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Drawing Clustered Graphs as Topographic Maps

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7704)

Abstract

The visualization of clustered graphs is an essential tool for the analysis of networks, in particular, social networks, in which clustering techniques like community detection can reveal various structural properties.

In this paper, we show how clustered graphs can be drawn as topographic maps, a type of map easily understandable by users not familiar with information visualization. Elevation levels of connected entities correspond to the nested structure of the cluster hierarchy.

We present methods for initial node placement and describe a tree mapping based algorithm that produces an area efficient layout. Given this layout, a triangular irregular mesh is generated that is used to extract the elevation data for rendering the map. In addition, the mesh enables the routing of edges based on the topographic features of the map.

Keywords

  • Convex Polygon
  • Cluster Node
  • Triangle Mesh
  • Root Cluster
  • Information Visualization

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Gronemann, M., Jünger, M. (2013). Drawing Clustered Graphs as Topographic Maps. In: Didimo, W., Patrignani, M. (eds) Graph Drawing. GD 2012. Lecture Notes in Computer Science, vol 7704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36763-2_38

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  • DOI: https://doi.org/10.1007/978-3-642-36763-2_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36762-5

  • Online ISBN: 978-3-642-36763-2

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