Visualizing Large Hierarchically Clustered Graphs with a Landscape Metaphor

  • Jan Christoph Athenstädt
  • Robert Görke
  • Marcus Krug
  • Martin Nöllenburg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7704)

Indroduction

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.

References

  1. 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. 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. 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. 4.
    Tamassia, R. (ed.): Handbook of Graph Drawing and Visualization. CRC Press (2013)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jan Christoph Athenstädt
    • 1
  • Robert Görke
    • 1
  • Marcus Krug
    • 1
  • Martin Nöllenburg
    • 1
  1. 1.Institute for Theoretical InformaticsKarlsruhe Institute of TechnologyGermany

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