Visualizing Large Hierarchically Clustered Graphs with a Landscape Metaphor
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.
KeywordsLarge Graph Hierarchical Cluster Algorithm Graph Drawing Cluster Hierarchy Parent Cluster
- 1.Bourqui, R., Auber, D., Mary, P.: How to draw clustered weighted graphs using a multilevel force-directed graph drawing algorithm. In: Proc. 11th Int’l Conf. Inform. Vis., IV 2007, pp. 757–764. IEEE (2007), doi:10.1109/IV.2007.65Google Scholar
- 2.Didimo, W., Montecchiani, F.: Fast layout computation of hierarchically clustered networks: Algorithmic advances and experimental analysis. In: Proc. 16th Int’l Conf. Inform. Vis., IV 2012, pp. 18–23. IEEE (2012) doi:10.1109/IV.2012.14Google Scholar
- 3.Fabrikant, S.I., Montello, D.R., Mark, D.M.: The natural landscape metaphor in information visualization: The role of commonsense geomorphology. J. Am. Soc. Inform. Sci. and Technol. 61(2), 253–270 (2010), doi:10.1002/asi.21227Google Scholar
- 4.Tamassia, R. (ed.): Handbook of Graph Drawing and Visualization. CRC Press (2013)Google Scholar