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14 avril 2014
- handle: 10670/1.wxs6v9
- hal: hal-01397164
- doi: 10.1007/978-3-642-55032-4_13
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-642-55032-4_13
http://creativecommons.org/licenses/by/ , info:eu-repo/semantics/OpenAccess
Mots-clés
Mashup Linked Data Big Data Semantic WebSujets proches
Large data sets Data sets, LargeCiter ce document
Azzakiy Hendrik et al., « Towards Semantic Mashup Tools for Big Data Analysis », HAL-SHS : sciences de l'information, de la communication et des bibliothèques, ID : 10.1007/978-3-642-55032-4_13
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Résumé
Big Data is generally characterized by three V’s: volume, velocity, and variety. For the Semantic Web community, the variety dimension could be the most appropriate and interesting aspect to contribute in. Since the real-world use of Big Data is for data analytics purposes of knowledge workers in different domains, we can consider mashup approach as an effective tool to create user-generated solution based on available private/public resources. This paper gives brief overview and comparison of some semantic mashup tools which can be employed to mash up various data sources in heterogenous data format.