Abstract collage of science-related imagery

Foundations of Data and Visual Analytics (FODAVA)

Status: Archived

Archived funding opportunity

This document has been archived.

Important information for proposers

All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements. Submitting a proposal prior to a specified deadline does not negate this requirement.

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.

 

Program contacts

Lawrence Rosenblum (CS Contact)
Program Director, Directorate for Computer & Information Science & Engineering, CCF Division
lrosenbl@nsf.gov (703) 292-8910
Tie Luo (Math Contact)
Program Director, Directorate for Mathematical and Physical Sciences, DMS Division
tluo@nsf.gov (703) 292-8448 MPS/OAD
Sankar Basu
Program Director, Directorate for Computer & Information Science & Engineering, CCF Division
sabasu@nsf.gov (703) 292-7843 CISE/CCF
Ephraim Glinert
Program Director, Directorate for Computer & Information Science & Engineering, IIS Division
eglinert@nsf.gov (703) 292-8930 CISE/IIS
Leland Jameson
Program Director, Directorate for Mathematical and Physical Sciences, DMS Division
ljameson@nsf.gov (703) 292-4883
Maria Zemankova
Program Director, Directorate for Computer & Information Science & Engineering, IIS Division
mzemanko@nsf.gov (703) 292-8930

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