Opportunity Information: Apply for 19 550
Harnessing the Data Revolution: Transdisciplinary Research in Principles of Data Science (HDR TRIPODS) Phase I is a National Science Foundation (NSF) grant opportunity designed to strengthen the theoretical foundations of data science by funding small, highly collaborative research institutes. The program sits within NSF's broader "Big Ideas" agenda introduced in 2016, which focuses on long-term, high-impact research directions meant to keep the United States at the leading edge of science and engineering. Although proposals are submitted through NSF's Directorate for Computer and Information Science and Engineering, Division of Computing and Communication Foundations (CISE/CCF), the proposals are intended to be handled by a cross-disciplinary team of NSF program directors, reflecting the program's strong emphasis on convergence research rather than work confined to a single field.
At the center of this opportunity is NSF's Harnessing the Data Revolution (HDR) Big Idea, a large, NSF-wide effort aimed at enabling new forms of data-driven discovery across science and engineering. HDR is framed as a national-scale push to make it possible to ask and answer fundamental questions using data at scales, levels of complexity, and levels of societal relevance that were previously out of reach. The solicitation highlights that HDR is not just about building tools, but about developing new knowledge and accelerating innovation through a coordinated set of investments that span foundations of data science, algorithms and systems, data-intensive science and engineering applications, data cyberinfrastructure, and education and workforce development. A key theme is that progress in data science requires deeper theoretical, technical, and ethical frameworks that can guide trustworthy and impactful data-driven decision-making.
HDR TRIPODS specifically targets the "principles" layer of data science: the core theory and conceptual foundations that can unify and advance the field. The program is explicitly structured to bring together four communities that often approach data problems with different languages and methods: electrical engineering, mathematics, statistics, and theoretical computer science. The intent is not simply to place researchers from these areas in the same project, but to require integrated collaboration in which the different disciplinary perspectives are essential to the institute's research and training agenda. For Phase I, each institute must include significant and integral participation from at least three of these four communities, emphasizing true transdisciplinary work rather than parallel efforts.
Phase I funding supports the creation and early development of small collaborative institutes that combine research with training activities, meaning teams are expected to do more than publish results; they are also expected to build capacity, develop talent, and help shape the next generation of data science researchers who can work across disciplinary boundaries. Phase I also serves as a stepping-stone to a planned Phase II: NSF anticipates a future competition (dependent on available funds) that will select a smaller number of larger institutes from among the Phase I awardees. In practice, that means Phase I institutes are meant to establish momentum, demonstrate effective collaboration, and lay out a compelling foundation that could scale.
Administratively, this is a discretionary grant program run by NSF. The funding opportunity number is 19-550, with an original closing date of May 8, 2019, and a posted creation date of February 8, 2019. The award ceiling is $1,500,000, and NSF expected to make about 20 awards under Phase I. The opportunity is categorized under science and technology and other research and development, and it references multiple NSF CFDA numbers (47.041, 47.049, 47.050, 47.070, 47.074, 47.075, 47.076, 47.079, 47.083), reflecting the cross-cutting nature of the program across NSF directorates and research areas. Eligibility is listed broadly as "Others" with further clarification indicated in the solicitation's eligibility text, which is typical for NSF programs that may include universities and other research organizations depending on the specific solicitation language.
Overall, HDR TRIPODS Phase I is best understood as a foundational investment in the underlying theory of data science, deliberately engineered to force deep collaboration across disciplines that traditionally drive core advances in signal processing and electrical engineering, mathematical structures, statistical inference, and computational complexity and algorithms. The goal is to create institute-style teams that can develop unifying principles and rigorous frameworks for data science, while also training researchers who can carry that integrated perspective into future scientific, engineering, and societal challenges.Apply for 19 550
- The National Science Foundation in the science and technology and other research and development sector is offering a public funding opportunity titled "Harnessing the Data Revolution: Transdisciplinary Research in Principles of Data Science Phase I" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 47.041, 47.049, 47.050, 47.070, 47.074, 47.075, 47.076, 47.079, 47.083.
- This funding opportunity was created on Feb 08, 2019.
- Applicants must submit their applications by May 08, 2019. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $1,500,000.00 in funding.
- The number of recipients for this funding is limited to 20 candidate(s).
- Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).
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HDR TRIPODS Phase I (NSF 19-550) - Frequently Asked Questions
What is the HDR TRIPODS Phase I grant opportunity?
Harnessing the Data Revolution: Transdisciplinary Research in Principles of Data Science (HDR TRIPODS) Phase I is a National Science Foundation (NSF) funding opportunity that supports small, highly collaborative research institutes focused on strengthening the theoretical foundations (the "principles" layer) of data science.
Which NSF initiative does this program belong to?
HDR TRIPODS Phase I sits within NSF's "Big Ideas" agenda introduced in 2016. More specifically, it aligns with NSF's Harnessing the Data Revolution (HDR) Big Idea, an NSF-wide effort aimed at enabling new forms of data-driven discovery across science and engineering.
What is the main goal of HDR TRIPODS Phase I?
