Title :
On-Demand Data Integration on the Cloud
Author :
Ghafour, Samer Abdul ; Barhamgi, Mahmoud ; Ghodous, Parisa
Author_Institution :
Claude Bernard Univ. Lyon 1, Villeurbanne, France
fDate :
June 27 2014-July 2 2014
Abstract :
On-demand data integration is among the key challenges in Cloud Computing. In this paper, we present an ontology-based framework for describing and integrating data on the fly to answer transient business needs. We provide a semantic modeling for cloud´s data services. The proposed modeling makes it possible to automatically resolve the different types of data heterogeneity that would arise when data from heterogeneous and autonomous providers need to be combined together to answer the business´s data needs.
Keywords :
business data processing; cloud computing; data integration; ontologies (artificial intelligence); business data needs; cloud computing; cloud data services; data heterogeneity; on-demand data integration; ontology-based framework; semantic modeling; transient business needs; Business; Data integration; Mashups; Ontologies; Resource description framework; Semantics; On-demand data integration; Ontologies; Services;
Conference_Titel :
Cloud Computing (CLOUD), 2014 IEEE 7th International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4799-5062-1
DOI :
10.1109/CLOUD.2014.127