19 June 2001




M. Cobb
University of Southern Mississippi
Hattiesburg, MS 39406-5106
H. Foley III
Xavier University
New Orleans, LA
F. Petry
Tulane University
New Orleans, LA 70118
K. Shaw
Naval Research Laboratory
Stennis Space Center, MS 39529-5004


Many facets of spatial data representation inherently involve issues of accuracy and uncertainty. This problem is greatly magnified when considering the integration of spatial data from different sources, such as in a distributed or interoperable environment. The general concept of schema merging involves the resolution of incompatibilities as in a distributed environment. These may be either structural or semantic in nature. Structural incompatibilities involve those, for example, in which attributes for representing the same values are defined differently. Semantic incompatibilities, however, represent those cases in which similarly defined attributes have different meanings or values. For example, an attribute of WIDTH for a road in one database may include the width of associated access lanes, while in another database it may be only the main driveable portion of the road. Such semantic issues are much more difficult to resolve, as they require a deeper understanding of the data. We will survey the issues as discussed above for spatial data in such environments and describe several approaches for different aspects of the data using fuzzy set techniques to deal with the incompatibilities.

Sponsored by the Marine Corps Warfighting Laboratory.

Published in the Recent Research Issues On The Management Of Fuzziness in Databases, accepted for the Physica-Verlag series "Studies in Fuzziness and Soft Computing," eds. G. Bordogna and G. Pasi, 1999.
Book Chapter