New Generation Metadata vocabulary for Ontology Description and Publication

Abstract : Scientific communities are using an increasing number of ontologies and vocabularies. Currently, the problem lies in the difficulty to find and select them for a specific knowledge engineering task. Thus, there is a real need to precisely describe these ontologies with adapted metadata, but none of the existing metadata vocabularies can completely meet this need if taken independently. In this paper, we present a new version of Metadata vocabulary for Ontology Description and publication, referred as MOD 1.2 which succeeds previous work published in 2015. It has been designed by reviewing in total 23 standard existing metadata vocabularies (e.g., Dublin Core, OMV, DCAT, VoID) and selecting relevant properties for describing ontologies. Then, we studied metadata usage analytics within ontologies and ontology repositories. MOD 1.2 proposes in total 88 properties to serve both as (i) a vocabulary to be used by ontology developers to annotate and describe their ontologies, or (ii) an explicit OWL vocabulary to be used by ontology libraries to offer semantic descriptions of ontologies as linked data. The experimental results show that MOD 1.2 supports a new set of queries for ontology libraries. Because MOD is still in early stage, we also pitch the plan for a collaborative design and adoption of future versions within an international working group.
Document type :
Conference papers
Liste complète des métadonnées

Cited literature [13 references]  Display  Hide  Download

https://hal-lirmm.ccsd.cnrs.fr/lirmm-01605783
Contributor : Clement Jonquet <>
Submitted on : Monday, October 2, 2017 - 10:02:52 PM
Last modification on : Tuesday, November 20, 2018 - 8:09:38 PM

File

Article_MTSR-2017_MOD1.2.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Biswanath Dutta, Anne Toulet, Vincent Emonet, Clement Jonquet. New Generation Metadata vocabulary for Ontology Description and Publication. MTSR: Metadata and Semantics Research Conference, Nov 2017, Tallinn, Estonia. pp.173-185, ⟨10.1007/978-3-319-70863-8_17⟩. ⟨lirmm-01605783⟩

Share

Metrics

Record views

562

Files downloads

227