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A content-focused method for re-engineering thesauri into semantically adequate ontologies using OWL.

Authors :
Kless, Daniel
Jansen, Ludger
Milton, Simon
Source :
Semantic Web (1570-0844); 2016, Vol. 7 Issue 5, p543-576, 34p
Publication Year :
2016

Abstract

The re-engineering of vocabularies into ontologies can save considerable time in the development of ontologies. Current methods that guide the re-engineering of thesauri into ontologies often convert vocabularies merely syntactically and ignore problems arising from interpreting vocabularies as ontologies, i.e. as sets of statements of facts. Current re-engineering methods also do not make use of the semantic capabilities of formal languages in order to detect logical mistakes and improve vocabularies. In this paper, we introduce a content-focused method for building domain-specific ontologies based on a thesaurus, a popular type of vocabulary. Application of the method results in an ontology that not only adheres to the semantics of the description logic OWL, but also contains a semantically rich description of the modeled entities, enables non-trivial, automated reasoning, and can be integrated with other ontologies following the same development principles. We explain the motivation and sub-activities for each of the steps in our method and illustrate their application through a case study in the domain of agricultural fertilizers based on the ACROVOC Thesaurus. Our method shows, first and foremost, that a considerable manual effort is required to derive a semantically rich ontology from a thesaurus, particularly in connection with the alignment to a top-level ontology as well as for the identification and formal specification of membership conditions. Applying our method will likely change the structure of a thesaurus considerably. Our method is particularly useful where a highly reliable is-a hierarchy or consistent definitions are crucial. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15700844
Volume :
7
Issue :
5
Database :
Complementary Index
Journal :
Semantic Web (1570-0844)
Publication Type :
Academic Journal
Accession number :
116483502
Full Text :
https://doi.org/10.3233/SW-150194