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Synthesis of semantic modelling and risk analysis methodology applied to animal welfare

Published online by Cambridge University Press:  01 July 2008

M. B. M. Bracke*
Affiliation:
Animal Sciences Group, Wageningen University and Research Centre, P.O. Box 65, 8200 AB Lelystad, The Netherlands
S. A. Edwards
Affiliation:
University of Newcastle, School of Agriculture, Food and Rural Development, King George VI Building, Newcastle upon Tyne, NE1 7RU, UK
J. H. M. Metz
Affiliation:
Department of Agrotechnology and Food Sciences, Farm Technology Group, Wageningen University and Research Centre, P.O. Box 6700 AA, Wageningen, The Netherlands
J. P. T. M. Noordhuizen
Affiliation:
Department of Animal Health & Public Health, National Veterinary School of Nantes, Nantes, France Department of Obstetrics, Reproduction & Herd Health, Faculty of Veterinary Medicine, University of Gent, Belgium
B. Algers
Affiliation:
Department of Animal Environment and Health, Faculty of Veterinary Medicine, Swedish University of Agricultural Sciences, P.O. Box 234, SE-53223 Skara, Sweden
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Abstract

Decision-making on animal welfare issues requires a synthesis of information. For the assessment of farm animal welfare based on scientific information collected in a database, a methodology called ‘semantic modelling’ has been developed. To date, however, this methodology has not been generally applied. Recently, a qualitative Risk Assessment approach has been published by the European Food Safety Authority (EFSA) for the first time, concerning the welfare of intensively reared calves. This paper reports on a critical analysis of this Risk Assessment (RA) approach from a semantic-modelling (SM) perspective, emphasizing the importance of several seemingly self-evident principles, including the definition of concepts, application of explicit methodological procedures and specification of how underlying values and scientific information lead to the RA output. In addition, the need to include positive aspects of welfare and overall welfare assessments are emphasized. The analysis shows that the RA approach for animal welfare could benefit from SM methodology to support transparent and science-based decision-making.

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Copyright
Copyright © The Animal Consortium 2008

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