A Study on the Improvement of Query Processing Performance of OWL Data Based on Jena2

The present Web has not provided the function of more than the information store in that the collected and retrieved information should be interpreted and be purified though the present Web has a merit that can search correlated information easily through simple connections between documents. So, to overcome the limitation of the existing Web like this, researches for semantic Web ontology languages (RDF, RDFS, OWL and so on) prescribed as standard of W3C and for the related technologies have conducted actively. Also, recently the interest for Jena2, Java framework, including rule-based inference engine and the programming environment for the languages like RDF, FDFS, OWL, SPARQL and so on has been heightened. Jena2 has problems that the performance for simple selection operation and the performance for the query that join operations are required slow down, and the performance in processing OWL data slows down because storing document information in a single table. This paper designed and realized OWL translator to move to the relational database designing in this paper the data being in multiple translator and Jena relational database for storing each data information in a separate table after dividing the meaning of OWL documents into class, property, individual to solve this problem. Also, this paper compared the processing performances of the engine quality realizing by using multiple translator and OWL Translator and the engine realizing by applying as it is the functions providing in Jena2 by using university ontology providing in SPARQL engine of Jena2.