Matrix depictions for large layered graphs

Traditional node-link depictions of layered graphs such as flow charts and process or genealogy diagrams are in widespread use. Layers emerge from applied context (e.g. process stages or familial generations), or are inserted to improve visual clarity. However, these diagrams quickly lose their utility as graph complexity grows. Layout algorithms such as crossing minimizers can preserve utility for larger graphs, but also quickly reach their limits. We offer three new matrix depictions for layered graphs: sorted matrices, centered & sorted matrices, and quilts. Unlike node-link depictions, these matrix depictions scale well to layered graphs containing several hundred nodes. To date, we have only implemented the most complex and scalable of these depictions: quilts. We demonstrate quilting using activity-based management (ABM), an application that must depict layered graphs with thousands or even hundreds of thousands of nodes. For displaying layered graphs that reach such sizes, we show how to summarize these depictions using online analytical processing (OLAP) hierarchies.

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