Prof. Ghassan Beydoun, UTS, Australia

Abstract:

To facilitate Disaster Management knowledge sharing many international and national bodies create knowledge models to allow knowledge sharing and effective DM activities. But these are often narrow in focus and deal with specified disaster types. Over the past seven years, we have undertaken research to enable the unification of DM knowledge across various disaster types and jurdisctions. In this talk, I will describe our disaster-indepedent descritpion that models common DM activities across various events. It enables partitioning a DM problem into sub-problems. Decision makers can then develop a variety of domain solutions models based on mixing and matching solutions for sub-problems indentified using the metamodel. A repository of domain knowledge structured using the metamodel would allow the transformation of models generated from a higher level to a lower level according to scope of the disaster problem on hand. In developed countries, for recurring disasters (e.g. floods), there are dedicated document repositories of Disaster Management Plans (DMP) that can be accessed as needs arise. However, accessing the appropriate plan in a timely manner and sharing activities between plans often requires domain knowledge and intimate knowledge of the plans in the first place. I will describe an agent-based knowledge analysis method to convert DMPs into a collection of knowledge units that can be stored into a unified repository based on the unifiying metamodel. The repository of DM actions then enables the mixing and matching knowledge between different plans. We use the flood management plans used by SES (State Emergency Service), an authoritative DM agency in NSW (New State Wales) State of Australia to illustrate and give a preliminary validation of the approach. It is illustrated using DMPs along the flood prone Murrumbidgee River in central NSW. I will also conclude by examining the opportunities to capture real time constraints in the provision of knowledge services offered by this approach.

Brief biography:

Ghassan Beydoun is a Professor of Information Systems at the School of Systems, Management and Leadership at University of Technology, Sydney. He received a degree in computer engineering and a PhD degree in knowledge systems from the University of New South Wales. His research interests include complex systems modelling, distributed decision support systems and knowledge analysis. He has been applying his results in developing decision support systems for disaster management, multi agent systems, e-learnin g systems and other areas. He is currently working on a project sponsored by an Australian Research Council Discovery Grant to investigate the best uses of domain knowledge in developing methodologies for complex systems and at the same time working on decision support systems with SES on exploring the use of ontologies for flood management decision support. He has authored more than 100 journal and conference papers in these areas over the past 15 years. His most recent publication appeared in Information and Management, Information Systems Frontiers, IEEE Transactions of Software Engineering, Information Systems journal, International Journal of Human Computer Studies, Information Processing and management and others. He serves on the board of a number of international journals including: International Journal of Intelligent Information Technologies (IJIIT), Journal of Software and others.