The Privacy-Preserving Data Sharing in Practice (PDaSP) program is a grant from NSF's TIP and CISE directorates, in partnership with Intel, VMware, the U.S. Department of Transportation, and NIST, that funds translational research bridging the gap between privacy-enhancing technologies and real-world deployment.

The program supports projects advancing practical adoption of PETs across domains including transportation, healthcare, and financial services. Funded work must demonstrate measurable progress toward scalable, interoperable privacy solutions. Awards range from ,000 to ,500,000.

Eligible applicants include universities, research institutions, industry partners, and federal agencies working collaboratively on applied privacy challenges.

NSF 24-585: Privacy-Preserving Data Sharing in Practice (PDaSP) | NSF - U.S. National Science Foundation Archived funding opportunity This solicitation is archived. NSF's implementation of the revised 2 CFR NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website .

These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

Important information for proposers All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements.

Submitting a proposal prior to a specified deadline does not negate this requirement.

Updates to NSF Research Security Policies On July 10, 2025, NSF issued an Important Notice providing updates to the agency's research security policies, including a research security training requirement, Malign Foreign Talent Recruitment Program annual certification requirement, prohibition on Confucius institutes and an updated FFDR reporting and submission timeline.

NSF 24-585: Privacy-Preserving Data Sharing in Practice (PDaSP) Download the solicitation (PDF, 1mb) U.S. National Science Foundation Directorate for Technology, Innovation and Partnerships Innovation and Technology Ecosystems Directorate for Computer and Information Science and Engineering Division of Computer and Network Systems U.S. Department of Transportation, Federal Highway Administration National Institute of Standards and Technology Full Proposal Deadline(s) (due by 5 p.

m. submitting organization’s local time): Important Information And Revision Notes Any proposal submitted in response to this solicitation should be submitted in accordance with the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted.

The NSF PAPPG is regularly revised and it is the responsibility of the proposer to ensure that the proposal meets the requirements specified in this solicitation and the applicable version of the PAPPG. Submitting a proposal prior to a specified deadline does not negate this requirement.

Summary Of Program Requirements Privacy-Preserving Data Sharing in Practice (PDaSP) In today’s hyperconnected and device-rich world, increasing computational power and the explosive growth of data present us with tremendous opportunities to enable data-driven, evidence-based decision-making capabilities to accelerate scientific discovery and innovation.

However, to be able to responsibly leverage the insights from and power of data, such as for training powerful artificial intelligence (AI) models, it is important to have practically deployable and scalable technologies that allow data sharing in a privacy-preserving manner.

While there has been significant research progress in privacy-related areas, privacy-preserving data sharing technologies remain at various levels of maturity in terms of practical deployment.

The goals of the PDaSP program are aligned with the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (AI EO), which emphasizes the role for privacy-enhancing technologies (PETs) in a responsible and safe AI future.

The EO directs NSF to, “where feasible and appropriate, prioritize research — including efforts to translate research discoveries into practical applications — that encourage the adoption of leading-edge PETs solutions for agencies’ use.

” It also tasks NSF with “developing and helping to ensure the availability of testing environments, such as testbeds, to support the development of safe, secure, and trustworthy AI technologies, as well as to support the design, development, and deployment of associated PETs.

” In addition to meeting these directives in the AI EO, the PDaSP program strives to address key recommendations made in the National Strategy to Advance Privacy Preserving Data Sharing and Analytics (PPDSA).

In particular, the program strives to advance the strategy’s priority to “Accelerate Transition to Practice , ” which includes efforts to “promote applied and translational research and systems development,” develop “tool repositories, measurement methods, benchmarking, and testbeds,” and “improve usability and inclusiveness of PPDSA solutions.

” The PDaSP program welcomes proposals from qualified researchers and multidisciplinary teams in the following tracks with expected funding ranges for proposals as shown below.

Track 1: Advancing key technologies to enable practical PPDSA solutions: Track 1 projects are expected to be budgeted in the $500K - $1M range for up to 2 years Track 2: Integrated and comprehensive solutions for trustworthy data sharing in application settings: Track 2 projects are expected to be budgeted in the $1M - $1.

