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Carlea Holl-Jensen||cholljen@umd.edu


HCIL-2009-13

Dunne, C., Shneiderman, B. (May 2009)
Improving Graph Drawing Readability by Incorporating Readability Metrics: A Software Tool for Network Analysts
HCIL-2009-13

Designing graph drawings that effectively communicate the underlying network is challenging as for every network there are many potential unintelligible or even misleading drawings. Automated graph layout algorithms have helped, but frequently generate ineffective drawings. In order to build awareness of effective graph drawing strategies, we detail readability metrics on a [0,1] continuous scale for node occlusion, edge crossing, edge crossing angle, and edge tunneling and summarize many more. Additionally, we define new node & edge readability metrics to provide more localized identification of where improvement is needed. These are implemented in SocialAction, a tool for social network analysis, in order to direct users towards poor areas of the drawing and provide real-time readability metric feedback as users manipulate it. These contributions are aimed at heightening the awareness of network analysts that the images they share or publish could be of higher quality, so that readers could extract relevant information.



TreeVersity: Comparing trees by topology and node attribute values Screenshot

TreeVersity: Comparing trees by topology and node attribute values
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