Semantic modelling of animal welfare explained – Part 1: Calculating overall welfare scores for husbandry systems using the ANyWEL model framework

Abstract. A modern evidence-driven approach to assess the welfare of farm animals is semantic modelling. It enables the (semi-)quantitative assessment of the overall welfare status, as well as a welfare comparison of different housing systems, through systematic and formalised knowledge extraction from the scientific literature. A semantic model essentially enables a description of housing systems in terms of their welfare-relevant properties (so-called attributes, e.g. space per pen or the availability of enrichment materials) using weighted welfare component scales. Based on this approach, we developed the ANyWEL framework (ANimal WELfare assessment of anY farm animal): a semantic-modelling framework to assess the welfare status of any species of farmed animal kept in housing systems that meet predefined criteria (i.e. the model's assessment domain and the available scientific literature). Compared to previous semantic models, the ANyWEL framework is not restricted to a single species or production direction. It is generalised across species and production directions. Due to its conceptual character, the ANyWEL framework can be applied to new species and systems in the future. We show that it can use new scientific knowledge, even when this would go against mainstream perceptions (e.g. that extensive systems “must be” better for welfare than intensive systems). The objectives of this paper are (i) to explain the general procedure and principles used in semantic modelling, (ii) to introduce the ANyWEL framework by comparing it with a previous semantic model and to illustrate it with an example of a fictitious animal species called anYmal, and (iii) to reflect on the strengths and limitations of this new generalised model framework even with unexpected outcomes.