Abstract
Although it is possible to encode a great deal of process knowledge about database design into a system, experience has shown that the contribution of a human designer extends beyond his or her knowledge of database design techniques. The next step in the evolution of automated database design tools is to incorporate knowledge and reasoning capabilities to support this higher level of participation. Doing so, requires some understanding of what different terms mean. This paper presents an ontology that can be used as a surrogate for the meaning of words in a database design system to simulate the contributions that a designer would make to a design session with a user based on the designer's general knowledge. The ontology classifies a term into one or more categories such as person, abstract good, or tradable document. It is comprised of a semantic network, a knowledge base containing information on the meaning of terms that have been classified, an expert system knowledge acquisition component, and a distance measure for assessing the distance between the meanings of terms. The ontology was tested by different types of users on a variety of problems and was shown to be quite effective.
This research was supported by the National Science Foundation under Research Initiation Award IRI-9209252 to the first author, a research grant from the College of Business Administration, Georgia State University, and the William E. Simon Graduate School of Business Administration, University of Rochester. The authors with to thank Robert C. Goldstein, Roger Chiang and Deb Dey for useful discussions on this research and Shigetaka Yamakawa for his assistance in analyzing the data.
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Storey, V.C., Ullrich, H., Sundaresan, S. (1997). An Ontology for Database Design Automation. In: Embley, D.W., Goldstein, R.C. (eds) Conceptual Modeling — ER '97. ER 1997. Lecture Notes in Computer Science, vol 1331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63699-4_2
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DOI: https://doi.org/10.1007/3-540-63699-4_2
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