5M range for up to 3 years Track 3: Usable tools, and testbeds for trustworthy sharing of private or otherwise confidential data. Track 3 projects are expected to be budgeted in the $500K - $1.

5M range for up to 3 years The PDaSP program represents the collaborative efforts of the NSF Technology, Innovation and Partnerships (TIP) and Computer and Information Science and Engineering (CISE) directorates, Intel Corporation and VMware LLC as industry partners, and the U.S. Department of Transportation Federal Highway Administration (FHWA) and the U.S. Department of Commerce National Institute of Standards and Technology (NIST) as federal agency partners.

This solicitation includes partners from both industry and the federal government, and welcomes new partners from both public and private sectors ahead of the proposal submission deadline. PIs will be given the option of having their proposals considered for new partner co-funding based on matching areas of interest.

Broadening Participation In STEM: NSF recognizes the unique lived experiences of individuals from communities that are underrepresented and/or underserved in science, technology, engineering, and mathematics (STEM) and the barriers to inclusion and access to STEM education and careers.

NSF highly encourages the leadership, partnership, and contributions in all NSF opportunities of individuals who are members of such communities supported by NSF. This includes leading and designing STEM research and education proposals for funding; serving as peer reviewers, advisory committee members, and/or committee of visitor members; and serving as NSF leadership, program, and/or administrative staff.

NSF also highly encourages demographically diverse institutions of higher education (IHEs) to lead, partner, and contribute to NSF opportunities on behalf of their research and education communities. NSF expects that all individuals, including those who are members of groups that are underrepresented and/or underserved in STEM, are treated equitably and inclusively in the Foundation's proposal and award process.

NSF encourages IHEs that enroll, educate, graduate, and employ individuals who are members of groups underrepresented and/or underserved in STEM education programs and careers to lead, partner, and contribute to NSF opportunities, including leading and designing STEM research and education proposals for funding.

Such IHEs include, but may not be limited to, community colleges and two-year institutions, mission-based institutions such as Historically Black Colleges and Universities (HBCUs), Tribal Colleges and Universities (TCUs), women's colleges, and institutions that primarily serve persons with disabilities, as well as institutions defined by enrollment such as Predominantly Undergraduate Institutions (PUIs), Minority-Serving Institutions (MSIs), and Hispanic Serving Institutions (HSIs).

"Broadening participation in STEM" is the comprehensive phrase used by NSF to refer to the Foundation's goal of increasing the representation and diversity of individuals, organizations, and geographic regions that contribute to STEM teaching, research, and innovation. To broaden participation in STEM, it is necessary to address issues of equity, inclusion, and access in STEM education, training, and careers.

Whereas all NSF programs might support broadening participation components, some programs primarily focus on supporting broadening participation research and projects. Examples can be found on the NSF Broadening Participation in STEM website. Cognizant Program Officer(s): Please note that the following information is current at the time of publishing.

See program website for any updates to the points of contact.

Anna Squicciarini, CISE/CNS, Questions regarding this program can be emailed to, Applicable Catalog of Federal Domestic Assistance (CFDA) Number(s): --- Highway Research and Development Program --- Computer and Information Science and Engineering --- NSF Technology, Innovation and Partnerships Anticipated Type of Award: Standard Grant or Continuing Grant Estimated Number of Awards: 26 NSF anticipates making up to 12 Track 1 awards; up to 7 Track 2 awards; and up to 7 Track 3 awards, depending on the quality of submissions and the availability of funds.

Anticipated Funding Amount: $23,000,000 $23M, subject to availability of funds 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 U.S., acting on behalf of their faculty members.

Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities.

U.S.-based small businesses, as defined by SBA’s small business size regulations 13 CFR Part 121 , with strong capabilities in scientific or engineering research or education and a passion for innovation. NSF SBIR/STTR recipients are especially encouraged to submit, though NSF welcomes proposals from all interested and qualifying small business concerns, including those funded by other agency SBIR/STTR programs.

The PI, co-PIs, or any other senior/key personnel must hold an appointment at an organization that is eligible to submit as described under "Who May Submit Proposals." Researchers with primary appointments at overseas branch campuses of U.S. institutions of higher education are not eligible.

