Semantic Transformation Rules and Patterns (STRP) Method: The Method Transforming Relational Databases to Ontologies
2007 (English)Student thesis (Other (popular science, discussion, etc.))
Since the early day, when we invented Information Systems, database is a crucial component. Organizations store millions of organizational information in the database. In information age, not only constructing new knowledge acquires competitive advantage in business but also sharing and reusing knowledge. Ontology is intended to formally and explicitly represent, share, and reuse knowledge. Also, an introduction of the Semantic Web technologies leads organizations moving toward the semantic aspects of information and processes. The semantic information carries deeper meaning than just rearranging data. Hence, this work proposes a method to conduct a semantic transformation of organizational information residing in relational databases to ontologies. The method provides a stepwise guideline from selecting the source database to a stage that an ontology is generated. It also provides a set of transformation rules and patterns helping with the meaningful transformation. In addition, it gives out a framework for realizing the efficacy of the proposed method. The results produced from the research are the Semantic Learning Rules and Pattern method and the Semantic Transformation framework. The proposed method tackles a need in semantic transformation approach while, the framework helps to realize the utility of the proposed method.
Place, publisher, year, edition, pages
data, models,, model, transformation,, ontology
IdentifiersURN: urn:nbn:se:su:diva-12098OAI: oai:DiVA.org:su-12098DiVA: diva2:178618