A Visual Inquiry System for Space-Time and Multivariate Patterns (VIS-STAMP)

The research reported here integrates computational, visual, and cartographic methods to develop a novel geo-visual analytic strategy for exploring and understanding spatio-temporal and multivariate patterns. The developed methodology and tools can cluster, sort, and visualize large datasets and help analysts investigate complex patterns across multivariate, spatial, and temporal dimensions. Specifically, the approach involves a self-organizing map, a parallel coordinate plot, several forms of reorderable matrices (including several ordering methods), a novel geographic small multiple display, and a 2-dimensional cartographic color design method. Novel coupling among these methods leverages their independent strengths and facilitates a visual exploration of patterns that are difficult to discover otherwise. The visual inquiry system we developed supports overview of complex patterns and, through a variety of interactions, enables users to focus on specific patterns and examine detailed views. We demonstrate with an application to the IEEE InfoVis 2005 Contest data set, which contains time series, geographically referenced data for companies in the U.S.