Division of Computing and Communication Foundations
Foundations of Data and Visual Analytics
(FODAVA)
CONTACTS
PROGRAM GUIDELINES
Solicitation
09-525
Please be advised that the NSF Proposal & Award Policies & Procedures Guide (PAPPG) includes
revised guidelines to implement the mentoring provisions of the America COMPETES Act (ACA)
(Pub. L. No. 110-69, Aug. 9, 2007.) As specified in the ACA, each proposal that requests
funding to support postdoctoral researchers must include a description of the mentoring
activities that will be provided for such individuals. Proposals that do not comply
with this requirement will be returned without review (see the PAPP Guide Part I:
Grant Proposal Guide Chapter II for further information about the implementation of
this new requirement).
DUE DATES
Full Proposal Deadline Date: January 20, 2010
Third Wednesday in January, Annually Thereafter
SYNOPSIS
Individuals working in areas as diverse as science, engineering, finance, medicine, and national security all face the challenge of synthesizing information and deriving insight from massive, dynamic, ambiguous and possibly conflicting digital data. The goal of collecting and examining these data sets is not to merely acquire information, but to derive increased understanding from them and to facilitate effective decision-making. To capitalize on the opportunities provided by these data sets, research in Data and Visual Analytics seeks to facilitate analytical reasoning through the use of interactive visual interfaces. To be successful, this research must extend beyond traditional scientific and information visualization to include statistics, mathematics, knowledge representation, management and discovery technologies, cognitive and perceptual sciences, decision sciences, and more. With this solicitation, the National Science Foundation (NSF) and the Department of Homeland Security (DHS) invite research proposals whose outcomes will enable data stakeholders to detect the expected and discover the unexpected in massive data sets. Research outcomes will be applicable across broad application areas, establishing a solid scientific foundation for visual analytics systems of the future. Proposals should focus on creating fundamental research advances that will be widely applicable across scientific, engineering, commercial, and governmental domains that utilize visualization and analytics to gain insight and derive knowledge from massive, often streaming, dynamic, ambiguous and possibly conflicting, data sets. Research activities proposed should emphasize novel data transformations, while also demonstrating research relevance to visual analytics systems by including a research component in areas such as, but not limited to, visualization, human-computer interaction, and cognitive psychology.
THIS PROGRAM IS PART OF
Additional Funding Opportunities for the CCF Community
Additional Funding Opportunities for the IIS Community
Special Research Programs
Abstracts of Recent Awards Made Through This Program
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