Grouping and Aggregate queries Over Semantic Web Databases

Author

Seid, Dawit ; Mehrotra, Sharad

Author_Institution

Univ. of California, Irvine

fYear

2007

fDate

17-19 Sept. 2007

Firstpage

775

Lastpage

782

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Semantic Computing, 2007. ICSC 2007. International Conference on

Conference_Location

Irvine, CA

Print_ISBN

978-0-7695-2997-4

Type

conf

DOI

10.1109/ICSC.2007.91

Filename

4338422