visualization to abstract data sets like network intrusion detection, recommender systems, and database query results. Although display algorithms are a critical component in the visualization process, they are not the only issue to consider. More and more, we see visualization as a pathfromdatatounderstanding.Fromthisperspective, two obvious questions arise: What should we do before we display the data? What can we do after the user views the data? This is not a new idea, of course. Our work is motivated by others in the community, including methods to integrate data management into visualization, metadata generation and management, techniques to preprocess data to extract and display critical details, and intelligent systems that help users design effective visualizations. This article describes our initial end-to-end system that starts with data management and continues through assisted visualization design, display, navigation, and user interaction (see Figure 1). The purposes of t...
Brent M. Dennis, Sarat Kocherlakota, Amit P. Sawan