A user study on visualizing directed edges in graphs

Graphs are often visualized using node-link representations: vertices are depicted as dots, edges are depicted as (poly)lines connecting two vertices. A directed edge running from vertex A to B is generally visualized using an arrow representation: a (poly)line with a triangular arrowhead at vertex B. Although this representation is intuitive, it is not guaranteed that a user is able to determine edge direction as quickly and unambiguously as possible; alternative representations that exhibit less occlusion and visual clutter might be better suited. To investigate this, we developed five additional directed-edge representations using combinations of shape and color. We performed a user study in which subjects performed different tasks on a collection of graphs using these representations and combinations thereof to investigate which representation is best in terms of speed and accuracy. We present our initial hypotheses, the outcome of the user studies, and recommendations regarding directed-edge visualization.

[1]  Chris North,et al.  Toward measuring visualization insight , 2006, IEEE Computer Graphics and Applications.

[2]  Graham J. Wills,et al.  Visualizing Network Data , 2009, Encyclopedia of Database Systems.

[3]  Colin Ware,et al.  Visualizing graphs in three dimensions , 2008, TAP.

[4]  Victoria Interrante,et al.  User Studies: Why, How, and When? , 2003, IEEE Computer Graphics and Applications.

[5]  David H. Laidlaw,et al.  Thoughts on User Studies: Why, How and When , 1993 .

[6]  Bernard Kerr Thread Arcs: an email thread visualization , 2003, IEEE Symposium on Information Visualization 2003 (IEEE Cat. No.03TH8714).

[7]  Colin Ware,et al.  Supporting Visual Queries on Medium-Sized Node–Link Diagrams , 2005, Inf. Vis..

[8]  Emden R. Gansner,et al.  Graphviz and Dynagraph – Static and Dynamic Graph Drawing Tools , 2003 .

[9]  Pak Chung Wong,et al.  Dynamic visualization of graphs with extended labels , 2005, IEEE Symposium on Information Visualization, 2005. INFOVIS 2005..

[10]  Martin Wattenberg,et al.  Arc diagrams: visualizing structure in strings , 2002, IEEE Symposium on Information Visualization, 2002. INFOVIS 2002..

[11]  M. Sheelagh T. Carpendale,et al.  Edgelens: an interactive method for managing edge congestion in graphs , 2003, IEEE Symposium on Information Visualization 2003 (IEEE Cat. No.03TH8714).

[12]  Danny Holten,et al.  Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data , 2006, IEEE Transactions on Visualization and Computer Graphics.

[13]  Jean-Daniel Fekete,et al.  Overlaying Graph Links on Treemaps , 2003 .

[14]  Alan M. Frieze,et al.  Random graphs , 2006, SODA '06.

[15]  Guy Melançon,et al.  Just how dense are dense graphs in the real world?: a methodological note , 2006, BELIV '06.