Graduate Student Posters 2007

Author: Zhengxiang Pan

The Semantic Web extends the traditional Web by introducing a mechanism to annotate Web data with formal semantics. Systems can then leverage these semantics in order to integrate heterogeneous data sources. The current Semantic Web consists of numerous independent ontologies. We have shown that the Web Ontology Language OWL can be used to integrate these ontologies and thereby integrate the data sources that commit to them. Hawkeye, a system that given sufficient OWL descriptions, can answer queries that span heterogeneous data sources. In order to perform scalable reasoning, Hawkeye loosely couples a description logic reasoner with a relational database management system. In the evaluation, we have successfully loaded more than 200 million facts. We use this database of facts to demonstrate realistic integration queries in e-government and academic scenarios. These queries cannot be answered by traditional search engines. We show that many complex queries have response time under one minute, and that simple queries can be answered in seconds.