GIDA____________________ Journal of Geographic Information and Decision Analysis 2001, Vol. 5, No.2, pp . 129-139 © GIDA 2001 ISSN 1480-8943 Sharing Exploratory Geospatial Analysis and Decision Making using GeoVISTA Studio: From a Desktop to the Web Masahiro Takatsuka School of Information Technologies University of Sydney NSW, Australia masa@staff.usyd.edu.au Mark Gahegan GeoVISTA Center Department of Geography The Pennsylvania State University University Park, PA 16802 USA mng1@psu.edu ABSTRACT The main objective of the GeoVISTA Studio project is to improve geoscientific analysis by providing an environment that operationally integrates a wide range of analysis activities, including those both computationally and visually based. We argue here that improving the infra- structure used in analysis has far-reaching potential to better integrate human-based and computationally-based expertise, whether locally or remotely available, and so ultimately improve scientific and decision making outcomes. The improvements to research infrastructure proposed have implications for web-based deployment of analysis methods. This paper illustrates various features of GeoVISTA Studio, such as ease of program construction (visual programming), an open (non-proprietary) architecture, simple component-based integration and advanced deployment methods, which allow us to rapidly construct and share applications that combine geocomputation and geovisualization methods. It also demonstrates that GeoVISTA Studio can be used as both a Web GIS application and a Web GIS application builder. This versatility has the potential to change the nature of systems development for the geosciences, providing better mechanisms to coordinate complex functionality, and as a consequence, to improve analyses and decision making processes by closer integration of software tools and better engagement of the human expert. KEYWORDS: GeoVISTA Studio, visual pro- gramming, decision sharing, exploratory data analysis. Acknowledgements Our thanks go to Sanju Mathew, Frank Hardisty, Xiping Dai and Michael Wheeler for building various data visualization and analysis tools and an application design used in the example. This research is partly sponsored under the NSF Digital Government Program, grant EIA -9983445. 1. Introduction With massive increases in the amount of geospatial data available, and corresponding increases in the complexity of analysis tasks, the kinds of analysis methods required by geographic information systems (GIS) are changing markedly. As a result of the successful integration of historically separate geospatial databases, and with the constant stream of geo-coded data captured by satellite platforms, point of sale systems, integrated sensor networks, mobile computing devices and other location-based