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Workshop on Status and Trends in Spatial Analysis WORKSHOP ON STATUS AND TRENDS IN SPATIAL ANALYSIS Santa Barbara, California: December 10-12, 1998 Introduction The National Science Foundation sponsored a workshop from December 10-12, 1998 at the Upham Hotel, Santa Barbara. The workshop included about 35 international scholars, and was organized under the Varenius program, the National Center for Geogaphi Ifoatio ad Aalysis NCGIAs project to advance geographic information science, by a steering committee of Michael Goodchild (NCGIA/UCSB), Luc Anselin (University of Texas at Dallas), Arthur Getis (San Diego State University), Ayse Ca Faie Mae, Joh Paul Joes II Uiesity of Ketuky, Moto OKelly Ohio State University), John Wilson (University of Southern California), and Paul Longley (University of Bristol). Funds were available to support participation. Purpose of the meeting: Since their inception, geographic information systems have been promoted as vehicles for conducting spatial analysis, that is, for supporting scientists trying to extract meaning and insight from geographic data. Geographers in particular have hoped that GIS would be the 'trojan horse' encouraging and facilitating greater attention to spatial perspectives in other disciplines, and thus raising the utility and practical relevance of geography, and to a large degree this expectation has been realized. But the pace of methodological change in both GIS and spatial analysis has been so rapid in recent years that a stock-taking is appropriate. An assessment is needed of how successful GIS has been at making spatial analysis widely available to physical and social scientists, and of what new directions might be researched in the future. How satisfactory is the environment currently provided by GIS, and how might it be improved? Is spatial analysis being neglected by the sheer diversity of current research in geographic information science? Have GIS and spatial analysis responded appropriately to the critiques published in recent years by social theorists and humanist geographers? How likely are current research efforts to provide an optimum environment for research in geography, regional science, and other disciplines that study the Earth's surface in the coming decade? This document includes a list of the participants involved in the workshop, as well as the position papers they submitted with their application. NCGIA Varenius Project: Workshop on Status and Trends in Spatial Analysis Participants Natalia Andrienko German National Research Center for Information Technology, Sankt-Augustin, Germany Luc Anselin Department of Geography, University of Texas - Dallas Bernie Bauer Geography, National Science Foundation, Washington, D.C. Ling Bian Department of Geography, State University of New York, Buffalo Nancy Bockstael Department of Economics, University of Maryland College Park Barry Boots Department of Geography, Wilfrid Laurier University Paul Box Department of Geography and Earth Resources, Utah State University Lawrence Brown Department of Geography, The Ohio State University, Columbus Aileen Buckley Department of Geography, University of Oregon, Eugene Peter Burrough Department of Geography, University of Utrecht Ayse Can Fannie Mae Diane Cook Department of Statistics, Iowa State University Noel Cressie Department of Statistics, Iowa State University (until June 1999) Department of Statistics, The Ohio State University (after June 1999) Santa Barbara, CA: December 10-12, 1998 2 NCGIA Varenius Project: Workshop on Status and Trends in Spatial Analysis Jack Dangermond Environmental Systems Research Institute, Redlands, California Marcus Felson Department of Sociology, Rutgers University A. Stewart Fotheringham Department of Geography, University of Newcastle, United Kingdom Andrew Frank Department of Geoinformation, Technical University of Vienna, Austria Janet Franklin Department of Geography, San Diego State University Mark Gahegan Department of Geographic Information Science, Curtin University of Technology, Perth, Western Australia Jacqueline Geoghegan Department of Economics, Clark University,Worcester, MA Art Getis Department of Geography, San Diego State University Michael Goodchild NCGIA, University of California-Santa Barbara Daniel A. Griffith Department of Geography, Syracuse University, New York Steve Guptill U. S. Geological Survey, Reston, Virginia Bob Haining Department of Geography, University of Sheffield, Sheffield, UK Geoffrey M. Jacquez BioMedWare, Ann Arbor, Michigan John Paul Jones Department of Geography, University of Kentucky Santa Barbara, CA: December 10-12, 1998 3 NCGIA Varenius Project: Workshop on Status and Trends in Spatial Analysis Konstantin Krivoruchko Environmental Systems Research Institute, Redlands, California Mei Po Kwan Department of