We developed the ANyWEL (ANimal WELfare assessment of anY farm animal) model for improved semantic modelling. The model allows for the synthesis of scientific information about animal welfare. Housing conditions can be compared and ranked and welfare-relevant properties can be distinguished. We explain how this procedure works through a fictitious animal species. Herewith, semantic modelling becomes more transparent with regard to how scientific knowledge can be used to produce overall welfare scores.

Semantic modelling is a procedure that can be used to assess overall animal welfare. Through the selection of scientific statements, semantic models can generate overall welfare scores. Our objective was to provide guidelines to make semantic modelling more formalised and transparent and to facilitate the use of this methodology to assess (farm) animal welfare. Ultimately, those guidelines should aid (new) modellers in applying the principles of semantic modelling in a standardised way.