Identification & Reconciliation of Semantic Conflicts Using Metadata

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With the development of complex information systems, the integration of heterogeneous systems, and the availability of numerous online computer data sources, it has become increasingly important that methods be developed that consider the meaning of the data used in these systems. For example, it is important that an application requiring financial data in US dollars does not receive data from a source that reports in another currency. This problem is further complicated by the fact that the meaning of data may change at any time. To deal with this problem, information systems must have the ability to represent data semantics and detect and automatically resolve semantic conflicts. This research focuses on the representation and manipulation of data semantics (i.e., metadata). This research develops: (1) a rule-based approach to metadata specification, (2) query processing techniques that identify semantic conflicts, (3) methods that use conversion routines to automatically resolve these conflicts. When applied to source-receiver systems, these techniques create a dynamic system environment that permits changes in data semantics. Similarly, in heterogeneous information systems these techniques define a dynamic schema integration environment where the integrated system can continue to operate as the component systems independently modify data semantics.