Data as models: An approach to implementing model management

The concept of model management as a logical extension and parallel of data management has resulted in attempts to extend existing data models to incorporate modeling functionality. This fosters a data-oriented view which artificially restricts the domain of model management. This paper suggests that a model-oriented approach which views ‘data as a model’ not only expands the scope of model management but also offers a more integrated and balanced conceptual foundation from which to implement model management. On the organizational level, this approach recognizes the transition from informal modeling as exemplified by the use of spreadsheets to formal modeling which manages models as a resource in conjunction with data. The notion of information administration is introduced as an organizational mechanism for controlling this evolution. On the technological level, a generalized model management system (GMMS) is required for support of organizational modeling activities. Geoffrion's structured modeling is suggested as a foundation from which to build a model-oriented GMMS. The incorporation of artificial intelligence capabilities into a GMMS is seen as a second implementation step which require the development of a sufficiently flexible meta-level architecture. Model abstractions are introduced as a vehicle for implementing this architecture.