Adaptive Integration of Distributed Semantic Web Data

Abstract

AbstractThe use of RDF (Resource Description Framework) data is a cornerstone of the Semantic Web. RDF data embedded in Web pages may be indexed using semantic search engines, however, RDF data is often stored in databases, accessible via Web Services using the SPARQL query language for RDF, which form part of the Deep Web which is not accessible using search engines. This paper addresses the problem of effectively integrating RDF data stored in separate Web-accessible databases. An approach based on distributed query processing is described, where data from multiple repositories are used to construct partitioned tables that are integrated using an adaptive query processing technique supporting join reordering, which limits any reliance on statistics and metadata about SPARQL endpoints, as such information is often inaccurate or unavailable, but is required by existing systems supporting federated SPARQL queries. The approach presented extends existing approaches in this area by allowing tables to be added to the query plan while it is executing, and shows how an approach currently used within relational query processing can be applied to distributed SPARQL query processing. The approach is evaluated using a prototype implementation and potential applications are discussed.KeywordsQuery ProcessingResource Description FrameworkSPARQL QueryQuery PlanTriple PatternThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.