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MODELLING AS A DISCIPLINE

Modelling is an essential and inseparable part of all scientific, and indeed all intellectual, activity. How then can we treat it as a separate disciphne? The answer is that the professional modeller brings special skills and techniques to bear in order to produce results that are insightful, reliable, and useful. Many of these techniques can be taught formally, such as sophisticated statistical methods, computer simulation, systems identification, and sensitivity analysis. These are valuable tools, but they are not as important as the ability to understand the underlying dynamics of a complex system well enough to assess whether the assumptions of a model are correct and complete. Above all, the successful modeller must be able to recognise whether a model reflects reality, and to identify and deal with divergences between theory and data. Theories can be wrong or merely incomplete, and even “raw” data are just the outputs of experimental interpretations, i.e., models. These points are illustrated with examples from the scientific literature, accompanied by horror stories of modelling projects gone awry.