Geography, The Ohio State University Tony Lea Micromarketing Data and Systems, Toronto, Canada Michael Leitner Department of Geography and Anthropology, Louisiana State University, Baton Rouge Yee Leung Department of Geography, Chinese University, Hong Kong Paul Longley Department of Geography, University of Bristol Duane Marble Center for Mapping & the Department of Geography, The Ohio State University, Columbus Harvey Miller Department of Geography, University of Utah, Salt Lake City Atsuyuki Okabe Department of Urban Engineering, University of Tokyo, Tokyo Morton O'Kelly Department of Geography, The Ohio State University, Columbus Pat Pellegrini Department of Geography, The Ohio State University, Columbus Jonathan D. Phillips Department of Geography, College of Geosciences, Texas A&M University, College Station Rhonda Ryznar Department of City and Regional Planning, University of North Carolina Dan Sui Department of Geography, Texas A&M University, College Station Santa Barbara, CA: December 10-12, 1998 4 NCGIA Varenius Project: Workshop on Status and Trends in Spatial Analysis Lance Waller Department of Biostatisitcs, University of Minnesota Elizabeth A. Wentz Department of Geography, Arizona State University, Tempe John Wilson Department of Geography, University of Southern California Position Papers In Alphabetical Order Natalia V. Andrienko German National Research Center for Information Technology, Sankt-Augustin, Germany Knowledge Extraction from Spatially Referenced Databases: a Project of an Integrated Environment Current state The notion of Knowledge Discovery in Databases (KDD) denotes the work on revealing significant relationships and regularities in data based on the use of algorithms collectively entitled data mining. The KDD process consists in an iterative fulfillment of the following steps [5]: 1. Data selection and preprocessing, such as checking for errors, removing outliers, handling missing values, and transformation of formats. 2. Data transformations, for example, discretization of variables or production of derived variables. 3. Selection of a data mining method and adjustment of its parameters. 4. Data mining, i.e. application of the selected method. 5. Interpretation and evaluation of the results. In this process the phase of data mining takes no more than 20% of the total workload. However, this phase is much better supported methodologically and by software than all others [6]. This is not surprising because performing of these other steps is a matter of art rather than a routine allowing automation [7]. Lately some efforts in the KDD field have been directed towards intelligent support to the data mining process, in particular, assistance in the selection of an analysis method depending on data characteristics [2,3]. A particular case of KDD is knowledge extraction from spatially referenced data, i.e. data referring to geographic objects or locations or parts of a territory division. In analysis of Santa Barbara, CA: December 10-12, 1998 5 NCGIA Varenius Project: Workshop on Status and Trends in Spatial Analysis such data it is very important to account for the spatial component (relative positions, adjacency, distances, directions etc.). However, information about spatial relationships is very difficult to represent in discrete, symbolic form required for the data mining methods. Known are works on spatial clustering [4] and use of spatial predicates [8], but a complexity of data description and large computational expenses are characteristic for them. Our suggestion For the case of analysis of spatially referenced data we propose to integrate traditional data mining instruments with automated cartographic visualization and tools for interactive manipulation of graphical displays. The essence of the idea is that an analyst can view both source data and results of data mining in the form of maps that convey spatial information to a human in a natural way. This offers at least a partial solution to the challenges caused by spatially referenced data: the analyst can easily see spatial relationships and patterns that are inaccessible for a computer, at least on the present stage of development. In addition, on the ground of such an integration various KDD steps can be significantly supported. The most evident use of cartographic visualization is in evaluation and interpretation of data mining results. However, maps can be helpful also in other activities. For example, visual analysis of spatial distributions of different data components can help in selection of representative variables for data mining and, possibly, suggest which derived variables would be useful to produce. On the stage of data preprocessing a map presentation can expose strange values that may be errors in the data or outliers. Discretization,
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