Identification of Hidden Inheritance Patterns in a Relational Database Based on Ontologies

Nowadays, information sharing and reuse across varying relational databases using Ontology Web Language (OWL) for knowledge representation is being studied. Nevertheless, the basic methods generally neglected the hidden heritage, and as a result, the hierarchic relationships could be omitted during the OWL to RDB conversion. It leads to ontologies equipped with relational connections that are out of sync with the structure of database tables. In this regard, this paper presents a new technique to assist an OWL system identify and change ubiquitous inherited traits in relational databases. To be more concrete, in Criminology, our approach emphasizes the improvement of semantic data representation by revealing hidden genetic similarities between individuals and families. Through experimentation, we show the effectiveness of our method to exactly accomplish that by depicting the relationships in hierarchy within relational databases. This study helps to improve the quality of kernels of ontologies which are used to build semantic information from database systems.