EuroVisPosters2021

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https://diglib.eg.org/handle/10.2312/2633049

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Browsing EuroVisPosters2021 by Subject "Human centered computing"

Now showing 1 - 5 of 5
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    Elastic Tree Layouts for Interactive Exploration of Mentorship
    (The Eurographics Association, 2021) Yan, Xin Yuan; Ma, Yi Fang; Byška, Jan and Jänicke, Stefan and Schmidt, Johanna
    Mentorship is an important collaborative relationship among scholars. The existing tools to visualize it mainly suffer from a waste of space, lack of overview representation, and less displayed attribute information. To solve these problems, we propose a novel elastic tree layout based on node-link diagrams, in which nodes and edges are represented as elastic rectangles and bands respectively. By stretching, compressing, aggregating, and expanding nodes and edges, we can: get a compact tree layout with high space-efficiency, display both the detailed subtree and compressed context in a single view, use labeling, charts, and node opacity to show multiple attributes. Besides, we designed various animated interactions to facilitate the exploration.
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    Online Study of Word-Sized Visualizations in Social Media
    (The Eurographics Association, 2021) Huth, Franziska; Awad-Mohammed, Miriam; Knittel, Johannes; Blascheck, Tanja; Isenberg, Petra; Byška, Jan and Jänicke, Stefan and Schmidt, Johanna
    We report on an online study that compares three different representations to show topic diversity in social media threads: a word-sized visualization, a background color, and a text representation. Our results do not provide significant evidence that people gain knowledge about topic diversity with word-sized visualizations faster than with the other two conditions. Further, participants who were shown word-sized visualizations performed tasks with equally few or only slightly fewer errors.
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    SimBaTex: Similarity-based Text Exploration
    (The Eurographics Association, 2021) Witschard, Daniel; Jusufi, Ilir; Kerren, Andreas; Byška, Jan and Jänicke, Stefan and Schmidt, Johanna
    Natural language processing in combination with visualization can provide efficient ways to discover latent patterns of similarity which can be useful for exploring large sets of text documents. In this poster abstract, we describe the ongoing work on a visual analytics application, called SimBaTex, which is based on embedding technology, dynamic specification of similarity criteria, and a novel approach for similarity-based clustering. The goal of SimBaTex is to provide search-and-explore functionality to enable the user to identify items of interest in a large set of text documents by interactive assessment of both high-level similarity patterns and pairwise similarity of chosen texts.
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    Towards a Collaborative Experimental Environment for Graph Visualization Research in Virtual Reality
    (The Eurographics Association, 2021) Heidrich, David; Meinecke, Annika; Schreiber, Andreas; Byška, Jan and Jänicke, Stefan and Schmidt, Johanna
    Graph visualization benefit from virtual reality (VR) technology and a collaborative environment. However, implementing collaborative graph visualizations can be very resource consuming and existing prototypes cannot be reused easily. We present a work-in-progress collaborative experimental environment for graph visualization research in VR, which is highly modular, contains all fundamental functionality of a collaborative graph visualization, and provides common interaction techniques. Our environment enables researchers to create and evaluate modules in the same environment for a wide range of experiments.
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    Unfolding Edges for Exploring Multivariate Edge Attributes in Graphs
    (The Eurographics Association, 2021) Bludau, Mark-Jan; Dörk, Marian; Tominski, Christian; Byška, Jan and Jänicke, Stefan and Schmidt, Johanna
    With this research we present an approach to network visualization that expands the capabilities for visual encoding and interactive exploration through edges in node-link diagrams. Compared to the various possibilities for visual and interactive properties of nodes, there are few techniques for interactive visualization of multivariate edge attributes in node-link diagrams. Visualization of edge attributes is oftentimes limited by occlusion and space issues of methods that globally encode attributes in a node-link diagram for all edges, not sufficiently exploiting the potential of interaction. Building up on existing techniques for edge encoding and interaction, we propose 'Unfolding Edges' as an exemplary use of an on-demand detail enhancing approach for exploration of multivariate edge attributes.