This program has been archived.
Directorate for Computer and Information Science and Engineering
Critical Techniques, Technologies and Methodologies for Advancing Foundations and Applications of Big Data Sciences and Engineering (BIGDATA)
|Chaitanya Baruemail@example.com||(703) 292-4541|
|John C. Cherniavskyfirstname.lastname@example.org||(703) 292-5136|
|Almadena Y. Chtchelkanovaemail@example.com||(703) 292-8910|
|David Cormanfirstname.lastname@example.org||(703) 292-8754|
|James C. Frenchemail@example.com||(703) 292-8930|
|Sara Kieslerfirstname.lastname@example.org||(703) 292-8643|
|Anthony Kuhemail@example.com||(703) 292-2210|
|Alexis Lewisfirstname.lastname@example.org||(703) 292-2624||E 13328|
|Bogdan Mihailaemail@example.com||(703) 292-8235|
|Rahul T. Shahfirstname.lastname@example.org||(703) 292-2709|
|Ralph Wachteremail@example.com||(703) 292-8950|
|Maria Zemankovafirstname.lastname@example.org||(703) 292-7348|
|Aidong Zhangemail@example.com||(703) 292-5311|
General Correspondence email
For general correspondence, please reply to firstname.lastname@example.org.
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 19-1), is effective for proposals submitted, or due, on or after February 25, 2019. Please be advised that, depending on the specified due date, the guidelines contained in NSF 19-1 may apply to proposals submitted in response to this funding opportunity.
The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics leading towards the further development of the interdisciplinary field of data science. The program also seeks innovative applications in domain science, including social and behavioral sciences, education, physical sciences, and engineering, where data science and the availability of big data are creating new opportunities for research and insights not previously possible.
The solicitation invites two categories of proposals:
- Foundations (BIGDATA: F): those developing or studying fundamental theories, techniques, methodologies, and technologies of broad applicability to big data problems, motivated by specific data challenges and requirements; and
- Innovative Applications (BIGDATA: IA): those engaged in translational activities that employ new big data techniques, methodologies, and technologies to address and solve problems in specific application domains. Projects in this category must be collaborative, involving researchers from domain disciplines and one or more methodological disciplines, e.g., computer science, statistics, mathematics, simulation and modeling, etc.
Proposals are expected to be well motivated by specific big data problems in one or more science and engineering research domains. All proposals are expected to clearly articulate the big data aspect(s) that motivate the research. Innovative Applications proposals must provide clear examples of the impacts of the big data techniques, technologies and methodologies on applications in one or more domains.
In FY 2018, the BIGDATA program continues the cloud option that was introduced in FY 2017, in partnership with Amazon Web Services (AWS), Google Cloud, IBM, and Microsoft Azure (see Use of Cloud Resources, at the end of Section II, Program Description).
Before preparing a proposal in response to this BIGDATA solicitation, applicants are strongly urged to review other related programs and solicitations and contact the respective NSF program officers to identify whether those solicitations are more appropriate. In particular:
- Proposals that focus exclusively on areas of biology supported by NSF’s Directorate for Biological Sciences (BIO) should be submitted to programs such as Advances in Biological Informatics that are managed by the BIO Division of Biological Infrastructure (DBI; https://www.nsf.gov/div/index.jsp?div=DBI);
- Proposals specific to geosciences that respond to the community needs and requirements expressed by the geosciences community should consider the EarthCube program for Developing a Community-Driven Data and Knowledge Environment for the Geosciences (https://www.nsf.gov/geo/earthcube/);
- For the development of robust and shared data- or software-centric cyberinfrastructure capabilities, applicants should consider the Cyberinfrastructure for Sustained Scientific Innovation - Data and Software program(CSSI; https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505505);
- For computational and data science research not specifically addressing big data issues, applicants should consider the Computational and Data Enabled Science and Engineering program (CDS&E; http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504813);
- For work that is focused more on scaling performance of software rather than data-related issues, applicants should consider the Scalable Parallelism in the Extreme program (SPX; https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505348);
- Proposals that focus on research in mathematics or statistics that is not tied to a specific big data problem should be submitted to the appropriate program within NSF’s Directorate for Mathematical & Physical Sciences (MPS) Division of Mathematical Sciences (DMS); see a list of DMS programs at https://www.nsf.gov/funding/programs.jsp?org=DMS; and
- Proposals that focus on research relevant to NSF’s Directorate for Computer and Information Science and Engineering (CISE) not tied to a specific big data problem should be submitted to the appropriate CISE program, including the core programs:
- Computer and Network Systems (CNS) Core Programs: https://www.nsf.gov/pubs/2017/nsf17570/nsf17570.htm;
- Computing and Communication Foundations (CCF) Core Programs: https://www.nsf.gov/pubs/2017/nsf17571/nsf17571.htm; and
- Information and Intelligent Systems (IIS) Core Programs: https://www.nsf.gov/pubs/2017/nsf17572/nsf17572.htm.