Management Science · 1994 · 79 citations · 64 references
EngineeringSystems EngineeringFormal MethodsSystems ArchitectureSystems ModelingConceptual ModelingModel ExecutionModel FormulationModel ManagementModel TransformationSoftware ModelingData IndependenceMeta-modelingMeta-modeling LanguagesModel AbstractionModel CompositionModel Composition SemanticsModel Specification LanguageModeling
We present a new framework for model management based on system concepts and theory. Underlying the framework is a set of meta-modeling concepts that are useful in capturing the semantics of the modeling process in a modeling environment. These concepts include the notions of a general-model type, type specialization, atomic and composite model versions, model instances, and parameterized versions. We describe these concepts both conceptually and formally and then briefly present a Model Description Language (MDL) that embodies them. While other researchers have suggested some of these concepts primarily in different contexts, this paper makes at least four valuable contributions: (1) the identification of fundamental issues and principles related to model management; (2) the development and enhanced treatment of meta-modeling concepts specifically for model management; (3) the synthesis of those concepts into a coherent, unifying framework for model management; and (4) a demonstration of the practicality of those concepts through a prototype system implementation. Our framework proposes a graph-oriented, nonprocedural, and hierarchical approach for model composition. The framework also supports both model-solver independence and model-data independence. Moreover, it offers general solutions to two critical issues in model management: model-model linkage and model-data linkage. We argue that the system framework can serve as a guide for an effective design of a flexible and extensible model management system. An architecture of such a system and its prototype implementation—called SYMMS—are briefly described. Examples are presented to illustrate the features and advantages of our approach.
64
Time Series Analysis: Forecasting and Control
Michael D. Geurts, George E. P. Box, Gwilym M. Jenkins · Journal of Marketing Research · 1977 · 19.3K citations
Computing, Data Science, Forecasting +11
Anthony Brook, David A. Kendrick, Alexander Meeraus · ACM SIGNUM Newsletter · 1988 · 3K citations
Building effective decision support systems
Computers and Standards · 1982 · 1.4K citations
Business, Information Systems, Clinical Decision Support +11
John Miles Smith, Diane C. P. Smith · ACM Transactions on Database Systems · 1977 · 1.4K citations · Full text
The structure of the “THE”-multiprogramming system
Edsger W. Dijkstra · Communications of the ACM · 1968 · 1.1K citations · Full text