From AGROVOC to the Agricultural Ontology Service / Concept Server

Boris Lauser, Margherita Sini, Anita Liang, Johannes Keizer, Stephen Katz

From AGROVOC to the Agricultural Ontology Service / Concept Server

An OWL model for creating ontologies in the agricultural domain

Year of publication 2006

Pages 10

Author Boris Lauser, Margherita Sini, Anita Liang, Johannes Keizer, Stephen Katz

Product type Book (stand-alone)

Edition 1

Full item page

Synopsis (short abstract) 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.

Language English

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French

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Project

D7.2.2: Revised and enhanced fisheries ontologies
NeOn: Lifecycle Support for Networked Ontologies, Integrated Project (IST-2005-027595). Priority: IST-2004-2.4.7, "Semantic-based knowledge and content systems"
2007

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This document describes and discusses the fisheries ontologies developed for use within the Fish Stock Depletion Assessment System (FSDAS). All ontologies are publicly available from the FAO website, from http://www.fao.org/aims/aos/fi. This document is organized as follows. In Chapter 1 we place our work in the context of the WP7 case study. In Chapter 2 we describe previous attempts to create ontologies for the fisheries domain. In Chapter 3 we recap the user requirements presented i n our previous deliverable D7.1.1, with special attention to the functionalities needed for modelling, population and maintenance. In Chapter 4 we describe the domains and the data on which the ontologies described here are based. In Chapter 5 we describe the fisheries database where the data used to populate the fisheries ontologies is stored; we also introduce the tool used for population of the ontologies. In Chapter 6 we describe the models of all ontologies produced. In Chapter 7 we discuss some features of the ontologies. In Chapter 8 we summarize the lessons learned in the course of this work. Finally, in Chapter 9 we draw our conclusions. This document also includes four Annexes: the list of naming conventions adopted (Annex I), an essential glossary of fisheries terms (Annex II) a list of acronyms (Annex III) and a report on the conversion of the XML schema for fisheries factsheets into an ontology.
Document

The AGROVOC concept server: rationale, goals and usage 2007

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The main objective of the AGROVOC Concept Server (CS)is to create a collaborative reference platform and a one-stop shop for a pool of commonly used concepts related to agriculture, containing terms, definitions and relationships between terms in multiple languages derived from various sources. This paper aims to address the issues.
Book (stand-alone)
D'AGROVOC a l'Agricultural Ontology Service / Concept Server
Un modele OWL pour la creation d'ontologies dans le domaine de l'agriculture
2006

Also available in:

English

Cet article décrit la conversion du thésaurus AGROVOC dans sa forme traditionnelle en un service d'ontologies dans le domaine de l'agriculture (Agricultural Ontology Service/Concept Server AOS/CS). Ce Serveur de concepts (AOS/SC) est un entrepôt multilingue de concepts dans ce domaine proposant des relations ontologiques et une terminologie étendue et sémantiquement riche. L'Organisation des Nations Unies pour l'alimentation et l'agriculture, FAO (Food and Agriculture Organization) a récemment d éveloppé le modèle pour ce nouveau système dans le langage d’ontologies : OWL. Dans cet article, nous décrivons l'objectif de cette conversion et l’utilisation du langage OWL ; nous mettons en évidence en particulier les principales fonctionnalités de ce modèle OWL. Nous avons voulu expliquer comment il évolue et diffère de l'approche traditionnelle des thesauri.