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From AGROVOC to the Agricultural Ontology Service / Concept Server

An OWL model for creating ontologies in the agricultural domain








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    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
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    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.
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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.
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    Document
    The AGROVOC Concept Server Workbench: A collaborative tool for managing multilingual knowledge 2008
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    Ontology plays an important role in the enhancement performance of systems, addressing issues such as knowledge sharing, knowledge aggregation as well as information retrieval and question answering. This paper presents the AGROVOC Concept Server Workbench (ACSW) for multilingual ontological concept construction and maintenance. The ACSW is a web 2.0 based application consisting of two main functionalities that are user management and ontological knowledge management (i.e. concept, sch eme, relationship, export, search, validate and consistency check) in order to maintain the knowledge acquisition life-cycle in food and agriculture domain. Knowledge is stored in the form of multilingual concept hierarchy and also kept in the OWL format in order to exchange between machines and to do reasoning. This workbench uses Protégé API as an OWL framework. Moreover the Ontology Game conceptual framework is also presented in order to acquire ontology terms more pleasant.

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