Browsing by Author "Bludau, Mark-Jan"

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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.
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    Unfolding Edges: Adding Context to Edges in Multivariate Graph Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Bludau, Mark-Jan; Dörk, Marian; Tominski, Christian; Bujack, Roxana; Archambault, Daniel; Schreck, Tobias
    Existing work on visualizing multivariate graphs is primarily concerned with representing the attributes of nodes. Even though edges are the constitutive elements of networks, there have been only few attempts to visualize attributes of edges. In this work, we focus on the critical importance of edge attributes for interpreting network visualizations and building trust in the underlying data. We propose 'unfolding of edges' as an interactive approach to integrate multivariate edge attributes dynamically into existing node-link diagrams. Unfolding edges is an in-situ approach that gradually transforms basic links into detailed representations of the associated edge attributes. This approach extends focus+context, semantic zoom, and animated transitions for network visualizations to accommodate edge details on-demand without cluttering the overall graph layout. We explore the design space for the unfolding of edges, which covers aspects of making space for the unfolding, of actually representing the edge context, and of navigating between edges. To demonstrate the utility of our approach, we present two case studies in the context of historical network analysis and computational social science. For these, web-based prototypes were implemented based on which we conducted interviews with domain experts. The experts' feedback suggests that the proposed unfolding of edges is a useful tool for exploring rich edge information of multivariate graphs.