Researchers from foreign academic institutions who contribute essential expertise to the project may participate as senior/key personnel or collaborators but may not receive NSF support. Individuals affiliated with a partner involved in this solicitation, notably those who are currently employed by, consulting for, or on an active agreement to provide services for the partner, may NOT participate in proposals to the program.

Limit on Number of Proposals per Organization: There are no restrictions or limits. Limit on Number of Proposals per PI or co-PI: 2 An individual can participate as PI, co-PI, or senior/key personnel in no more than TWO PDaSP proposals submitted in response to this solicitation.

If an individual exceeds this limit, the first TWO proposals received within the deadline will be accepted based on the earliest date and time of proposal submission.  No exceptions will be made. Proposal Preparation and Submission Instructions A.

Proposal Preparation Instructions Letters of Intent: Not required Preliminary Proposal Submission: Not required Full Proposals submitted via Research. gov: NSF Proposal and Award Policies and Procedures Guide (PAPPG) guidelines apply. The complete text of the PAPPG is available electronically on the NSF website at: https://www.

nsf. gov/publications/pub_summ. jsp?

ods_key=pappg . Full Proposals submitted via Grants. gov: NSF Grants.

gov Application Guide: A Guide for the Preparation and Submission of NSF Applications via Grants. gov guidelines apply (Note: The NSF Grants. gov Application Guide is available on the Grants.

gov website and on the NSF website at: https://www. nsf. gov/publications/pub_summ.

jsp? ods_key=grantsgovguide ). Cost Sharing Requirements: Inclusion of voluntary committed cost sharing is prohibited.

Indirect Cost (F&A) Limitations: Other Budgetary Limitations: Other budgetary limitations apply. Please see the full text of this solicitation for further information. Full Proposal Deadline(s) (due by 5 p.

m. submitting organization’s local time) Proposal Review Information Criteria National Science Board approved criteria. Additional merit review criteria apply.

Please see the full text of this solicitation for further information. Award Administration Information Additional award conditions apply. Please see the full text of this solicitation for further information.

Additional reporting requirements apply. Please see the full text of this solicitation for further information Data plays a central role in our increasingly digital world, where technological innovations allow for the generation, collection, sharing, analysis and seamless flow of large amounts of privacy-sensitive information.

These advances, including the explosive growth and rapid adoption of AI, provide unprecedented opportunities to derive value from data to enable better-informed, data-driven decision-making capabilities, accelerate scientific innovation, and enable societal progress. These advances, however, also raise significant concerns related to privacy and possible harm to individuals, enterprises, and society at large.

To unleash a future in which the power of data is leveraged for the benefit of all, it is important to develop practical and easily deployable privacy-preserving data sharing and analytics (PPDSA) technologies.

The Privacy-preserving Data Sharing in Practice (PDaSP) program seeks to foster innovative, use-inspired and translational research to mature and scale existing models, methodologies, or constructs in order to accelerate the development and deployment of practical privacy-preserving data sharing solutions.

Through this program, NSF, in partnership with industry funding partners and other federal agencies, aims to accelerate efforts to develop practical and deployable solutions that enable data sharing and analytics in a privacy-preserving manner.

The PDaSP program combines the expertise of NSF’s Technology, Innovation and Partnerships (TIP) and Computer and Information Science and Engineering (CISE) directorates in developing and managing use-inspired and translational PPDSA research.

NSF has a long history of supporting privacy R&D through programs such as Secure and Trustworthy Cyberspace (SaTC), and PDaSP aims to provide a path to transition innovative ideas into real-world deployment. The TIP directorate is charged with accelerating use-inspired and translational research and development (R&D) to advance U.S. competitiveness in key technology focus areas .

The explosive growth of data enabled by technological advances, and the proliferation of data protection and privacy laws and regulations in various states throughout the U.S. as well as around the globe over the last few years show the urgency of strengthening data privacy and minimizing privacy harms to people and communities.

They also add significant challenges to developing practical technological and socio-technical PPDSA solutions that are easy-to-use, and compliant with regulations within the interconnected multi-jurisdictional environments where privacy-sensitive data is shared and used.

While there are promising initial real-world deployments of various PPDSA techniques such as differential privacy, secure multiparty computation, and trusted execution environments (TEEs), to name a few, broad adoption of such technologies has been slow due to challenges related to inadequate understanding of privacy risks and harms, limited access to technical expertise, trust and transparency among participants with regard to data collection and use, uncertainty about legal compliance, financial costs, and technical maturity or deployment readiness of solutions.

