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The purpose of the paper is to obtain insight into, and provide practical advice for, event‐based conceptual modeling.

The paper analyzes a set of event concepts and uses the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static information models.

The paper characterizes events as short‐duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can be used to integrate dynamic modeling of processes and static modeling of information structures.

The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used to improve dynamic and static modeling.

Compares experimental (eg. prototyping) and analytical (eg. specifying) approaches in systems design. Derives ′The Principle of Limited Reduction′. Defines this as: “Relying on an analytical mode of operation to reduce complexity introduces new sources of uncertainty requiring experimental countermeasures; relying on an experimental mode of operation to reduce complexity introduces new sources of uncertainty requiring analytical countermeasures”. Concludes that a mixed approach is best, but warns that this is as yet (1992) hypothetical.