Research On Information Integration And Sharing Based On Distributed Ontologies

With the continual increase of data and information on Web, the integration and sharing of distributed data became more difficult. This paper proposes an approach based on ontology context immigration (OCI), which can reduce the implementation complexity in contrast to traditional integration methods. This approach can be mainly divided into three phases:ontology context determination for a given term, ontology semantic similarity computation between ontology terms, and ontology context immigration. As for a local semantic term based on distributed ontologies, an appropriate ontology context of the term will be dynamically immigrated to the source ontology for enriching semantic information related to the term. A system called Distributed Information Sharing System (DISS) is developed to illustrate this approach. The system can achieve better communication and coordination between different ontology information sources, and does not require the support of global ontology or the maintenance of complex ontology mapping relations, thus has a better maintainability and scalability. The experimental results show that the method based on OCI is efficient for distributed ontology information integration and sharing.