Exploring Geo-Data Spaces-The Search for Meaning

MACEACHREN, Alan M. (alan@essc.psu.edu), Pennsylvania State University, 302 Walker, Department of Geography, University Park, PA 16802

Key Words: geographic visualization, data mining, spatiotemporal representation, exploratory data analysis

Technology for collection, transmission, and display of georeferenced data, at scales from architectural to global, has advanced rapidly in the past decade-resulting in an order of magnitude increase in availability of georeferenced data. While computational methods allow us to extract information from these masses of data, domain expertise coupled with the power of human vision provides the necessary complement to these computational methods that allow us to extract meaning from the information. Recent and anticipated developments in geographic visualization (GVis) provide the mechanism for linking human experts to computational tools, facilitating the critical step from information extraction to knowledge construction. These developments and their potential are presented in this paper.

GVis synthesizes perspectives on visual representation and analysis, thus far primarily from visualization in scientific computing (ViSC), cartography, and exploratory data analysis (EDA). For GVis to be an effective method in knowledge construction, a closer coupling is needed between the visual methods at the core of GVis and the analytical methods of geocomputation. Beyond this integration, for geo-knowledge construction environments to reach their potential, a more complete understanding must be achieved concerning how people (particularly domain specialists) conceptualize problems and interact with computer systems.

Within the International Cartographic association, a four-component research agenda for GVis is under development (focusing on issues in representation, interface design, GVis-database integration, and cognitive aspects of visualization method development and use). Elements within each component of this research agenda have direct implications for design of knowledge construction environments that involve integration of visualization with computational methods. In this paper, the author provides a brief overview of the ICA research agenda, then focuses specifically on selected issues that underlie design of knowledge construction environments linking analytical with visual methods. Particular attention will be directed to three topics: design of exploratory spatiotemporal data analysis methods (particularly the adaptation of EDA to space-time data); integration of GVis with knowledge discovery in database methods; and the cognitive issues that must be addressed if we are to achieve the next generation of geo-knowledge construction environments that create a more effective conjunction of human and machine capabilities.