“to model is to write a prescription on how to synthesise data that model experimental data”
This main idea is developed in Scientific modelling, model prescription and the lightness of data. On the right you can find several examples of model prescriptions that can be applied to biological chemistry or biophysics undergraduate laboratory experiments.
The linguistic description is proposed as the centrepiece of scientific modelling, being the way by which the concepts that are considered relevant to a target system’s composition and behaviour are presented, manipulated and communicated. The expression “model prescription” is used to mean the linguistic piece that describes a target system and consequently prescribes the production of synthetic data intended to model physically acquired data. The model prescription is in itself a concept of a target system that uses other systems’ concepts, as well as concepts of objects, properties, relations and actions, to describe its structure and behaviour. The communication of a model prescription is therefore dependent on the intersubjective understanding and acceptance of the concepts used. Disentangled and narrower concepts of model and graphics are proposed. “Model” is restricted to representation by the same kind, categorically matched, while representations by different kind are named “graphics”. Data is identified as the sole touching point between physical systems and its human conceptualizations and the use of data-based inference by regression is analysed and some problems identified. Besides logical-mathematical relations, causal relations are an important part of modelling and a strict characterization of causal mechanisms is made based on energy transfers. Modelling examples are given to illustrate the generality of the definitions used as well as some of the problems with scientific modelling.
model prescription; scientific model; scientific modelling; inference from empirical data; causal relations; linguistic description of target systems.