Semantic Enterprise Optimizer and Coexistence of Data Models

The authors propose a semantic ontology–driven enterprise data–model architecture for interoperability, integration, and adaptability for evolution, by autonomic agent-driven intelligent design of logical as well as physical data models in a heterogeneous distributed enterprise through its life cycle. An enterprise-standard ontology (in Web Ontology Language [OWL] and Semantic Web Rule Language [SWRL]) for data is required to enable an automated data platform that adds life-cycle activities to the current Microsoft Enterprise Search and extend Microsoft SQL Server through various engines for unstructured data types, as well as many domain types that are configurable by users through a Semantic- query optimizer, and using Microsoft Office SharePoint Server (MOSS) as a content and metadata repository to tie all these components together.