Value and Relation Display: Interactive Visual Exploration of Large Datasets with Hundreds of Dimensions

 

Authors:  Jing Yang, Daniel Hubball, Matthew Ward, Elke Rundensteiner,and William Ribarsky

 

Few existing visualization systems can handle large datasets with hundreds of dimensions, since high dimensional datasets cause clutter on the display and large response time in interactive exploration. In this paper, we present a significantly improved multi-dimensional visualization approach named Value and Relation (VaR) display that allows users to effectively and efficiently explore large datasets with several hundred dimensions. In the VaR display, data values and dimension relationships are explicitly visualized in the same display by using dimension glyphs to explicitly represent values in dimensions and glyph layout to explicitly convey dimension relationships. In particular, pixel-oriented techniques and density-based scatterplots are used to create dimension glyphs to convey values. Multi-dimensional scaling, Jigsaw map hierarchy visualization techniques, and an animation metaphor named Rainfall are used to convey relationships among dimensions. A rich set of interaction tools have been provided to allow users to interactively detect patterns of interest in the VaR display. A prototype of the VaR display has been fully implemented. The case studies presented in this paper show how the prototype supports interactive exploration of datasets of several hundred dimensions. A user study evaluating the prototype is also reported in this paper.

 

UNCC Technical Report # CVC-UNCC-07-05