TY - GEN
T1 - An Overview+Detail Layout for Visualizing Compound Graphs
AU - Han, Chang
AU - Lieffers, Justin
AU - Morrison, Clayton
AU - Isaacs, Katherine E.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - compound graphs
KW - graph drawing
KW - graph visualization
KW - network layout
KW - ntework visualization
UR - http://www.scopus.com/inward/record.url?scp=85215317267&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85215317267&partnerID=8YFLogxK
U2 - 10.1109/VIS55277.2024.00035
DO - 10.1109/VIS55277.2024.00035
M3 - Conference contribution
AN - SCOPUS:85215317267
T3 - Proceedings - 2024 IEEE Visualization Conference - Short Papers, VIS 2024
SP - 136
EP - 140
BT - Proceedings - 2024 IEEE Visualization Conference - Short Papers, VIS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE Visualization and Visual Analytics Conference, VIS 2024
Y2 - 13 October 2024 through 18 October 2024
ER -