Semantic Web Based Approach For Enterprise Information Integration

Recently, with the development of the IT technology, more and more information systems have been built across an enterprise, and various data sources have been constructed for those systems to store and manage critical business and operational data. After decades of accumulation and growth, organizations are processing and storing larger volumes of data than ever before. However, because of the lack of global consideration during the design phase, the data sources for the different systems are very different. Maybe some data sources exist in the form of the file, some are in the databases. Even with databases, maybe the database schemas are different or supported by different product vendors. On the other hand, currently almost all the data are structured at syntax level and meaningless to the computers so that it's difficult for the computers to understand and integrate the information automatically and effectively. As a result, each system becomes an information island and it is very difficult to share the knowledge behind the system. For the purpose of managing the information across the enterprise and providing integrated and correlated data from heterogeneous data sources, a new integration solution, enterprise information integration (Ell) has been separated from enterprise application integration (EAI) and extract transformation load engine (ETL). Meanwhile, the technology of semantic web is also becoming the hottest topic to provide a common framework that allows data to be shared and reused across the applications and enterprises by using ontology to construct the conceptual module for some specific domain and manage resources in RDF format. In this paper, we are going to introduce an approach based on the semantic web technology for the enterprise information integration. In the approach, ontology is the standard data model combining with the rules engine to make the integration automatically by rules driven. Based on this approach, it is also able to build an intelligent system through the rules inference. Finally, the approach is applied to integrate various data sources for building the data dissemination system in State Street Bank, a financial custodian institution in the United States.