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Viewing Abstract Data as Maps

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Handbook of Human Centric Visualization

Abstract

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.

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Notes

  1. 1.

    A weighted Voronoi diagrams can be used to make the area of each Voronoi cell proportional to its weight. We do not use this approach, however, because we want the Voronoi cell to also contain a specific shape, e.g., the bounding box of a label.

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Acknowledgements

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

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Authors and Affiliations

  1. AT&T Labs – Research, Florham Park, NJ, USA

    Emden R. Gansner & Yifan Hu

  2. University of Arizona, Tucson, AZ, USA

    Stephen G. Kobourov

Authors
  1. Emden R. Gansner
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  2. Yifan Hu
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  3. Stephen G. Kobourov
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Corresponding author

Correspondence to Emden R. Gansner .

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Editors and Affiliations

  1. CSIRO ICT Centre, Marsfield, New South Wales, Australia

    Weidong Huang

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Gansner, E.R., Hu, Y., Kobourov, S.G. (2014). Viewing Abstract Data as Maps. In: Huang, W. (eds) Handbook of Human Centric Visualization. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7485-2_3

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  • DOI: https://doi.org/10.1007/978-1-4614-7485-2_3

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