Chapter 1: No model without a Purpose Modelling Purposes in the context of research Explain X (Why is X the case?): An explanation assumes the presence of some accepted theory in which the explanation should make sense Predict X (When will X happen (if)? What will happen to X (if)?) Compress X (How can X be written down in a more compact form?) Abstract X (What is essential in X?): gives an explanation Unify (What do X and Y have in common?): providing a representation that allows explanations and predictions in two domains that initially were thought unrelated. Unification is a special case of abstraction; leaving out details in the hope that the remaining essentials allow for generic explanation, applying to two (or more) domains. Analyse X (What is the relation between X and Y?): analysis (deduce properties) or do predictions. To do predictions some analysis is required, not all analysis lead to prediction Modelling purposes in the context of design Data compression: al large and heterogeneous amount of information should be condensed into a structured and accessible format Communicate (How do I make sure person P knows X?) Specify (Which requirements should X (which does not yet exist) fulfil?) Exploration (What are the various possibilities for X?): closed = all possible outcomes are fully known beforehand. Open = the designer has to invent the alternatives Optimization (What should we choose for Y such that X is as large or as small as possible?) Decide (What do I choose for X so that some condition is fulfilled?) Verify X (Is it true that X holds?) Steer and control (What interventions should take place in X such certain conditions hold?) Train (How could a prospective user learn to operate X without actual dealing with X?) Model Dimensions Material – Immaterial Material: Models involving material objects (natural object (guinea pig) or artefact (scaled down model)) Immaterial: formal models such as mathematical, logical or software models Static – Dynamic Static: involves only stationary quantities Dynamic: models that involve time Continuous – Discreet Continuous: quantity can assume any value (weight, height, speed) Discreet: Quantity that can only occur as an integer (number of people, cars, etc) Numerical – Symbolic Symbolic: Uses mathematical analysis
Chapter 1: No model without a Purpose Modelling Purposes in the context of research Explain X (Why is X the case?): An explanation assumes the presence of some accepted theory in which the explanation should make sense Predict X (When will X happen (if)? What will happen to X (if)?) Compress X (How can X be written down in a more compact form?) Abstract X (What is essential in X?): gives an explanation Unify (What do X and Y have in common?): providing a representation that allows explanations and predictions in two domains that initially were thought unrelated. Unification is a special case of abstraction; leaving out details in the hope that the remaining essentials allow for generic explanation, applying to two (or more) domains. Analyse X (What is the relation between X and Y?): analysis (deduce properties) or do predictions. To do predictions some analysis is required, not all analysis lead to prediction Modelling purposes in the context of design Data compression: al large and heterogeneous amount of information should be condensed into a structured and accessible format Communicate (How do I make sure person P knows X?) Specify (Which requirements should X (which does not yet exist) fulfil?) Exploration (What are the various possibilities for X?): closed = all possible outcomes are fully known beforehand. Open = the designer has to invent the alternatives Optimization (What should we choose for Y such that X is as large or as small as possible?) Decide (What do I choose for X so that some condition is fulfilled?) Verify X (Is it true that X holds?) Steer and control (What interventions should take place in X such certain conditions hold?) Train (How could a prospective user learn to operate X without actual dealing with X?) Model Dimensions Material – Immaterial Material: Models involving material objects (natural object (guinea pig) or artefact (scaled down model)) Immaterial: formal models such as mathematical, logical or software models Static – Dynamic Static: involves only stationary quantities Dynamic: models that involve time Continuous – Discreet Continuous: quantity can assume any value (weight, height, speed) Discreet: Quantity that can only occur as an integer (number of people, cars, etc) Numerical – Symbolic Symbolic: Uses mathematical analysis
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