DocumentCode :
173013
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
fYear :
2014
fDate :
June 27 2014-July 2 2014
Firstpage :
924
Lastpage :
927
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;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing (CLOUD), 2014 IEEE 7th International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4799-5062-1
Type :
conf
DOI :
10.1109/CLOUD.2014.127
Filename :
6973833
Link To Document :
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