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A content-focused method for re-engineering thesauri into semantically adequate ontologies using OWL.
- 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]
- Subjects :
- THESAURI
SEMANTIC Web
ONTOLOGIES (Information retrieval)
Subjects
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