Harnessing the Data Revolution (HDR): Institutes for Data-Intensive Research in Science and Engineering - Ideas Labs | 19 543

Opportunity Information: Apply for 19 543

The National Science Foundation (NSF) funding opportunity "Harnessing the Data Revolution (HDR): Institutes for Data-Intensive Research in Science and Engineering - Ideas Labs" is part of NSF's larger HDR Big Idea, one of the agency's 10 long-term "Big Ideas" introduced in 2016 to push U.S. leadership at the frontiers of science and engineering. Even though proposals are submitted through the Directorate for Computer and Information Science and Engineering, Office of Advanced Cyberinfrastructure (CISE/OAC), NSF makes clear that the program is inherently cross-cutting and proposals will be handled by a team of program directors spanning multiple disciplines. The central purpose is to spark new, convergence-style research directions that use modern data-driven methods to unlock discoveries across science and engineering, while also building the theory, tools, and infrastructure needed for that work to scale and last.

At its core, HDR is NSF's push to make data-intensive discovery a first-class driver of scientific and engineering progress. The initiative emphasizes a connected set of priorities: foundations of data science (the underlying theory and principles), algorithms and systems (the computational methods and platforms), data-intensive science and engineering (domain-facing research driven by complex data), data cyberinfrastructure (the pipelines, platforms, storage, and computing needed to make it all work), and education and workforce development (training and broadening participation so the community can sustain this new mode of research). NSF also highlights that HDR is not just about technical advances; it aims to establish theoretical, technical, and ethical frameworks that enable trustworthy and societally relevant data-driven decision-making.

This specific solicitation focuses on "Ideas Labs" for Data-Intensive Research in Science and Engineering (DIRSE). The Ideas Lab model is a structured, facilitated, in-person (or workshop-style) process designed to accelerate team formation and help researchers rapidly co-develop bold, interdisciplinary concepts. These Ideas Labs are not the institute awards themselves. Instead, they are positioned as one pathway within a "conceptualization phase" whose job is to generate strong, collaborative, and well-shaped prototype concepts that could later mature into full HDR Institutes. In other words, NSF is using the Ideas Labs as an organized way to pull together people who may not normally collaborate and to help them shape institute-scale ideas grounded in real science and engineering challenges, but empowered by cutting-edge data science.

NSF describes a two-phase pipeline for building HDR Institutes. Phase one, the conceptualization phase (implemented in FY 2019), provides two-year awards intended to build research communities, sharpen shared research priorities, and produce interdisciplinary prototypes that demonstrate what a future institute could do. There are two complementary conceptualization opportunities: the one in this solicitation (Ideas Labs, which assemble and shape teams through the lab process) and another FY 2019 opportunity aimed at teams that already have an integrated framework of science/engineering problems and data science solutions. Phase two, anticipated around 2021, is the convergence and co-design phase, where NSF expects to fund larger, more comprehensive HDR Institutes that integrate and scale successful prototypes and promising new concepts. Those later institutes are envisioned as an "integrated fabric" of interrelated entities that collectively accelerate discovery across multiple domains by sharing approaches, infrastructure, and methods.

The solicitation places heavy emphasis on convergence research and true interdisciplinarity. The target teams are expected to combine domain scientists and engineers who face pressing data-intensive problems with data science experts such as computer and computational scientists, mathematicians, statisticians, and information scientists. It also explicitly calls out the importance of systems and cyberinfrastructure specialists, including expertise in open-source software development, reproducibility, and transfer learning, signaling that NSF wants solutions that are usable, sustainable, and portable across domains rather than one-off analyses. The long-term intent is to develop collaborative, co-designed programs that can produce breakthroughs on critical national challenges by pairing high-impact application areas with generalizable data science advances.

Ideas Labs under this program are meant to concentrate on areas that are ready for a step-change. NSF frames this as focusing on domains at a "tipping point," where timely investment in data-intensive approaches could be transformative. They also want areas with clear needs for interdisciplinary investments in data analytics infrastructure, and areas aligned with investment priorities across NSF directorates during and beyond the HDR Big Idea timeframe. This is a signal that proposals should not only be exciting scientifically, but also well-positioned for long-term relevance, community uptake, and alignment with NSF's broader portfolio.

From a submission and eligibility process standpoint, the program uses a gated approach. U.S. researchers first submit preliminary proposals specifically to participate in an Ideas Lab, and they must do this via NSF FastLane (as stated in the solicitation). NSF may run one or multiple Ideas Labs in parallel depending on how many preliminaries come in and what mix of science/engineering domains and data science expertise is represented. Importantly, participation in an Ideas Lab is mandatory if a team wants to be eligible to submit a full conceptualization proposal through this particular solicitation. Full proposals are not open submission; they are submitted by invitation only, based on ideas developed during the Ideas Lab process. NSF also makes clear that the invited full proposals must reflect real interdisciplinary collaboration rather than loosely connected contributions.

In terms of the administrative details included in the opportunity listing, this is a discretionary grant program run by NSF (Opportunity Number 19-543), created December 13, 2018, with an original closing date of June 19, 2019. The listing notes an expected number of awards of about 15. The award ceiling is shown as 0 in the summary data, which typically indicates the ceiling is not specified in that field rather than meaning no funding; applicants usually need to rely on the full solicitation for budget guidance. The CFDA numbers span multiple NSF program areas, reinforcing the cross-directorate nature of the effort, and the eligibility line indicates "Others (see text field...)," meaning the official solicitation language governs who can apply and under what institutional conditions.

Taken together, the opportunity is best understood as NSF building the early-stage pipeline for a national network of HDR Institutes by using Ideas Labs to rapidly generate high-quality, interdisciplinary institute concepts. It is designed for researchers who have either compelling, data-intensive science and engineering problems that are ripe for data-driven breakthroughs, or deep technical expertise in data science and cyberinfrastructure that could unlock those breakthroughs when paired with the right domain challenges. The main deliverable at this stage is not a finished institute, but a well-formed, collaborative conceptualization proposal that can seed community-building, prototype development, and a credible path toward a larger, scaled HDR Institute in the later convergence phase.

• 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 - Ideas Labs" 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 Dec 13, 2018.
• Applicants must submit their applications by Jun 19, 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 15 candidate(s).
• Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).

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