This solicitation seeks to foster innovative use-inspired and translational research to mature and scale existing models, methodologies, or constructs at the intersection of privacy goals and socio-economic or policy challenges.

Of particular interest is innovation and translation of technologies that empowers data subjects, owners/curators, and other stakeholders to control how privacy-sensitive data is shared and used in order to maximize the utility of data while minimizing potential harms.

It is expected that proposers will consider opportunities and gaps that extend across the computing stack, across development and operations, and across the span of modern deployment scenarios including technologies that may be operated by untrusted parties (e.g., private cloud, public cloud, edge computing).

A central element of this solicitation is to apply, mature, and scale the use of both hardware and software foundations for sharing data while preserving privacy and appropriate use of that data.

In that spirit, this solicitation seeks proposals related to maturing PPDSA technologies to increase the utility of data, accompanied by clear plans for relevant demonstration of the viability of the proposed solutions for one or more identified use-cases and/or application contexts. Proposers in academia, non-profit organizations and firms qualifying as small businesses, are welcome.

Proposals will be accepted into three tracks as described below. Track 1: Advancing key technologies to enable practical PPDSA solutions This track is focused on maturing an individual PPDSA technology, or a combination of technologies, driven by a specific use-case or application area.

Illustrative examples are maturing homomorphic encryption to support privacy-preserving analytics over shared data; or attribute-based encryption to enforce privacy-aware access control and data use policies to support a chosen application (e.g., in healthcare, finance, or transportation) in an edge-cloud environment.

Similarly, examples of innovative combinations of specific PPDSA technologies may include combining a cryptographic technique (e.g., multi-party computation) with a statistical disclosure limitation technique (e.g., differential privacy) to enable privacy-preserving collaborative machine learning over distributed datasets for real-world applications (e.g., detection of financial fraud; public health prediction).

It is expected that proposing teams will include relevant expertise representing the use-case or application domain selected, and/or collaboration with a potential adopter of the developed solution. The solutions developed should consider clear and relevant threat models, well-understood risks and harms, and practical privacy-utility tradeoffs with verifiable privacy guarantees.

Track 2: Integrated and comprehensive solutions for trustworthy data sharing in application settings This track is focused on advancing integrated and comprehensive privacy management to enable trustworthy data sharing through the development of holistic system architectures that support end-to-end privacy protection and establish verifiable chain of trust considering the deployment context (e.g., meeting requirements for regulatory compliance, and use by diverse user base).

In particular, the integrated solutions are expected to empower data subjects and/or owners to be able to control and manage their privacy-sensitive data with respect to access to, sharing of, and use of their data. The proposed solutions should show promise for enhancing, extending, and creating new opportunities for using data.

As such, they should consider ecosystem challenges such as cross-organizational and cross-jurisdictional issues, economic incentives, regulatory environments, open-source ecosystems, and open standards. Proposals in this track should emphasize customization or maturing of integrative PPDSA solutions that tackle challenges related to specific use-cases and application contexts.

These application contexts could include various technological (e.g., Internet of Things-Edge-Cloud continuum) and regulatory/legal contexts (e.g., GDPR, CCPA, HIPAA); incentives for sharing; or one or more of the emerging application domains where integrative PPDSA solutions are or will be critical, such as healthcare (e.g., personalized medicine, genomics), transportation (e.g., autonomous driving, urban planning, smart city infrastructure, and traffic management), disaster management and public health (e.g., pandemic predication), immersive technologies, and digital assets or finance (e.g., anti-money laundering, or combating terrorist financing).

The projects funded under this track are expected to demonstrate the viability of solutions in specific application settings, ensuring usability, and verifiable and acceptable privacy-tradeoff guarantees. One technology that demonstrates significant promise for addressing end-to-end protection and the trade-offs between usability and verifiable privacy is confidential computing.

Confidential computing is a hardware-based security paradigm that has shown (potentially, in combination with other PPDSA technologies) significant promise as an element of effective comprehensive privacy management. Industry partners Intel and VMware have special interest in the use of confidential computing or equivalent to create a verifiable chain of trust related to privacy protection.

