|Chaitanya Baru||CISE/OAD||Sylvia Spengler||CISE/IIS|
|Rahul T. Shah||CISE/CCF||Amy Apon|
|Reed S. Beaman||BIO/DBI||John C. Cherniavsky||EHR/DRL|
|Hao Ling||ENG/ECCS||Chengshan Xiao||ENG/ECCS|
|Eva Zanzerkia||GEO/EAR||Nandini Kannan||MPS/DMS|
|Bogdan Mihaila||MPS/OAD||Heng Xu||SBE/SES|
|General Correspondence email|
For general correspondence, please reply to email@example.com.
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 16-1), is effective for proposals submitted, or due, on or after January 25, 2016. Please be advised that, depending on the specified due date, the guidelines contained in NSF 16-1 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, along with innovative applications in domain science, including social and behavioral sciences, geosciences, education, biology, the physical sciences, and engineering that lead towards the further development of the interdisciplinary field of data science. The solicitation invites two types of proposals: "Foundations" (F): those developing or studying fundamental theories, techniques, methodologies, and technologies of broad applicability to big data problems; and "Innovative Applications" (IA): those developing techniques, methodologies, and technologies of key importance to a Big Data problem directly impacting at least one specific application. 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. While IA proposals may address critical big data challenges within a specific domain, a high level of innovation is expected in all proposals which should, in general, strive to provide solutions with potential for a broader impact on data science and its applications. IA proposals may focus on novel theoretical analysis and/or on experimental evaluation of techniques and methodologies within a specific domain. Proposals in all areas of sciences and engineering covered by participating directorates at NSF are welcome.
While notions of volume, velocity, and variety are commonly ascribed to big data problems, other key issues include data quality and provenance. Data-driven solutions must carefully ascribe quality and provenance to results in a manner that is helpful to the users of the results. For example, in some cases, such as in education research, data quality may aggregate to test or measurement instrument quality, where a composite of variables may be used to describe one or more constructs.
In addition to approaches such as search, query processing, and analysis, visualization techniques will also become critical across many stages of big data use--to obtain an initial assessment of data as well as through subsequent stages of scientific discovery. Research on visualization techniques and models will be necessary for serving not only the experts, who are collecting the data, but also those who are users of the data, including “cross-over” scientists who may be working with big data and analytics for the first time, and those using the data for teaching at the undergraduate and graduate levels. The BIGDATA program seeks novel approaches related to all of these areas of study.
Before preparing a proposal in response to this BIGDATA solicitation, applicants are strongly urged to consult other related programs and solicitations and review the respective NSF program officers listed in them should those solicitations be more appropriate. In particular, applicants interested in deployable cyberinfrastructure pilots that would support a broader research community should see the Campus Cyberinfrastructure - Data, Networking, and Innovation Program (CC*DNI) program (http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504748&org=ACI&from=home). Applicants should also consider the Computational and Data Enabled Science and Engineering (CDS&E) program (http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504813) for work not specifically addressing big data issues, and the Exploiting Parallelism and Scalability (XPS) program (http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504842) for work focused on scaling of software.
Frequently Asked Questions (FAQS) for NSF 12-499
1st BIGDATA Webinar (Presentation, Audio File and Transcript)
2nd BIGDATA Webinar - May 21, 2012 (Presentation, Audio File and Transcript)
REVISIONS AND UPDATES