Authors:
Henry Ehlers
1
;
Diana Marin
2
;
Hsiang-Yun Wu
3
and
Renata Raidou
1
Affiliations:
1
Visualization Group, Institute of Visual Computing and Human-Centered Technology, TU Wien, Favoritenstr. 9-11 / E193-02, A-1040 Vienna, Austria
;
2
Rendering and Modeling Group, Institute of Visual Computing and Human-Centered Technology, TU Wien, Favoritenstr. 9-11 / E193-02, A-1040 Vienna, Austria
;
3
St. Pölten University of Applied Sciences, Department of Media and Digital Technologies, Campus-Platz 1, St. Pölten, A-3100, Austria
Keyword(s):
Compound Graph Visualization, Literature Survey, Group Structure Visualization.
Abstract:
Compound graphs are common across domains, from social science to biochemical pathway studies, and their visualization is important to both their exploration and analysis. However, effectively visualizing a compound graph’s topology and group structure requires careful consideration, as evident by the many different approaches to this particular problem. To better understand the current advancements in compound graph visualization, we have consolidated and streamlined existing surveys’ taxonomies. More specifically, we aim to disentangle the visual relationship between graph topology and group structure from the visual encoding used to visualize its group structure in order to identify interesting gaps in the literature. In so doing, we are able to enumerate a number of lessons learned and gain a better understanding of the outstanding research opportunities and practical implications across domains.