During an emergency, water and land resources managers are required to make decisions quickly and often on the basis of information of poor quality, or needed data is inaccessible, and/or incomprehensibly displayed. Frequently, they need to ask a series of "what if" questions to rapidly determine the next actions to take and are often frustrated by not getting the help and information they need. Sulis is a computer-based decision support system to help decision makers of many types make not only routine decisions but also decisions needed in an emergency.
This proposal continues the on-going research and development of Sulis by extending the current structure and starting research and development of the inference engine in support of the NGI effort to define the ecosystem perturbations caused by the Macondo 252 oil spill. The first part of the work described in this proposal is extending and improving the infrastructure of the Sulis framework and is development work needed to expand the entire system. Critical to the success of this portion of the effort will be involvement of subject-matter experts and two case studies that will enable testing and evaluation of the framework. The second part of the work is fundamental research into the use of advanced computer-based reasoning and decision techniques, incorporated into the part of Sulis called the inference engine. Additionally, we will work with and incorporate the work on uncertainty analysis and visualization proposed by Dr. Song Zhang of MSU.