Detection of contextual identity links in a knowledge base

Joe Raad*, Nathalie Pernelle, Fatiha Saïs

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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. These misuses, which are mainly caused by the lack of other well-defined linking alternatives, can lead to erroneous statements or inconsistencies. We propose in this paper a new contextual identity link: IdentiConTo that could serve as a replacement for owl : SameAs in linking identical instances in a specified context. To detect these contextual links, we have defined an algorithm named DECIDE that has been tested on scientific knowledge bases describing transformation processes.

Original languageEnglish
Title of host publicationProceedings of the Knowledge Capture Conference, K-CAP 2017
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450355537
DOIs
Publication statusPublished - 4 Dec 2017
Externally publishedYes
Event9th International Conference on Knowledge Capture, K-CAP 2017 - Austin, United States
Duration: 4 Dec 20176 Dec 2017

Publication series

NameProceedings of the Knowledge Capture Conference, K-CAP 2017

Conference

Conference9th International Conference on Knowledge Capture, K-CAP 2017
CountryUnited States
CityAustin
Period4/12/176/12/17

Keywords

  • Context
  • Identity link discovery
  • Scientific data

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