Abstract
Ontologies have long been considered the core of semantics as they offer shareable and reusable knowl- edge about a particular domain. Improving and sharing domain specific knowledge residing in a database is one of the key challenges faced while developing any application. Due to the ever growing amount of data on the Web, it is almost impossible to extract meaningful data and the amount of manual work during creation of ontology poses series of challenges. And researchers are facing challenges such as the unavailability of well-formed databases, domain expert's help for extracting cardinality restrictions and generation of un-resolvable URIs. Therefore, we have focused on domain specific relational databases for constructing ontologies as a solution. Our aim is to analyze the various Ontology construction approaches from relational databases and identify the advantages and disadvantages of these techniques, so that an enhanced and efficient approach can be proposed. We have performed detailed analysis of vari- ous ontology construction techniques from relational database (RDB) based on database schema analysis (meta-data, cardinality restrictions and datatype information), stored data (through data mining) and also performed a comparative analysis of these techniques.
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