Article ID: | iaor19931638 |
Country: | Switzerland |
Volume: | 38 |
Issue: | 1/4 |
Start Page Number: | 359 |
End Page Number: | 396 |
Publication Date: | Dec 1992 |
Journal: | Annals of Operations Research |
Authors: | Muhanna Waleed A. |
Keywords: | artificial intelligence: decision support |
Central to the Model Management (MM) function is the creation and maintenance of a knowledge-based model repository. The Model Knowledge Base (MKB) provides the basis by which information about models can be shared to facilitate consistent and controlled utilization of existing models for decision making, as well as the development of new models. Various schemes for representing individual models have been proposed in the literature. This paper focuses on how best to structure, control, and administer a large MKB to support organization-wide modeling activities. Guided by a recently proposed systems framework for MM, the paper describes a number of concepts which are useful for capturing the semantics and structural relationships of models in an MKB. These concepts, and the nature of the MMS functions to be supported, are then used to derive specific information management requirements for model bases. Four major requirements are identified: (1) management of composite model configurations; (2) management of model version histories; (3) support for the model consultation and selection functions of an MMS; and (4) support for multiple logical MKBs (private, group, and public). The paper argues that traditional record-based approaches to data management appear to fall short of capturing the rich semantics present in an MM environment. It proposes an architecture for an MMS, focusing on its major component-the MKB Management Subsystem. An implementation of this architecture is briefly described.