. A query-based selection mechanism supports a flexible comparison of selected groups of elements across the temporal evolution. The main timeline view is complemented with additional panels to provide details about the elements. While the proposed visualization is an application-independent visualization technique for dynamic sets, we demonstrate its effectiveness and applicability through three diverse application examples and expert feedback.
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    Symbolic Event Visualization for Analyzing User Input and Behavior of Augmented Reality Sessions
    (The Eurographics Association, 2023) Rabsahl, Solveig; Satzger, Thomas; Kalamkar, Snehanjali; Grubert, Jens; Beck, Fabian; Gillmann, Christina; Krone, Michael; Lenti, Simone
    Interacting with augmented reality (AR) systems involves different domains and is more complex than interacting with traditional user interfaces. To analyze AR interactions, we suggest an event visualization approach that discerns different event layers on a timeline. It is based on symbolic event representations of typical user actions, such as physical movement or interaction with scene objects. Although focusing on the Microsoft HoloLens 2, the approach can generalize to similar environments and provide a basis for developing a more comprehensive visual analytics and annotation solution for AR usage sessions.
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    A Taxonomy and Survey of Dynamic Graph Visualization
    (© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Beck, Fabian; Burch, Michael; Diehl, Stephan; Weiskopf, Daniel; Chen, Min and Zhang, Hao (Richard)
    Dynamic graph visualization focuses on the challenge of representing the evolution of relationships between entities in readable, scalable and effective diagrams. This work surveys the growing number of approaches in this discipline. We derive a hierarchical taxonomy of techniques by systematically categorizing and tagging publications. While static graph visualizations are often divided into node‐link and matrix representations, we identify the representation of time as the major distinguishing feature for dynamic graph visualizations: either graphs are represented as animated diagrams or as static charts based on a timeline. Evaluations of animated approaches focus on dynamic stability for preserving the viewer's mental map or, in general, compare animated diagrams to timeline‐based ones. A bibliographic analysis provides insights into the organization and development of the field and its community. Finally, we identify and discuss challenges for future research. We also provide feedback from experts, collected with a questionnaire, which gives a broad perspective of these challenges and the current state of the field.Dynamic graph visualization focuses on the challenge of representing the evolution of relationships between entities in readable, scalable and effective diagrams. This work surveys the growing number of approaches in this discipline. We derive a hierarchical taxonomy of techniques by systematically categorizing and tagging publications. While static graph visualizations are often divided into node‐link and matrix representations, we identify the representation of time as the major distinguishing feature for dynamic graph visualizations: either graphs are represented as animated diagrams or as static charts based on a timeline. Evaluations of animated approaches focus on dynamic stability for preserving the viewer's mental map or, in general, compare animated diagrams to timeline‐based ones.
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    Visualizing Group Structures in Graphs: A Survey
    (© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Vehlow, Corinna; Beck, Fabian; Weiskopf, Daniel; Chen, Min and Zhang, Hao (Richard)
    Graph visualizations encode relationships between objects. Abstracting the objects into group structures provides an overview of the data. Groups can be disjoint or overlapping, and might be organized hierarchically. However, the underlying graph still needs to be represented for analyzing the data in more depth. This work surveys research in visualizing group structures as part of graph diagrams. A particular focus is the explicit visual encoding of groups, rather than only using graph layout to indicate groups implicitly. We introduce a taxonomy of visualization techniques structuring the field into four main categories: visual node attributes vary properties of the node representation to encode the grouping, juxtaposed approaches use two separate visualizations, superimposed techniques work with two aligned visual layers, and embedded visualizations tightly integrate group and graph representation. The derived taxonomies for group structure and visualization types are also applied to group visualizations of edges. We survey group‐only, group–node, group–edge and group–network tasks that are described in the literature as use cases of group visualizations. We discuss results from evaluations of existing visualization techniques as well as main areas of application. Finally, we report future challenges based on interviews we conducted with leading researchers of the field.Graph visualizations encode relationships between objects. Abstracting the objects into group structures provides an overview of the data. Groups can be disjoint or overlapping, and might be organized hierarchically. However, the underlying graph still needs to be represented for analyzing the data in more depth. This work surveys research in visualizing group structures as part of graph diagrams. A particular focus is the explicit visual encoding of groups, rather than only using graph layout to indicate groups implicitly. We introduce a taxonomy of visualization techniques structuring the field into four main categories: visual node attributes vary properties of the node representation to encode the grouping, juxtaposed approaches use two separate visualizations, superimposed techniques work with two aligned visual layers, and embedded visualizations tightly integrate group and graph representation.
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    Visualizing the Evolution of Multi-agent Game-playing Behaviors
    (The Eurographics Association, 2022) Agarwal, Shivam; Latif, Shahid; Rothweiler, Aristide; Beck, Fabian; Krone, Michael; Lenti, Simone; Schmidt, Johanna
    Analyzing the training evolution of AI agents in a multi-agent environment helps to understand changes in learned behaviors, as well as the sequence in which they are learned. We train an existing Pommerman team from scratch and, at regular intervals, let it battle against another top-performing team. We define thirteen game-specific behaviors and compute their occurrences in 600 matches. To investigate the evolution of these behaviors, we propose a visualization approach and showcase its usefulness in an application example.
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    Visually Analyzing Topic Change Points in Temporal Text Collections
    (The Eurographics Association, 2023) Krause, Cedric; Rieger, Jonas; Flossdorf, Jonathan; Jentsch, Carsten; Beck, Fabian; Guthe, Michael; Grosch, Thorsten
    Texts are collected over time and reflect temporal changes in the themes that they cover. While some changes might slowly evolve, other changes abruptly surface as explicit change points. In an application study for a change point extraction method based on a rolling Latent Dirichlet Allocation (LDA), we have developed a visualization approach that allows exploring such change points and related change patterns. Our visualization not only provides an overview of topics, but supports the detailed exploration of temporal developments. The interplay of general topic contents, development, and similarities with detected change points reveals rich insights into different kinds of change patterns. The approach comprises a combination of views including topic timeline representations with detected change points, comparative word clouds, and temporal similarity matrices. In an interactive exploration, these views adapt to selected topics, words, or points in time. We demonstrate the use cases of our approach in an in-depth application example involving statisticians.
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    Visually Explaining Publication Ranks in Citation-based Literature Search with PURE Suggest
    (The Eurographics Association, 2022) Beck, Fabian; Krause, Cedric; Krone, Michael; Lenti, Simone; Schmidt, Johanna
    Tracing citation links helps retrieve related publications. While most tools only allow the user to follow the citations of a single publication, some approaches support jointly analyzing the citations of a set of publications. Along similar lines, PURE suggest provides a detailed visual explanation of the ranking of suggested publications. The ranking is based on a score that combines citation numbers with keyword matching and is shown as a glyph for each publication. A citation network component references this glyph and visually embeds it into a timeline and cluster visualization.