Track 3: Usable tools and testbeds for trustworthy sharing of private or otherwise confidential data This track emphasizes and recognizes the urgent need to develop tools and testbeds to support and accelerate adoption of PPDSA technologies.

There exists a high barrier to adoption for PPDSA technologies, including more mature approaches, due to a lack of effective and easy-to-use tools that help data owners and other stakeholders in the data ecosystem who need to make privacy protection decisions.

Effective and easy-to-use tools that support privacy auditing , help assess privacy disclosure risks, improve trust and transparency, facilitate decision-making, and assist in managing privacy parameters, are critical components needed to help us extract value from of data.

Innovative proposals that focus on developing practical tools that enhance capabilities of users (e.g., research community, citizen scientists, data subjects, and data administrators) to foster and democratize PPDSA solutions are encouraged. Proposals should include an application area or use-case that will serve as the demonstration for the effectiveness of the proposed tools and make the tool publicly available.

This track also emphasizes testbeds that support assessment, comparative analysis, vulnerability or threat analysis, privacy risk assessments, and privacy-utility trade-off analysis. Curated datasets relevant to different use-cases can be essential parts of testbeds. The track also welcomes work related to creating sandboxes to enable experiments on PPDSA technologies and to help address policy challenges in controlled environments.

The PDaSP program is catalyzed by partnerships with industry and other federal agencies. Current partners for this solicitation include: (1) Intel Corporation; (2) VMware LLC; (3) Federal Highway Administration (FHWA), U.S. Department of Transportation; and (4) National Institute of Standards and Technology (NIST), U.S. Department of Commerce.

These four partners’ specific areas of interest and nature of collaboration for the PDaSP program are described below. NSF may enter into partnerships with other agencies, foundations, and organizations interested in co-funding projects submitted to this solicitation up to one month prior to the proposal submission deadline. Potential partners from industry and other federal agencies may reach out to TIP-PDaSP-Ask@nsf.

gov for more details. Intel Corporation: Intel will provide funding and limited access to relevant hardware resources for PDaSP awards. Intel Corporation has a shared belief in the importance of making progress in use-inspired and translational research related to PPDSA.

As part of this partnership, the following has been agreed: Intel’s funding contribution will primarily support projects in Track 2. In particular, Intel would like to support comprehensive privacy-preserving data sharing solutions that use confidential computing.

Upon request, Intel will provide limited access to hardware resources to projects mainly in Track 2, but also in other tracks where the use of confidential computing is justified. The key resource made available will be Intel-hosted virtual machines that support modern confidential computing technologies such as Intel Software Guard Extensions (SGX) or Intel Trust Domain Extensions (TDX).

Proposers are required to include a request in the proposal for such resource access and justify the need. Intel will make decisions based on the merit of such requests. VMware LLC: VMware is interested in providing funding mainly to Track 2 and Track 3 awards, but will also consider proposals that focus on confidential computing and other privacy techniques and technologies that are relevant in the context of AI applications.

Federal Highway Administration (FHWA): FHWA partnership includes co-funding of projects relevant to FHWA. In particular, FHWA will consider co-funding of projects in Track 1 or Track 2 that are aligned with the following interest area(s). Naturalistic Traffic Studies in Privacy Preserving manner .

The highway transportation research community increasingly is using naturalistic data to understand traffic behavior, which includes both the study of drivers and the study of other road users such as pedestrians or bicyclists.

Data collection may involve use of on and in vehicle sensors, roadside sensors, and mobile devices that obtain different modes of data including inertial, radar, LIDAR, visible image, thermal, audio, and GPS location. Such data can provide information that would disclose or allow inference of the identity of people and information about their behavior.

FHWA is interested in supporting methods/approaches that would allow secure and privacy-preserving sharing of such data to improve the safety, mobility, and convenience of travel that balances access for research purposes and public benefits. Such proposed methods should include integration of technical approaches and administrative controls.

