Visualizing large hierarchically clustered graphs with a landscape metaphor

Authors:
Jan Christoph Athenstädt;Robert Görke;Marcus Krug;Martin Nöllenburg
Affiliations:
Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Germany;Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Germany;Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Germany;Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Germany
Venue:
GD'12 Proceedings of the 20th international conference on Graph Drawing
Year:
2012

Citing 4
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Abstract

Large graphs appear in many application domains. Their analysis can be done automatically by machines, for which the graph size is less of a problem, or, especially for exploration tasks, visually by humans. The graph drawing literature contains many efficient methods for visualizing large graphs, see e.g. [4, Chapter 12], but for large graphs it is often useful to first compute a sequence of coarser and more abstract representations by grouping vertices recursively using a hierarchical clustering algorithm. Then the task is to compute an overview picture of the graph based on a given cluster hierarchy, such that details of the graph, e.g., within clusters, remain visible on demand.