How to represent and detect contextual identity links in a knowledge base: Application on experimental data in life sciences

How to represent and detect contextual identity links in a knowledge base: Application on experimental data in life sciences

Joe Raad Nathalie Pernelle Fatiha Saïs Juliette Dibie Liliana Ibanescu Stéphane Dervaux  

UMR MIA-PARIS, INRA, AgroParisTech, Université Paris-Saclay Paris, France

LRI, Paris Sud University Orsay, France

Corresponding Author Email: 
{joe.raad,juliette.dibie,liliana.ibanescu,stephane.dervaux}@agroparistech.fr; {nathalie.pernelle,fatiha.sais}@lri.fr
Page: 
345-372
|
DOI: 
https://doi.org/10.3166/RIA.32.345-372
Received: 
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Accepted: 
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Published: 
30 June 2018
| Citation

OPEN ACCESS

Abstract: 

Most of the Linked Data applications currently rely on the use of owl:sameAs for linking ontology instances. However, several studies have noticed multiple misuses of this identity link, which can lead to erroneous statements or inconsistencies. We propose in this paper a new contextual identity link, that could serve as a replacement in linking identical instances in a specified context. To detect these contextual links, we have defined an algorithm named DECIDE, which has been tested on scientific knowledge bases from several INRA projects.  

Keywords: 

context, identity links, knowledge base, scientific data

1. Introduction
2. Identité contextuelle
3. DECIDE – Méthode de détection des liens d’identité contextuelle
4. Expérimentations
5. Travaux connexes
6. Conclusion
Remerciements
  References

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