IEEE VIS 2024 Content: An Overview + Detail Layout for Visualizing Compound Graphs

An Overview + Detail Layout for Visualizing Compound Graphs

Chang Han - University of Utah, Salt Lake City, United States

Justin Lieffers - University of Arizona, Tucson, United States

Clayton Morrison - University of Arizona, Tucson, United States

Katherine E. Isaacs - The University of Utah, Salt Lake City, United States

Room: Bayshore VI

2024-10-16T12:39:00ZGMT-0600Change your timezone on the schedule page
2024-10-16T12:39:00Z
Exemplar figure, described by caption below
An illustration of our proposed variant of Reingold-Tilford algorithm. The input data is shown in both our layout and a tree view without inner structure. As we follow the RT bottom-up placement, we place group parents with respect to expanded children based on the position of their corresponding internal node. We then make separation passes in both directions of tree expansion.
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Keywords

compound graphs, network layout, graph drawing, network visualization, graph visualization

Abstract

Compound graphs are networks in which vertices can be grouped into larger subsets, with these subsets capable of further grouping, resulting in a nesting that can be many levels deep. In several applications, including biological workflows, chemical equations, and computational data flow analysis, these graphs often exhibit a tree-like nesting structure, where sibling clusters are disjoint. Common compound graph layouts prioritize the lowest level of the grouping, down to the individual ungrouped vertices, which can make the higher level grouped structures more difficult to discern, especially in deeply nested networks. Leveraging the additional structure of the tree-like nesting, we contribute an overview+detail layout for this class of compound graphs that preserves the saliency of the higher level network structure when groups are expanded to show internal nested structure. Our layout draws inner structures adjacent to their parents, using a modified tree layout to place substructures. We describe our algorithm and then present case studies demonstrating the layout's utility to a domain expert working on data flow analysis. Finally, we discuss network parameters and analysis situations in which our layout is well suited.