A Framework for Visualising Large Graphs

Wanchun Li, Seok-Hee Hong, P. Eades
Ninth International Conference on Information Visualisation (IV'05)  
Visualising large graphs faces the challenges of both data complexity and visual complexity. This paper presents a framework for visualising large graphs that reduces data complexity using the clustered graph model and provides users with navigational approaches for browsing clustered graphs. A key design task of such a system is to define a strategy for generating logical abstractions of a clustered graph during navigation. An appropriate abstraction strategy should represent a clustered graph
more » ... well and avoid visual overload. The semantic fisheye view of a clustered graph is proposed for such a purpose. Two case studies were investigated, and the experiment results show that during navigation the first-order fisheye view of a clustered graph conserves visual complexity at a constant level.
doi:10.1109/iv.2005.7 dblp:conf/iv/LiHE05 fatcat:64wp6zzytvg2jmwchqeagdnuh4