Resolution Control for Balancing Overview and Detail in Multivariate Spatial Analysis

Parallel coordinates, re-orderable matrices, and dendrograms are widely used for visual exploration of multivariate data. This research proposes an approach to systematically integrate the methods in a complementary manner for supporting multi-resolution visual data analysis with an enhanced overview+detail exploratory strategy. The paper focuses on three topics: (1) dynamic control across resolutions at which data are explored; (2) coordination and color mapping among the views; and (3) enhanced features of each view designed for the overview+detail exploratory tasks. We contend that systematically coordinating the views through user-controlled resolutions within a highly interactive analysis environment will boost productivity for exploration tasks. We offer a case study analysis to demonstrate this potential. The case study is focused on a complex, geographically referenced dataset including public health, demographic and environmental components.