Automated sensor units and information systems have the potential to transform and advance hazard management. The combined efforts of such systems could help scientists manage and mitigate both extreme hazards such as large-scale explosions in urban environments and chronic hazards such as long-term environmental pollution.

Recent developments in sensors and information technologies allow efficient monitoring and assessment of complex, system-wide interactions. To accomplish this, however, the information systems used must often combine information from multiple sensor systems, which can range from large-scale, satellite-mapping systems to small-scale networked devices enabling real-time measurement of physical qualities like water levels in an estuary. To transform the field of hazard management, multidisciplinary teams of experts must work together to make these sensor systems and their data an integrated and useable source of information.

Barbara Minsker, Tim Wentling, Michael Welge, Tom Prudhomme, Duane Searsmith, David Goldberg, and Dan Roth are developing a framework that can be used to effectively assess and manage hazards. Their collaborative framework will provide real-time, multi-objective access and integration of different types of data, models, and knowledge archives. It will include:

• A knowledge center with collaboration space including a message board, chat room, multipoint video conferencing system, a mechanism for locating and contacting experts to whom users can pose questions, and an e-learning management system capable of accepting recordings of presentations, slides, text instructional materials, and other forms of curriculum materials.
• An information extraction system that will effectively identify key documents relevant to topics of interest in hazard management.
• Two decision support tools--Evolutionary Multi-objective Optimization (EMO), and Distributed Innovation and Scalable Collaboration in Uncertain Settings (DISCUS), which are under development at TRECC.

All of these components will be adapted and combined in the framework to fit the computational Grid infrastructure at NCSA. The framework will undergo rigorous evaluation at a test bed carefully chosen by the project team.

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