OpportunityTitle: Cooperative Ecosystem Studies Unit, Rocky Mountain CESU
AdditionalInformationOnEligibility: This financial assistance opportunity is being issued under a Cooperative Ecosystem Studies Unit (CESU) Program.  CESU&#146;s are partnerships that provide research, technical assistance, and education.  Eligible recipients must be a participating partner of the Rocky Mountain Cooperative Ecosystem Studies Unit (CESU) Program.
Description: The purpose of the Northern Rocky Mountain Science Center (NOROCK) funding opportunity is to develop techniques and tools suited to tailored collection and dissemination of Web pages related to climate modeling. Little prior research has focused on either persistent information needs or Web information needs for a specific targeted user community. These two characteristics afford significant opportunities for exploitation in the methods developed. Another objective is to support understanding of climate change models by potential users. The results of tool application (harvested and organized Web pages) should help the user base figure out which models to use and how to use them. Long term, seek to develop technologies to support decision making using climate models. Ultimately, the decision could be very diverse from natural resource managers making species management decisions to climatologists determining future directions. In addition, the most likely technologies are expected to include personalized Web retrieval, tailored and possibly dynamic Web page organization to serve browsing, machine learning of capabilities of climate models, and representations of models that guide users in parameterization and interpretation of results. Overall, through this particular funding opportunity, goals are: 1) to develop a system for constructing search queries, submitting them to one or more search engines and disseminating the results to interested users who will offer relevance feedback; 2) to design a repository for persistent storage and sharing of the Web pages collected using the relevance feedback driven system; and 3) identify the machine learning and information retrieval techniques that are most effective for tailored search for this user community.
GrantorContactEmailDescription: Contract Specialist
GrantorContactText: FAITH GRAVES &lt;br/&gt;Contract Specialist &lt;br/&gt;Phone 703-648-7356