The main goal is to advance the core theory and conceptual foundations of data science in a way that can unify the field and support trustworthy, impactful data-driven decision-making. The program is designed to create institute-style teams that develop rigorous frameworks, not just applications or tools.
What does "TRIPODS" focus on within data science?
TRIPODS focuses on the principles of data science: underlying theory, foundational concepts, and unifying frameworks that support broad progress across data-driven fields. It is explicitly positioned as foundational rather than confined to a single application area.
What is meant by "transdisciplinary" in this program?
In this program, transdisciplinary means research and training must be deeply integrated across multiple disciplines, not divided into separate workstreams. The solicitation emphasizes convergence research where different disciplinary perspectives are essential to the institute's agenda.
Which research communities are expected to be integrated in an institute?
HDR TRIPODS is structured to bring together four communities that often address data problems with different methods and vocabulary: electrical engineering, mathematics, statistics, and theoretical computer science.
How many of the four communities must be included in a Phase I institute?
For Phase I, each institute must include significant and integral participation from at least three of the four communities (electrical engineering, mathematics, statistics, and theoretical computer science).
Is it enough to include researchers from multiple fields, or is deeper integration expected?
Deeper integration is expected. The intent is not simply to list multiple disciplines on a proposal, but to require integrated collaboration where the different perspectives are essential to the research and training program.
What kind of project structure does Phase I support?
Phase I supports the creation and early development of small, collaborative institutes. These institutes are expected to combine research with training activities to build capacity and develop talent in transdisciplinary data science foundations.
Does the program include training or workforce development expectations?
Yes. Phase I institutes are expected to do more than publish research results. They are also expected to include training activities that help shape the next generation of data science researchers who can operate across disciplinary boundaries.
How does HDR TRIPODS relate to the broader HDR effort?
HDR is described as a coordinated, NSF-wide set of investments spanning foundations of data science, algorithms and systems, data-intensive science and engineering applications, data cyberinfrastructure, and education and workforce development. TRIPODS is specifically targeted at the foundational principles layer within that broader HDR framework.
Is this opportunity focused on building tools and infrastructure?
HDR overall is not framed as only building tools. It emphasizes developing new knowledge and accelerating innovation through coordinated investments. TRIPODS, in particular, is centered on theoretical foundations and unifying principles rather than tool-building alone.
What NSF directorate and division handle proposal submission?
Proposals are submitted through NSF's Directorate for Computer and Information Science and Engineering (CISE), Division of Computing and Communication Foundations (CCF).
Are proposals reviewed only within CISE/CCF?
The solicitation indicates that proposals are intended to be handled by a cross-disciplinary team of NSF program directors, reflecting the program's emphasis on convergence research rather than work confined to a single field.
What is the funding opportunity number for HDR TRIPODS Phase I?
The funding opportunity number is 19-550.
What is the award ceiling for Phase I?
The award ceiling is $1,500,000.
How many Phase I awards did NSF expect to make?
NSF expected to make about 20 awards under Phase I.
What are the key dates provided for this opportunity?
The posted creation date is February 8, 2019, and the original closing date is May 8, 2019.
What type of grant program is this?
It is a discretionary grant program administered by NSF.
What category is this funding opportunity listed under?
It is categorized under "science and technology and other research and development."
What is the relationship between Phase I and a potential Phase II?
Phase I is described as a stepping-stone to a planned Phase II. NSF anticipated a future competition (dependent on available funds) that would select a smaller number of larger institutes from among the Phase I awardees.
Does Phase I guarantee selection for Phase II?
No. Phase II is described as a future competition that depends on available funds and would select only some institutes from the Phase I awardees.
What should Phase I institutes demonstrate to be positioned for Phase II?
Phase I institutes are intended to establish momentum, demonstrate effective collaboration, and lay out a compelling foundation that could scale into a larger institute if selected in a later Phase II competition.
How is eligibility described in the information provided?
Eligibility is listed broadly as "Others," with additional clarification indicated in the solicitation's eligibility text. This is typical of NSF opportunities that may allow universities and other research organizations depending on the specific solicitation language.
What CFDA numbers are associated with this opportunity?
The opportunity references multiple NSF CFDA numbers: 47.041, 47.049, 47.050, 47.070, 47.074, 47.075, 47.076, 47.079, and 47.083, reflecting the cross-cutting nature of the program.
Why are multiple CFDA numbers referenced?
The program is described as cross-cutting across NSF directorates and research areas. The presence of multiple CFDA numbers is consistent with that cross-disciplinary scope.
What does NSF mean by "Harnessing the Data Revolution" in this context?
HDR is framed as a national-scale effort to make it possible to ask and answer fundamental questions using data at scales, levels of complexity, and levels of societal relevance that were previously out of reach.
Does the solicitation emphasize ethics or trustworthiness in data science?
Yes. The description notes a theme that progress in data science requires deeper theoretical, technical, and ethical frameworks that can guide trustworthy and impactful data-driven decision-making.
What is the expected outcome of investing in "principles" of data science?
The expected outcome is the development of unifying principles and rigorous frameworks that advance data science as a field and support future scientific, engineering, and societal challenges, along with training researchers who can work across disciplinary boundaries.
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