A Scalable Indexing Mechanism for Ontology-Based Information Integration

In recent years, there has been an explosion of publicly available RDF and OWL web pages. Typically, these pages are small, heterogeneous and prone to change frequently. In order to effectively integrate them, we propose to adapt a query reformulation algorithm and combine it with an information retrieval inspired index in order to select all sources relevant to a query. We treat each RDF document as a bag of URIs and literals and build an inverted index. Our system first reformulates the user´s query into a set of sub goals and then translates these into Boolean queries against the index in order to determine which sources are relevant. Finally, the selected data sources and the relevant ontology mappings are used in conjunction with a description logic reasoner to provide an efficient query answering solution for the Semantic Web. We have evaluated our system using ontology mappings and ten million real world data sources.