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NeuroLOG: sharing neuroimaging data using an ontology-based federated approach.

Bernard Gibaud 1 Gilles Kassel 2 Michel Dojat 3 Bénédicte Batrancourt 4 Franck Michel 5 Alban Gaignard 5 Johan Montagnat 5, *
* Corresponding author
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE, INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique
5 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS
Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : This paper describes the design of the NeuroLOG middleware data management layer, which provides a platform to share heterogeneous and distributed neuroimaging data using a federated approach. The semantics of shared information is captured through a multi-layer application ontology and a derived Federated Schema used to align the heterogeneous database schemata from different legacy repositories. The system also provides a facility to translate the relational data into a semantic representation that can be queried using a semantic search engine thus enabling the exploitation of knowledge embedded in the ontology. This work shows the relevance of the distributed approach for neurosciences data management. Although more complex than a centralized approach, it is also more realistic when considering the federation of large data sets, and open strong perspectives to implement multi-centric neurosciences studies.
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https://hal.archives-ouvertes.fr/hal-00683087
Contributor : Johan Montagnat <>
Submitted on : Tuesday, March 27, 2012 - 4:55:47 PM
Last modification on : Friday, March 6, 2020 - 1:37:19 AM
Document(s) archivé(s) le : Thursday, June 28, 2012 - 2:31:47 AM

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  • HAL Id : hal-00683087, version 1
  • PUBMED : 22195101

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Bernard Gibaud, Gilles Kassel, Michel Dojat, Bénédicte Batrancourt, Franck Michel, et al.. NeuroLOG: sharing neuroimaging data using an ontology-based federated approach.. American Medical Informatics Association, Oct 2011, Washington DC, United States. pp.472-80. ⟨hal-00683087⟩

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