SpaceTree: Supporting Exploration in Large Node Link Tree, Design Evolution and Empirical Evaluation
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
Tree-Maps: a space-filling approach to the visualization of hierarchical information structures
VIS '91 Proceedings of the 2nd conference on Visualization '91
prefuse: a toolkit for interactive information visualization
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Data exploration with paired hierarchical visualizations: initial designs of PairTrees
dg.o '03 Proceedings of the 2003 annual national conference on Digital government research
Network Visualization by Semantic Substrates
IEEE Transactions on Visualization and Computer Graphics
Visual comparison for information visualization
Information Visualization - Special issue on State of the Field and New Research Directions
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Visualizing network data, from tree structures to arbitrarily connected graphs, is a difficult problem in information visualization. A large part of the problem is that in network data, users not only have to visualize the attributes specific to each data item, but also the links specifying how those items are connected to each other. Past approaches to resolving these difficulties focus on zooming, clustering, filtering and applying various methods of laying out nodes and edges. Such approaches, however, focus only on optimizing a network visualization in a single view, limiting the amount of information that can be shown and explored in parallel. Moreover, past approaches do not allow users to cross reference different subsets or aspects of large, complex networks. In this paper, we propose an approach to these limitations using multiple coordinated views of a given network. To illustrate our approach, we implement a tool called DualNet and evaluate the tool with a case study using an email communication network. We show how using multiple coordinated views improves navigation and provides insight into large networks with multiple node and link properties and types.