The Knowledge Management Lab
University of Toronto

Research Goals

Conceptual modelling and knowledge representation

We seek appropriate conceptual schemes for representing complex knowledge domains. We identify ontologies and define notations and representational and reasoning frameworks that are appropriate for the subject matter of the application area. Our group has a long track record in developing information modelling techniques (see [Mylopoulos98] for a review) for a number of areas, including data modelling, requirements engineering,
software development, and enterprise modelling. Recent research tasks and advances include:

• an extensible conceptual modelling language, Telos [MBJK90], for supporting
  information system modelling. The language has been adopted by many research groups world wide, and has at least three implementations.
• advancing beyond traditional static and dynamic ontologies to include intentional and social ones:
  • the NFR framework [Chung93] - a goal-oriented framework for dealing with non-functional requirements , and
  • the i* framework [Yu95] - an agent-oriented modelling framework

Technologies and tools

We develop the computational technologies and tools needed to support the various modelling frameworks. The tools provide analysis and reasoning support based on the semantics of the knowledge representation. Repository technology that builds on techniques from database research enables the effective storage and retrieval of large bodies of knowledge.

Processes and methods

We study, model, and analyse usage processes in order to develop methods and guidelines for building models of a given subject matter.