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                <term xml:lang="en">MODELS</term>
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                <term xml:lang="en">AGRICULTURAL POLICIES</term>
                <term xml:lang="en">SUSTAINABLE DEVELOPMENT</term>
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                <term xml:lang="en">FORECASTING</term>
                <term xml:lang="en">SUSTAINABILITY</term>
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                <term xml:lang="fr">GESTION DES CONNAISSANCES</term>
                <term xml:lang="fr">DEVELOPPEMENT DURABLE</term>
                <term xml:lang="fr">POLITIQUE AGRICOLE</term>
                <term xml:lang="fr">INTERDISCIPLINARITE</term>
                <term xml:lang="fr">MODELE</term>
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              <p>Integrated Assessment and Modelling (IAM) provides an interdisciplinary approach to support ex-ante decision-making by combining quantitative models representing different systems and scales into a framework for integrated assessment. Scenarios in IAM are developed in the interaction between scientists and stakeholders to explore possible pathways of future development. As IAM typically combines models from different disciplines, there is a clear need for a consistent definition and implementation of scenarios across models, policy problems and scales. This paper presents such a unified conceptualization for scenario and assessment projects. We demonstrate the use of common ontologies in building this unified conceptualization, e.g. a common ontology on assessment projects and scenarios. The common ontology and the process of ontology engineering are used in a case study, which refers to the development of SEAMLESS-IF, an integrated modelling framework to assess agricultural and environmental policy options as to their contribution to sustainable development. The presented common ontology on assessment projects and scenarios can be reused by IAM consortia and if required, adapted by using the process of ontology engineering as proposed in this paper. (C) 2009 Elsevier Ltd. All rights reserved.</p>
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