Title :
Grouping and Aggregate queries Over Semantic Web Databases
Author :
Seid, Dawit ; Mehrotra, Sharad
Author_Institution :
Univ. of California, Irvine
Abstract :
As a growing number of applications represent data as semantic graphs like RDF (Resource Description Format) and the many entity-attribute-value formats, query languages for such data are being required to support operations beyond graph pattern matching and inference queries. Specifically the ability to express aggregate queries is an important feature which is either lacking or is implemented with little attention to the peculiarities of the data model. In this paper, we study the meaning and implementation of grouping and aggregate queries over RDF graphs. We first define grouping and aggregate operators algebraically and then show how the SPARQL query language can be extended to express grouping and aggregate queries.
Keywords :
data models; database management systems; inference mechanisms; knowledge representation languages; ontologies (artificial intelligence); pattern matching; query languages; query processing; semantic Web; OWL; RDF graph; SPARQL query language; aggregate query; data model; data representation; entity-attribute-value format; graph pattern matching; grouping query; inference query; resource description format; semantic Web database; semantic graph; Aggregates; Application software; Books; Computer science; Data models; Database languages; Ontologies; Pattern matching; Resource description framework; Semantic Web;
Conference_Titel :
Semantic Computing, 2007. ICSC 2007. International Conference on
Conference_Location :
Irvine, CA
Print_ISBN :
978-0-7695-2997-4
DOI :
10.1109/ICSC.2007.91
