Simulationists, in their daily practice, draw on a vast array of heterogeneous resources, such as mathematical models and computers (hardware and software); input data needed for running the models; results of experiments or observations (for preparing the input data and for comparison with the output); general theories (for basing models on and for comparison with the output); skills and methodologies for developing and evaluating simulations; social relations within all kinds of institutions, be it simulation laboratories,* universities, government and business research institutes, scientic disciplines, professional societies, peer review systems, and the like or society at large. The list of elements of scientic simulation practice can be drawn up, extended, and rened in an unlimited number of ways.†

For analysing epistemological and methodological aspects of simulation, I argue that the activities of simulationists can be conceptually subdivided into four main types: (1) formulating the mathematical model, (2) preparing the model inputs, (3) implementing and running the model, and (4) processing the data and interpreting them.‡ These four types of activities refer to four epistemologically distinct elements in simulation practice: (1) the conceptual and mathematical model; (2) model inputs; (3) the technical model implementation; and (4) processed output data and their interpretation. Clearly, not all resources and activities in scientic simulation practice are captured by these categorisations. In as far as other resources and activities impinge on the four main types of activities, they are taken into account in our description of simulation practice.