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Reengineering Thesauri for New Applications: the AGROVOC Example








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    From thesauri to Ontologies: A short case study in the food safety area in how ontologies are more powerful than thesauri From thesauri to RDFS to OWL
    From thesauri to RDFS to OWL
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    This short case study will show on the basis of a simple example taken from the Food Safety area, how ontologies differ from thesauri. The example will start with showing an extract from the AGROVOC thesaurus, and exploring the information that can be extracted from here. We will then develop this example further in order to show growing functionality and expressive power first in RDFS and finally in OWL ontologies.
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    Automatic Term Relationship Cleaning and Refinement for AGROVOC 2005
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    AGROVOC is a multilingual thesaurus developed and maintained by the Food and Agricultural Organization of the United Nations. Like all thesauri, it contains some explicit semantics, which allow it to be transformed into an ontology or used as a resource for ontology construction. However, most thesauri, AGROVOC included, give very broad relationships that lack the semantic precision needed in an ontology. Many relationships in a thesaurus are incorrectly applied or defined too broadly. According ly, extracting ontological relationships from a thesaurus requires data cleaning and refinement of semantic relationships. This paper presents a hybrid approach for (semi-)automatically detecting these problematic relationships and for suggesting more precisely defined ones. The system consists of three main modules: Rule Acquisition, Detection and Suggestion, and Verification. The Refinement Rule Acquisition module is used to acquire rules specified by experts and through machine learning. The Detection and Suggestion module uses noun phrase analysis and WordNet alignment to detect incorrect relationships and to suggest more appropriate ones based on the application of the acquired rules. The Verification module is a tool for confirming the proposed relationships. We are currently trying to apply the learning system with some semantic relationships to test our method.
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    From AGROVOC to the Agricultural Ontology Service / Concept Server
    An OWL model for creating ontologies in the agricultural domain
    2006
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    This paper illustrates the conversion from a traditional thesaurus in agriculture (AGROVOC) to a new system, the Agricultural Ontology Service Concept Server (AOS/CS). The Concept Server will serve as a multilingual repository of concepts in the agricultural domain providing ontological relationships and a rich, semantically sound terminology. The Food and Agriculture Organization recently developed the underlying model for this new system in the Web ontology language OWL. In this paper, we desc ribe the purpose of this conversion and the use of OWL and highlight in particular the core features of the developed OWL model. We go on to explain how it evolves and differs from the traditional thesaurus approach.

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