Scale-out RDF molecule store for efficient, scalable data integration and querying

Yuan-Fang Li, Andrew Newman, Jane Louise Hunter

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review

Abstract

Resource Description Framework (RDF) and Web Ontology Language (OWL) offer significant potential as technologies designed to support the integration of and reasoning across heterogeneous disparate data sources. Comprehensive datasets from many disciplines, including environmental sciences, biological sciences, social sciences, and health sciences, have been semantically annotated using these languages to facilitate data correlation, integration, and reasoning. The widespread adoption of Semantic Web technologies is being driven by the need to answer complex queries that demand the integration and processing of multiple related but disparate multidisciplinary datasets.

Original languageEnglish
Title of host publicationCloud Computing and Software Services
Subtitle of host publicationTheory and Techniques
EditorsSyed A Ahson, Mohammad Ilyas
Place of PublicationBoca Raton FL USA
PublisherCRC Press
Pages329-354
Number of pages26
ISBN (Electronic)9781439803165
ISBN (Print)9781439803158
DOIs
Publication statusPublished - 1 Jan 2010
Externally publishedYes

Cite this

Li, Y-F., Newman, A., & Hunter, J. L. (2010). Scale-out RDF molecule store for efficient, scalable data integration and querying. In S. A. Ahson, & M. Ilyas (Eds.), Cloud Computing and Software Services: Theory and Techniques (pp. 329-354). CRC Press. https://doi.org/10.1201/EBK1439803158-c14