Posted · 09-525
Foundations of Data and Visual Analytics
U.S. National Science Foundation · NSF
CFDA Numbers
47.049, 47.070
Award Ceiling
$500K
Award Floor
$300K
Expected Awards
5
Close Date
—
Section I
How to Apply
Program Contact
NSF grants.gov support <br/>grantsgovsupport@nsf.gov <br/>
grantsgovsupport@nsf.gov
Section II
Eligibility
Eligible Applicant Types
99
Section III
Description
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.
Section IV
Key Dates
- Posted
- Jan 6, 2009
- Archive
- Sep 26, 2010