Query Transformation in Ontology-Based Relational Data Integration
Wearable Computing Systems（2010）
摘要
The emergence of the Semantic Web brings new paradigm shift of computing in data integration research where data is heterogeneous and distributed. Ontology-based heterogeneous relational data integration has recently attracted many diverse contributions, since most of the information is still stored in relational databases. This paper focuses on the query transformation problem in such an integration scenario. To bridge the semantic gap between the express power of SPARQL and SQL, we describe the semantic of SPARQL graph patterns using relational algebra, which is intended to bring formality and generality to manipulability of SPARQL query. The semantic equivalence of this SPARQL relational algebra is further discussed and a SPARQL to SQL query transforming algorithm is presented.
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关键词
data integration research,relational databases,relational database,sparql query,sparql,ontology-based relational data integration,relational algebra,relational data integration,ontology,sql query,query transforming algorithm,sparql graph patterns,query transformation problem,semantic web,ontologies (artificial intelligence),query transformation,sparql relational algebra,sparql graph pattern,data integration,ontology-based heterogeneous relational data,structured query language,query processing,sql,integration scenario,resource description framework,semantic gap,semantics,distributed computing,algebra,expressive power,wearable computers,automation,data integrity,relation algebra,ontologies,paradigm shift,relational data
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