Evaluating Partially Drawn Links for Directed Graph Edges

  • Michael Burch
  • Corinna Vehlow
  • Natalia Konevtsova
  • Daniel Weiskopf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7034)

Abstract

We investigate the readability of node-link diagrams for directed graphs when using partially drawn links instead of showing each link explicitly in its full length. Providing the complete link information between related nodes in a graph can lead to visual clutter caused by many edge crossings. To reduce visual clutter, we draw only partial links. Then, the question arises if such diagrams are still readable, understandable, and interpretable. As a step toward answering this question, we conducted a controlled user experiment with 42 participants to uncover differences in accuracy and completion time for three different tasks: identifying the existence of a direct link, the existence of an indirect connection with one intermediate node, and the node with the largest number of outgoing edges. Furthermore, we compared tapered and traditional edge representations, three different graph sizes, and six different link lengths. In all configurations, the nodes of the graph were placed according to the force-directed layout by Fruchterman and Reingold. One result of this study is that the characteristics of completion times and error rates depend on the type of task. A general observation is that partially drawn links can lead to shorter task completion times, which occurs for nearly all graph sizes, tasks, and both tapered and traditional edge representations. In contrast, there is a tendency toward higher error rates for shorter links, which in fact is task-dependent.

Keywords

Completion Time Link Length Graph Drawing Graph Size Graph Layout 
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 2012

Authors and Affiliations

  • Michael Burch
    • 1
  • Corinna Vehlow
    • 1
  • Natalia Konevtsova
    • 1
  • Daniel Weiskopf
    • 1
  1. 1.VISUS, University of StuttgartStuttgartGermany

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