TOVE Project

An Enterprise Model is a computational representation of the structure, activities, processes, information, resources, people, behaviour, goals and constraints of a business, government, or other enterprise. It can be both descriptive and definitional – spanning what is and what should be. The role of an enterprise model is to achieve model-driven enterprise design, analysis and operation.

In order to support enterprise integration, it is necessary that shareable representation of knowledge be available that minimizes ambiguity and maximizes understanding and precision in communication. Secondly, the creation of such a representation should eliminate much of the programming required to answer “simple” common sense questions about the enterprise.

The goal of the TOVE (TOronto Virtual Enterprise) project is to create a generic, reusable enterprise data model that has the following characteristics:

  • provides a shared terminology for the enterprise that each agent can jointly understand and use,
  • defines the meaning of each term (aka semantics) in a precise and as unambiguous manner as possible,
  • implements the semantics in a set of axioms that will enable TOVE to automatically deduce the answer to many “common sense” questions about the enterprise, and
  • defines a symbology for depicting a term or the concept constructed thereof in a graphical context.

The TOVE reusable representation represents a significant ontological engineering of industrial concepts.

Our ontology spans: activities, state, causality, time, resources, inventory, order requirements, and parts. We have also axiomatised the definitions for portions of our knowledge of activity, state, time, and resources. The axioms are implemented in Prolog and provide for common-sense question answering via deductive query processing.

An overview of the TOVE project can be found in: Fox, M.S., (1992), “The TOVE Project: A Common-sense Model of the Enterprise”, Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Belli, F. and Radermacher, F.J. (Eds.), Lecture Notes in Artificial Intelligence # 604, Berlin: Springer-Verlag, pp. 25-34.

The following ontologies have been developed to model Enterprises. For each ontology we provide a link to a paper that defines the ontology. For additional papers, please click on the research papers link in the side bar.