Hybrid approach for optimal management and querying of data and knowledge

Nowadays, many applications require to represent both data and knowledge together. Regardless of the requirement, the normal practice is either using only database or only ontology. These approaches are proven to have drawbacks. There is still no proper methodology to obtain the benefits from both ontology and database management systems together. The issues raised by the rapprochements between such worlds are well known and addressed by consolidated mapping and transforming languages which may result in loss of data or hindering the reasoning power in knowledge. Nevertheless, to the best of our knowledge, a best practice for establishing such rapprochement is missing which we present through this research; a guideline based cooperation between database and ontology. We have introduced a hybrid approach of relational database and ontology for optimal management and querying of data and knowledge. Our method optimizes the storing mechanism by allowing of distributing data between ontology and database. Further, it optimizes the query execution by allowing some part of the data to be queried through database via SQL and some part of the data to be queried through ontology via SPARQL. We were able to obtain promising results about the performance in terms of storage and query execution and accuracy from the proposed approach.