Model composition in a distributed environment
Decision Support Systems
A web services framework for distributed model management
Information Systems Frontiers
Research in Information Systems: An Empirical Study of Diversity in the Discipline and Its Journals
Journal of Management Information Systems
Model composition in multi-dimensional data spaces
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
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Decision models are often based on certain assumptions as to their validity. Relevant assumptions may include value-based assumptions, such as limitations on the range or values of some input variables or exogenous factors, as well as assumptions about model structure (e.g., linearity). In a model base consisting of many models, there may be several models (or collections of models) that can be used to solve a particular problem. We may wish to know what the applicable models are, what assumptions are associated with these models, and whether a given set of assumptions is necessary and/or sufficient for solving the problem. We describe an analytical approach, based on a graph-theoretic construct called a metagraph, and show how it can be used to represent and analyze assumptions in model bases.