Viewing Abstract Data as Maps

  • Emden R. Gansner
  • Yifan Hu
  • Stephen G. Kobourov


From telecommunications and abstractions of the Internet to interconnections of medical papers to on-line social networks, technology has spawned an explosion of data in the form of large attributed graphs and networks. Visualization often serves as an essential first step in understanding such data, when little is known. Unfortunately, visualizing large graphs presents its own set of problems, both technically in terms of clutter and cognitively in terms of unfamiliarity with the graph idiom. In this chapter, we consider viewing such data in the form of geographic maps. This provides a view of the data that naturally allows for reduction of clutter and for presentation in a familiar idiom. We describe some techniques for creating such maps, and consider some of the related technical problems. We also present and discuss various applications of this method to real data.


Bipartite Graph Recommender System Voronoi Cell Node Position Color Assignment 
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.



We would like to thank Stephen North and Chris Volinsky for helpful discussions and encouragement.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Emden R. Gansner
    • 1
  • Yifan Hu
    • 1
  • Stephen G. Kobourov
    • 2
  1. 1.AT&T Labs – ResearchFlorham ParkUSA
  2. 2.University of ArizonaTucsonUSA

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