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5JdOTYaUV0U881Q4TgeeQXY1oKJMLurqsa/XakUxZlLxzfL2WIAAFVa2NOFOQhEmRgTRgQwUAiEA oQztCWyjEsVh//uSBP8AAsEfT2slQeBkbCncaEJeS/x7Pa0sZ4Gij2cxpKTwJEeHEYaMoG8gjaQY RoLIEDewtiUG9dm+bd/ygbb1vVa2rX/9lZEctnP1m7I93nsUnq5FoepkyFksr+no29/+rqpSu5EZ kc6Ms7ql1uuLuMW8tYDLUjiate graphics. #165# Challenge winners will be notified by mid August 1993. #165# Final challenge projects will be displayed and challenge awards presented at GIS/LIS, November 1993. Implementation proposals and final papers should be sent to : Kate Beard National Center for Geographic Information and Analysis University of Maine Orono, ME 04469 Phone: (207) 581-2147 Fax: (207) 581-2206 email: beard@mecan1.maine.edu A panel of judges from the Soil Conservation Service, the Environmental Protection Agency, and from the areas of Geography, Cartography, Statistics, and Computer Science will review and judge the entries. Suggested problem areas The following paragraphs describe a number of possible contexts for data quality visualization in addition to the more specific quality issues described above for each data set. These are offered purely as suggestions and participants need not feel constrained by these suggestions. #165##202#Visualization of lineage information. This could cover ways of accessing and visualizing the narrative information describing a data set, such as how the data were collected, over what time period, using what instrumentation, by whom, and how they were compiled and updated. #165# Visualization of data processing errors: GIS processes can introduce errors. For example fuzzy polygon overlay can introduce changes in the positional accuracy of the data, generalization or aggregation can introduce attribute errors or changes in resolution. Visualization methods could be developed to track and document errors generated by specific GIS processes. #165##202#Visualization of product quality. This would include methods for documenting the quality of final products generated by a GIS. This could include visualization techniques for documenting quality on hardcopy products. For additional information on the topic, participants may request a copy of the NCGIA Technical Report 91-26 Report on the Specialist Meeting for I7- Visualization of Data Quality. This report is available via anonymous ftp from ncgia.ucsb.edu in directory pub/tech-reports/postscript. Additional references Beard M. K, and B. Buttenfield. 1992. Spatial, Statistical, and Graphical Dimensions of Data Quality. Proceedings Interface '92. Chrisman, N. R. 1983. The Role of Quality Information in the Long-term Functioning of a Geographic Information System. Cartographica 21 (2/3): 79-87. Clapham, S. and M. K. Beard, 1991. The Development of an Initial Framework for the Visualization of Spatial Data Quality. Proceedings of ACSM 2: 73-82. Defanti, T. A., M. D. Brown and B. H. McCormick. 1989. Visualization: Expanding the Scientific and Engineering Research Opportunities. Computer 22:6 27-38. Goodchild, M. and S. Gopal. 1989. Accuracy of Spatial Databases. New York: Taylor and Francis. Lanter, D. P. 1991. Design of a Lineage-Based Meta-Data Base for GIS Cartography and Geographic Information Systems. 18:4 255-261. Lanter, D. P. and Veregin, H. 1992. A Research Paradigm for Propagating Error in Layer Based GIS. Photogrammetric Engineering and Remote Sensing. 58:6 825-833. Moellering, H. 1988. The Proposed Standard for Digital Cartographic Data: Report of the Digital Cartographic Data Standards Task Force. The American Cartographer, 15:1 (entire issue). Veregin, H. 1989. A Taxonomy of Error in Spatial Databases 89-12 National Center for Geographic Information and Analysis.