Harnessing the Data Revolution (HDR): Institutes for Data-Intensive Research in Science and Engineering - Frameworks (I-DIRSE-FW) | 19 549

Opportunity Information: Apply for 19 549

The NSF opportunity "Harnessing the Data Revolution (HDR): Institutes for Data-Intensive Research in Science and Engineering - Frameworks (I-DIRSE-FW)" is part of NSF's broader HDR Big Idea, one of the agency's 10 long-term "Big Ideas" launched to push the frontiers of science and engineering through convergence research. The basic premise is that modern research is being reshaped by the explosive growth of data, and that new discoveries will increasingly depend on better ways to manage, understand, and use large, complex, and diverse datasets. While proposals for this program were submitted through NSF's CISE Office of Advanced Cyberinfrastructure (OAC), the program was designed to be managed by a cross-disciplinary team of NSF program directors because it intentionally spans many research communities and NSF directorates.

HDR, as NSF describes it, aims to enable new modes of data-driven discovery so researchers can ask and answer fundamental questions that were previously out of reach. The HDR vision is organized around several tightly linked thrusts: foundations of data science (theory, math, statistics, and principles), algorithms and systems for data science (computational methods and platforms), data-intensive science and engineering (domain-driven applications where data changes what is possible), data cyberinfrastructure (shared computing, storage, software, and services), and education and workforce development (training people to do this work at scale and responsibly). A central theme is that progress does not come from any one piece alone; it comes from combining domain science with data science, computation, and infrastructure, while also building ethical and technical frameworks that make data-driven work trustworthy and impactful for society.

This specific solicitation funded "Frameworks for Data-Intensive Research in Science and Engineering (DIRSE)" as one route into the HDR Institutes activity. Rather than immediately funding fully mature, large-scale institutes, NSF set up a staged approach. The DIRSE Frameworks awards were part of the conceptualization phase, meant to help teams define what an HDR Institute could be in a particular scientific or engineering area, build the right partnerships, and test early prototypes. NSF framed the long-term HDR Institutes vision as an "integrated fabric" of interrelated institutes that collectively accelerate discovery across many fields by sharing approaches, infrastructure concepts, and data science methods, rather than operating as isolated centers.

The conceptualization phase in FY 2019 had two complementary pathways. One pathway used an Ideas Lab model to help individuals self-organize around compelling data-intensive problems and/or technical capabilities and quickly form collaborative teams. The second pathway is this solicitation: it supported more directly proposed, team-based "frameworks" that connect a set of science and engineering challenge problems with the data science solutions and infrastructure concepts needed to tackle them. In practical terms, the program was looking for teams that could articulate a coherent research and collaboration blueprint, identify where the bottlenecks are (data barriers, methodological gaps, infrastructure shortfalls, workforce limitations), and demonstrate how coordinated work across disciplines could unlock a step-change in capability.

The awards produced by this solicitation were intended to be short, two-year efforts focused on community-building and planning plus early technical proof-of-concept work. NSF emphasized outcomes like defining shared research priorities, establishing collaborative structures that cut across departments and institutions, and developing interdisciplinary prototype solutions that make the institute concept credible and actionable. The idea was that the strongest concepts and prototypes from this phase, along with new ideas, could feed into a later "convergence and co-design" phase that NSF anticipated around 2021. That later phase would support larger, more comprehensive HDR Institutes that integrate and scale what worked, bringing multiple domain communities together with computer and computational scientists, mathematicians, statisticians, and information scientists around common data science approaches.

The solicitation's core objective was to foster genuinely convergent, data-driven research in science and engineering. NSF wanted Frameworks teams to pilot new collaboration modalities that go beyond traditional disciplinary boundaries and "institutional walls." That includes building durable links between domain researchers and data scientists and engineers, and also thinking deliberately about integrating research infrastructure (tools, platforms, data pipelines, standards, compute) with education infrastructure (training programs, student pipelines, professional development, curricula, and community practices). The emphasis was not only on producing research results, but also on creating a workable structure for sustained, scalable interdisciplinary collaboration.

NSF also gave clear guidance on what kinds of topic areas were a good fit. Frameworks were expected to target science and engineering domains that are at a "tipping point," meaning the field is ready for a timely data-intensive investment that could have outsized, transformative effects. They also needed to be areas where interdisciplinary investments in data analytics infrastructure would materially change what the community can do, and where there is alignment with investment priorities across relevant NSF directorates during and beyond the HDR Big Idea timeframe. In other words, NSF was not looking for isolated data projects; it was looking for places where the combination of urgent scientific questions, available or emerging data streams, and the right data science advances could reshape an entire research area.

In terms of concrete deliverables, NSF expected Frameworks to (1) identify frontier challenge problems in science and engineering, (2) map the associated data challenges and data-science barriers that currently limit progress (such as data heterogeneity, scale, quality, access, privacy, governance, reproducibility, or algorithmic limitations), and (3) propose and begin testing strategies that can produce breakthroughs by bringing together diverse researchers under a shared framework. This includes considering the theoretical and ethical dimensions of data use, not just the computational ones, since HDR explicitly highlights the need for technical and ethical frameworks that support trustworthy, societally relevant data-driven decision-making.

Administrative details from the opportunity listing include that it was a discretionary NSF grant program (Funding Opportunity Number 19-549) with an original closing date of May 7, 2019. It anticipated roughly 10 awards. The opportunity was associated with multiple NSF CFDA numbers (47.041, 47.049, 47.050, 47.070, 47.074, 47.075, 47.076, 47.079, 47.083), reflecting its cross-cutting scope. Eligibility was described broadly as "Others (see text...)," signaling that applicants needed to consult the full solicitation for specific eligibility rules and any constraints tied to institution types or partnership structures.

Taken as a whole, I-DIRSE-FW was essentially NSF's way of funding the "blueprint stage" for future HDR Institutes: short, focused awards to organize interdisciplinary communities, pinpoint high-leverage data bottlenecks in key science and engineering areas, build early prototypes, and lay the groundwork for larger, institute-scale efforts designed to change how data-intensive research is done across the US research ecosystem.

• 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 (HDR): Institutes for Data-Intensive Research in Science and Engineering - Frameworks (I-DIRSE-FW)" 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 07, 2019.
• Applicants must submit their applications by May 07, 2019. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• The number of recipients for this funding is limited to 10 candidate(s).
• Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).

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