An Overview + Detail Layout for Visualizing Compound Graphs

TL;DR

This paper introduces a novel layout method for compound graphs with nested, tree-like structures, enhancing the visualization of higher-level groupings while maintaining detail in expanded views, useful in data flow analysis.

Contribution

It presents an overview+detail layout algorithm that preserves higher-level structure in nested compound graphs, improving visualization clarity over traditional methods.

Findings

Layout preserves higher-level group saliency when expanding nested structures

Algorithm effectively visualizes complex nested networks in case studies

Suitable for data flow analysis and biological workflows

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.