Knowledge sifter: agent-based ontology-driven search over heterogeneous databases using semantic web services

Abstract

Knowledge Sifter is a scaleable agent-based system that supports access to heterogeneous information sources such as the Web, open-source repositories, XML-databases and the emerging Semantic Web. User query specification is supported by a user agent that accesses multiple ontologies using an integrated conceptual model expressed in the Web Ontology Language (OWL). A collection of cooperating agents supports interactive query specification and refinement, query decomposition, query processing, as well as result ranking and presentation. The Knowledge Sifter architecture is general and modular so that ontologies and information sources can be easily incorporated. A proof-of-concept implementation shows how Knowledge Sifter can search geo-spatial ontology services such as the USGS Geographic Names Information System (GNIS) and Princeton University's WordNet as well as image databases including Lycos and TerraServer. Each Agent is implemented as a Web Service and the external sources are also accessed via Web Service Technology. © IFIP International Federation for Information Processing 2004.