The evolution and problems of model management research

The evolution and problems of model management research

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Article ID: iaor19921218
Country: United Kingdom
Volume: 19
Start Page Number: 511
End Page Number: 528
Publication Date: Dec 1991
Journal: OMEGA
Authors: , ,
Keywords: artificial intelligence: expert systems, computers: data-structure, Computers: data structure
Abstract:

Models are a key resource for organizational decision making. The diversity, complexity, and reusability of this resource result in the need for model management systems. The construction of a model management system involves a modeling task dimension and a design level dimension. The modeling task dimension consists of model formulation, model representation, and model processing. The design level dimension addresses the architectural requirements of a system from a user’s standpoint and a computer system’s standpoint. The numerous architectures suggested in the model management systems literature address isolated areas identified by these dimensions. The research surveyed in this paper indicates that the primary focus has been on the system view of model representation. Before model management systems can be widely used in organizations, model management researchers must explore systems that address all areas of the task and design dimensions. In this paper, the authors identify and justify the necessary dimensions of model management research. Next, the existing model management research is critically reviewed. Finally, neglected research areas are discussed, and investigations necessary for the development of integrated model management systems are suggested.

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