eClims: An Extensible and Dynamic Integration Framework for Biomedical Information Systems - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Journal of Biomedical and Health Informatics Année : 2016

eClims: An Extensible and Dynamic Integration Framework for Biomedical Information Systems

(1) , (1) , (2)
1
2

Résumé

Biomedical information systems (BIS) require consideration of three types of variability: data variability induced by new high throughput technologies, schema or model variability induced by large scale studies or new fields of research, and knowledge variability resulting from new discoveries. Beyond data heterogeneity, managing variabilities in the context of BIS requires extensible and dynamic integration process. In this paper, we focus on data and schema variabilities and we propose an integration framework based on ontologies, master data, and semantic annotations. The framework addresses issues related to: 1) collaborative work through a dynamic integration process; 2) variability among studies using an annotation mechanism; and 3) quality control over data and semantic annotations. Our approach relies on two levels of knowledge: BIS-related knowledge is modeled using an application ontology coupled with UML models that allow controlling data completeness and consistency, and domain knowledge is described by a domain ontology, which ensures data coherence. A system build with the eClims framework has been implemented and evaluated in the context of a proteomic platform.
Fichier non déposé

Dates et versions

hal-01444029 , version 1 (23-01-2017)

Identifiants

Citer

Marinette Savonnet, Eric Leclercq, Pierre Naubourg. eClims: An Extensible and Dynamic Integration Framework for Biomedical Information Systems. IEEE Journal of Biomedical and Health Informatics, 2016, 20 (6), pp.1640 - 1649. ⟨10.1109/JBHI.2015.2464353⟩. ⟨hal-01444029⟩
172 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook Twitter LinkedIn More