The purpose of this study was to build Ontology based database for efficient operation and
interoperability of the human resource bank. The team 7,197,252 of human resources information was
collected through previous studies and classifies the 1,796 clinical item through high quality work. For a
clear expression of clinical terminology mapping and item of international standard terminology
Study on OWL-based database built for the efficient operation of human resources bank
SNOMED-CT it was found to have 826 different synonyms of the term and value types, the data type for
the international standard code. In this study, we selected a preferred term of 76 to minimize the
redundancy due to the synonyms. Also define the relationship between synonyms and preferred terms using
the OWL for interoperability between human resources banks and were stored in XML and databases.
OWL-based database built in this study has a common terminology, it can be interchangeably without
complex mapping process between the human resource banks.