To develop sophisticated database management systems, there is a need to incorporate more understanding of the real world in the information that is stored in a database. Semantic data models have been developed to try to capture some of the meaning, as well as the structure, of data using abstractions such as inclusion, aggregation, and association. Besides these well-known relationships, a number of additional semantic relationships have been identified by researchers in other disciplines such as linguistics, logic, and cognitive psychology. This article explores some of the lesser-recognized semantic relationships and discusses both how they could be captured, either manually or by using an automated tool, and their impact on database design. To demonstrate the feasibility of this research, a prototype system for analyzing semantic relationships, called the Semantic Relationship Analyzer, is presented.
