Integration of Models, Data and Expert Knowledge by Means of Indicators: the Seamless Project Experience

1 Business Economics, Wageningen University, the Netherlands ({irina.bezlepkina,sander.jansen,rob.knapen}@wur.nl) 2 Lunds University Centre for Sustainability Science, Sweden ([email protected]) 3 Dalle Molle Institute for Artificial Intelligence, Lugano, Switzerland ({ioannis,hongtao}@idsia.ch 4 AntOptima, Lugano, Switzerland ([email protected]) 5 INRA UMR INPL(ENSAIA)-INRA Nancy-Colmar, Colmar France ([email protected]) INRA Montpellier,France ([email protected]) 7 INRA Toulouse, France ([email protected]) Introduction The European Commission has introduced impact assessment as an essential step in the policy development. In the SEAMLESS integrated project (http://seamless-ip.org), researchers work to develop a computerised Integrated Framework, aiming to provide (among others) with a set of economic, social and environmental indicators allowing the assessment of ex-ante, alternative agricultural and environmental policy options. Stakeholders’ involvement is of crucial importance in impact assessment (European Commission, 2005). Key requirement for SEAMLESS-IF is consequently to be generic and transparent for different types of user groups. Indicators in SEAMLESS are built upon model outputs. However for social indicators model support is weak so the number of social indicators is low. These indicators will instead based on simple causal relations, expected trends and expert or stakeholder assessment. Moreover, threshold and target levels are essential to contextualise indicators. Stakeholders define threshold and target levels and their quantification. The challenge for SEAMLESS-IF is therefore to deploy a software implementation that enables the integration of the results from mechanistic models with the information provided by different types of stakeholder groups.