The Notion of a Model


Models are considered to be the third dimension of science. Disciplines have developed a different understanding of the notion of a model, of the function of models in scientific research and of the purpose of the model. Models are a common culture and common practice in sciences. Models are collaboration enablers.
Models are used as perception models, experimentation models, formal models, conceptual models, mathematical models, computational models, physical models, visualisation models, representation models, diagrammatic models, exploration models, heuristic models, etc. Experimental and observational data are assembled and incorporated into models and are used for further improvement and adaptation of those models. Models are used for theory formation, concept formation, and conceptual analysis. Models are used for a variety of purposes such as perception support for understanding the application domain, for shaping causal relations, for prognosis of future situations and of evolution, for planning, for retrospection of previous situations, for explanation and demonstration, for preparation of management, for optimisation, for construction, for hypothesis verification, and for control of certain environments. Models provide a utility to research and have an added value in research, e.g. for construction of systems, for education, for the research process itself. Their added value is implicit however can be estimated based on the model's capability.
Models are often language based. Their syntax uses the namespace and the lexicography from the application domain. Semantics is often implicit. The lexicology can be inherited from the application domain and from the discipline. Models do not need the full freedom for interpretation. The interpretation is governed by the purpose of the model within the research scenario, is based on disciplinary concerns (postulates, paradigms, foundations, commonsense, culture, authorities, etc.) and is restricted by disciplinary practices (concepts, conceptions, conventions, thought style and community, good practices, methodology, guidelines, etc.). Models combine at least two different kinds of meaning in the namespace: referential meaning establishes an interdependence between elements and the origin ("what"); functional meaning is based on the function of an element in the model ("how"). The pragmatics of a model depends on the community of practice, on the context of the research task and especially on the purpose or function of the model. Languages may be restricted to well-formed expressions. The development of an instrument as an artefact is supported by development methods.

The novel notion of a model

A model is a well-formed, adequate and dependable instrument that represents other origins within some context based on criteria of adequacy and dependability commonly accepted by its community of practice. A model has - as an instrument - its background with a undisputable grounding of the sub-discipline and with a basis consisting of chosen elements from the sub-discipline. A model is functioning if it is combined with utilisation/deployment methods. A functioning model is effective if it can be successfully deployed according to its deployment scenarios and its portfolio. They thus function in the application scenario ('deployment games').

This notion has been validated and verified against the model notions of many disciplines in our modelling community at CAU.
In different discipliens, models are built and modelling is performed in a similar form, with similar background and theories and within similar investigation scenarios despite the variety of models, the variety of purposes, the complexity, the range from micro to macro, and the variety of solutions. Each discipline has been developing also specific solutions to modelling and model deployment. These solutions may also be used for other disciplines, may be combined with their solutions, or may replace their solutions.

Some recent papers by B. Thalheim on models and modelling

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