Drawing Clustered Graphs as Topographic Maps

Gronemann, Martin and Jünger, Michael (2012) Drawing Clustered Graphs as Topographic Maps. [Preprint]

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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. We also discuss the pitfalls we encountered on the way from the initial idea to the current version of the experimental software that is able to deal with large social networks. We demonstrate this with our visualizations of benchmark instances.

Item Type: Preprint
Classifications: G Algorithms and Complexity > G.350 Clusters
M Methods > M.900 Tree
P Styles > P.300 Curved
S Software and Systems > S.120 Visualization
URI: http://gdea.informatik.uni-koeln.de/id/eprint/1283

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