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

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.

Salmon Welfare Index Model (SWIM 1.0): a semantic model for overall welfare assessment of caged Atlantic salmon: review of the selected welfare indicators and model presentation

“…It is designed to take the modeller’s point of view, as much as possible, out of the equation (Bracke et al. 2002b; Bracke 2008; Bracke et al . 2008).…”

“…1999b; Anon 2001), and the selected welfare indicators (WIs) should be species specific, validated, reliable, feasible and auditable (EFSA 2009). There are two closely related approaches for creating OWA models; risk analysis (EFSA 2006a,b; Bracke et al. 2008) and semantic modelling (Bracke et al.…”

Integration: Valuing stakeholder input in setting priorities for socially sustainable egg production

“…Semantic modeling has been used by Bracke and colleagues to evaluate the welfare of sows under different housing conditions (Bracke et al, 2002a(Bracke et al, ,b, 2005(Bracke et al, , 2007(Bracke et al, , 2008. The intent of the procedure is to reduce subjectivity in attribute selection and weighting.…”

Overall welfare assessment of laying hens: Comparing science‐based, environment‐based and animal‐based assessments

“…The decision support system developed by Bracke et al . (2002a) is based on a systematic analysis (‘semantic modelling’) of the scientific literature and therefore called science‐based or information‐based assessment (cf Bracke et al . 2008).…”

“…The decision support system developed by Bracke et al (2002a) is based on a systematic analysis ('semantic modelling') of the scientific literature and therefore called science-based or information-based assessment (cf Bracke et al 2008). It includes a definite selection of measurements including multiple parameters (animal-, environment-and management-based) and the weighting method is based on scientific statements from studies on farm animal welfare.…”