Harnessing the Data Revolution: Transdisciplinary Research in Principles of Data Science Phase I
The summary for the Harnessing the Data Revolution: Transdisciplinary Research in Principles of Data Science Phase I grant is detailed below.
This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants.
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Harnessing the Data Revolution: Transdisciplinary Research in Principles of Data Science Phase I: In 2016, the National Science Foundation (NSF) unveiled a set of “Big Ideas,” 10 bold, long-term research and process ideas that identify areas for future investment at the frontiers of science and engineering (seehttps://www.nsf.gov/news/special_reports/big_ideas/index.jsp). The Big Ideas represent unique opportunities to position our Nation at the cutting edge of global science and engineering leadership by bringing together diverse disciplinary perspectives to support convergence research. As such, when responding to this solicitation, even though proposals must be submitted to the Directorate for Computer & Information Science & Engineering/Division of Computing and Communication Foundations (CISE/CCF), once received, the proposals will be managed by a cross-disciplinary team of NSF Program Directors. NSF'sHarnessing the Data Revolution (HDR) Big Ideais a national-scale activity to enable new modes of data-driven discovery that will allow fundamental questions to be asked and answered at the frontiers of science and engineering. Through this NSF-wide activity, HDR will generate new knowledge and understanding, and accelerate discovery and innovation. The HDR vision is realized through an interrelated set of efforts in: Foundations of data science; Algorithms and systems for data science; Data-intensive science and engineering; Data cyberinfrastructure; and Education and workforce development. Each of these efforts is designed to amplify the intrinsically multidisciplinary nature of the emerging field of data science. The HDR Big Idea will establish theoretical, technical, and ethical frameworks that will be applied to tackle data-intensive problems in science and engineering, contributing to data-driven decision-making that impacts society. Harnessing the Data Revolution: Transdisciplinary Research In Principles Of Data Science (HDR TRIPODS) aims to bring together the electrical engineering,mathematics, statistics, and theoretical computer science communities to develop the theoretical foundations of data science through integrated research and training activities. Phase I, described in this solicitation, will support the development of small collaborative Institutes. Phase II (to be described in an anticipated future solicitation, subject to availability of funds) will support a smaller number of larger Institutes, selected from the Phase I Institutes via a second competitive proposal process. All HDR TRIPODS Institutes must involve significant and integral participation by researchers representing at least three of the four aforementioned communities. Please note that the ordering of the four communities is alphabetical and is not meant to emphasize any one discipline over another.
Federal Grant Title: | Harnessing the Data Revolution: Transdisciplinary Research in Principles of Data Science Phase I |
Federal Agency Name: | National Science Foundation (NSF) |
Grant Categories: | Science and Technology |
Type of Opportunity: | Discretionary |
Funding Opportunity Number: | 19-550 |
Type of Funding: | Grant |
CFDA Numbers: | 47.041, 47.049, 47.050, 47.070, 47.074, 47.075, 47.076, 47.079, 47.083 |
CFDA Descriptions: | Information not provided |
Current Application Deadline: | May 8th, 2019 |
Original Application Deadline: | May 8th, 2019 |
Posted Date: | February 8th, 2019 |
Creation Date: | February 8th, 2019 |
Archive Date: | June 7th, 2019 |
Total Program Funding: | $22,000,000 |
Maximum Federal Grant Award: | $1,500,000 |
Minimum Federal Grant Award: | $1,200,000 |
Expected Number of Awards: | 20 |
Cost Sharing or Matching: | No |
Last Updated: | February 8th, 2019 |
- Applicants Eligible for this Grant
- Others (see text field entitled "Additional Information on Eligibility" for clarification.)
- Additional Information on Eligibility
- *Who May Submit Proposals: Proposals may only be submitted by the following: - Institutions of Higher Education (IHEs) - Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in, the US, acting on behalf of their faculty members. Special Instructions for International Branch Campuses of US IHEs: If the proposal includes funding to be provided to an international branch campus of a US institution of higher education (including through use of subawards and consultant arrangements), the proposer must explain the benefit(s) to the project of performance at the international branch campus, and justify why the project activities cannot be performed at the US campus. Any institution that received an award under the previous TRIPODS Phase I solicitation<a href="https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf16615">NSF 16-615</a> (see <a href="https://www.nsf.gov/news/news_summ.jsp?cntn_id=242888">https://www.nsf.gov/news/news_summ.jsp?cntn_id=242888</a>) is not eligible to submit a single-institution proposal. These institutions may submit only as either (a) lead or non-lead collaborative partners on a multi-institution collaborative proposal, or (b) sub-awardees. *Who May Serve as PI: No PI, co-PI, or Senior Personnel for an award under the previous TRIPODS Phase I solicitation <a href="https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf16615">NSF 16-615</a> may serve as a PI, co-PI, or Senior Personnel. PI teams must collectively possess appropriate expertise in at least three of the four aforementioneddisciplines - electrical engineering,mathematics, statistics,or theoretical computer science. It is anticipated that in most cases this requirement will be met by assembling teams of three or more individuals. Teams may be composed of members at multiple institutions or a single institution.
- Link to Full Grant Announcement
- NSF Publication 19-550
- Grant Announcement Contact
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