A framework for complexity management in graph visualization
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
368 - 369
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Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27556
We present a comprehensive framework for development of complexity management techniques in graph visualization tools. The presented architecture is capable of managing multiple associated graphs with navigation links and nesting of graphs as well as ghosting, folding and hiding of unwanted graph elements. The theoretical analyses show that the involved data structures and algorithms are quite effcient, and an implementation in a graph drawing tool has proven to be successful. Our architecture is based on dynamic interactive compound graphs. The definition of compound graphs is extended to efficiently handle the graph editing and complexity management operations. A navigation forest is used to keep track of navigational links among nodes and graphs, and a nesting forest is used to keep track of nesting (inclusion) relations.