Scientists often do not have the software design skills, for implementing their theories with such flexible linkage and organizational structure. The system should therefore enable them to implement the science without investing in software design skills. It should be possible to use either a GUI aided model builder or simple interfaces to implement algorithms, customize calibration routines or configure model input and output. Additionally, current framework design should enable scientists to overcome fragmentation in methods and tools. Therefore it has to offer to the scientist the possibility to use and reuse model components developed in different domains seamlessly.
Engineers, in contrast, often do not want to be confronted with developing and scientifically validating model components, but are rather interested in optimizing systems or solving specific real world problems. This can be achieved using sets of readily available model solutions that are robust and well documented. The underlying problem solving approaches of scientific and engineering oriented modeling are fundamentally different. The former typically involves defining or changing the structure of a mathematical model while the latter is more oriented towards tuning its parameters and applying the tools for solving specific problems or decision questions. Modeling frameworks offer excellent opportunities for formally bridging between these two different modeling approaches for the benefit of scientists and engineers who want to learn from each other.
Decision makers are another important user group of modeling frameworks. Often they need model-based scenario analyses and visualization of results in simple graphs or maps. The group of decision makers is very diverse, including, for instance extension officers, wildlife park managers, farmers, members of environmental protection agencies, national authorities and even multi-national organizations. Each of these groups is presumably neither interested in the engineering nor the scientific components of a modeling framework but simply wants to utilize its capacity for decision making. Scientific documentation is provided in: SIMPLACE - A versatile modelling and simulation framework for sustainable crops and agroecosystems