Fundamental studies and their applications for ontological engineering and decision support systems for energy production and pollution processing systems

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Concerns about Canada's laggard productivity have been widely reported in the national media.  Given the importance of the oil and gas industry in Canada, the significant socio-economic impacts and costs of declining productivity in the industry requires urgent attention from the R&D sector of the economy.  It has been suggested that the reduced productivity in Canadian industries is due to our relatively low investments in information and communications technologies compared to the United States (Globe & Mail, Sept 9, 2005).  The proposed research program will address this concern by enhancing understanding of issues and problems related to development and application of advanced information technologies for improving productivity of industrial processes.  This program aims to build infrastructure for supporting construction of knowledge-based decision support systems, which assist operators and managers in performing complex tasks in industrial processes.  The research objectives include: (a) developing methods and tools for ontological engineering, which support building the knowledge foundations for intelligent decision support systems, and (b) developing artificial intelligence and knowledge-based system technologies for modeling and analysis of energy production and pollution processing systems. The advanced computing solutions developed will help enhance productivity and efficiency of some petroleum- and carbon dioxide-related processes in Canadian industries, which are in urgent need of cost-effective means of improving productivity.