Related Experiment Video
Updated: Jun 18, 2026

Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
Supporting the Process of Exploring and Interpreting Space-Time Multivariate Patterns: The Visual Inquiry Toolkit
Jin Chen1, Alan M Maceachren, Diansheng Guo
1Jin Chen and Alan M. MacEachren, GeoVISTA Center and Department of Geography, Pennsylvania State University, 302 Walker Building, University Park, Pennsylvania16802. Email:< jxc93@psu.edu >;< maceachren@psu.edu >. Tel: 814-865-1633;
Abstract:
While many data sets carry geographic and temporal references, our ability to analyze these datasets lags behind our ability to collect them because of the challenges posed by both data complexity and tool scalability issues. This study develops a visual analytics approach that leverages human expertise with visual, computational, and cartographic methods to support the application of visual analytics to relatively large spatio-temporal, multivariate data sets. We develop and apply a variety of methods for data clustering, pattern searching, information visualization, and synthesis. By combining both human and machine strengths, this approach has a better chance to discover novel, relevant, and potentially useful information that is difficult to detect by any of the methods used in isolation. We demonstrate the effectiveness of the approach by applying the Visual Inquiry Toolkit we developed to analyze a data set containing geographically referenced, time-varying and multivariate data for U.S. technology industries.
Related Concept Videos
Depth Perception and Spatial Vision
Real-World Applications of Space Curves
Gestalt Principles of Perception
Visual System
Once through the pupil, the light passes through the lens, a...
Thematic Layering in GIS
Introduction to GIS

