MS SQL server Knowledge Management (KM) and Data Mining (DM) capabilities form a decision support system for Business/Medical applications. The Standard for relational database applications is SQL, and OWL for ontology based applications. Various approaches are adapted by researchers for ontology based database applications. Mapping and transformation are very common integration models for intefacing between DB and Onotology based applications [1]. OWL uses XSD data types such as string, integer, float, boolean, time and date. Transformation is in fact conversion of data types from XSD to SQL. Mapping requires knowledge of data types and objects properties. For specific applications the researcher/user can pre-define set of rules for mapping or transformation. Ontology is segmentation of rules with existing database for creating a smart decision support system that enhances the conventional relational database management system [2].
References:
1- Irina Estrova et. al, "Storing OWL Ontologies in SQL Relational Databases" In Proceedings of
World Academy of Science, Engineering and Technology 29 2007,
2- Peter Mika et. al., "Towards a New Synthesis of Ontology, Technology and Knowledge Management", Technical Report IR-BI-001, 2004.
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