StreamEB: Stream Edge Bundling.

  • Quan Nguyen
  • Peter Eades
  • Seok-Hee Hong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7704)


Graph streams have been studied extensively, such as for data mining, while fairly limitedly for visualizations. Recently, edge bundling promises to reduce visual clutter in large graph visualizations, though mainly focusing on static graphs.

This paper presents a new framework, namely StreamEB, for edge bundling of graph streams, which integrates temporal, neighbourhood, data-driven and spatial compatibility for edges. Amongst these metrics, temporal and neighbourhood compatibility are introduced for the first time. We then present force-directed and tree-based methods for stream edge bundling. The effectiveness of our framework is then demonstrated using US flights data and Thompson-Reuters stock data.


Static Graph Graph Visualization Spatial Compatibility Stream Element Stream Edge 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Quan Nguyen
    • 1
  • Peter Eades
    • 1
  • Seok-Hee Hong
    • 1
  1. 1.School of Information TechnologiesUniversity of SydneyAustralia

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