FHWA would expect proposals to include investigators with experience in transportation research, data science, and privacy coming from different disciplines including civil engineering, systems engineering, computer or information science, applied psychology, organizational psychology, or other relevant social sciences. An example of a naturalistic study data is located at https://insight. shrp2nds.

us/home . The proposals aligned with this area is expected to be in either Track 1 or Track 2. Information on current Highway Safety Information System data is located at https://highways.

dot. gov/research/safety/hsis . For proposals that are directed to FHWA and are selected for co-funding, FHWA requires a minimum 20 percent funding match for the FHWA portion of funding .

The funding match may be in kind based on the value of equipment, materials, data, or labor. This requirement will not be included as a condition of the NSF award. Additional information will be provided by FHWA, and the cost match will be reported to and managed by the FHWA.

National Institute of Standards and Technologies (NIST): NIST is building a PETs testbed initially focused on a privacy-preserving federated learning (PPFL) model environment. The project aims to provide open-source software to run locally and a cloud environment that simulates a central server connected to a set of data silos.

The initial deployment of the environment focuses on genomic data and providing input and output privacy protections.

Participants in this funding opportunity are welcome to use NIST software or to potentially collaborate with NIST – this may include enhancing the PPML environment design and broadening its use; adding modular components to support its expansion; contributing benchmark datasets (create and share) for different use-cases (especially beyond genomics); and conducting privacy, security, efficiency, and accuracy research on existing resources.

PIs interested in exploring NIST collaboration can reach out to the NIST team at privacyeng@nist. gov . NSF may enter into partnerships with other interested agencies, foundations, and organizations interested in co-funding projects submitted to this solicitation up to one month prior to the proposal submission deadline.

PIs on proposals that meet the general eligibility requirements of one or more of these new partners may be contacted by the cognizant NSF Program Officer following submission of their proposals and be given the option of having their proposals considered jointly by NSF and the new partner(s).

Any industry partner that joins after the solicitation has been released is expected to: Make co-funding contributions at a level that at least matches those from the current industry partners mentioned in this solicitation, which can be discussed when the potential partnership is explored; and Agree to the “public dedication” approach to intellectual property, publishing and licensing discussed in the "Award Conditions" section of this solicitation.

PIs have the option to accept or decline to be considered for co-funding from the new partners and the sharing of proposals with them in the pre-award phase. Any partner who joins after the solicitation has been released will be included in the ”Updates and Announcements” section of the PDaSP program page . PIs are encouraged to check this webpage frequently for news of additional partner involvement.

PIs may consider utilizing NSF-supported research infrastructure (such as the Platforms for Advanced Wireless Research , FABRIC , Chameleon , CloudLab ) when formulating their research plans and submitting proposals. Descriptions of the capabilities of each system and their availability can be found at their websites: https://advancedwireless. org/ , https://fabric-testbed.

net/ , https://www. chameleoncloud. org/ , https://cloudlab.

us/ . Anticipated Type of Award: Standard Grant or Continuing Grant Estimated Number of Awards: NSF anticipates making up to 12 Track 1 awards; up to 7 Track 2 awards; and up to 7 Track 3 awards, depending on the quality of submissions and the availability of funds.

Anticipated Funding Amount: $23M, subject to availability of funds Estimated program budget, number of awards and average award size/duration are subject to the availability of funds. IV.

Eligibility Information 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 U.S., acting on behalf of their faculty members.

Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities.

U.S.-based small businesses, as defined by SBA’s small business size regulations 13 CFR Part 121 , with strong capabilities in scientific or engineering research or education and a passion for innovation. NSF SBIR/STTR recipients are especially encouraged to submit, though NSF welcomes proposals from all interested and qualifying small business concerns, including those funded by other agency SBIR/STTR programs.

The PI, co-PIs, or any other senior/key personnel must hold an appointment at an organization that is eligible to submit as described under "Who May Submit Proposals." Researchers with primary appointments at overseas branch campuses of U.S. institutions of higher education are not eligible.

Researchers from foreign academic institutions who contribute essential expertise to the project may participate as senior/key personnel or collaborators but may not receive NSF support. Individuals affiliated with a partner involved in this solicitation, notably those who are currently employed by, consulting for, or on an active agreement to provide services for the partner, may NOT participate in proposals to the program.

Limit on Number of Proposals per Organization: There are no restrictions or limits. Limit on Number of Proposals per PI or co-PI: 2 An individual can participate as PI, co-PI, or senior/key personnel in no more than TWO PDaSP proposals submitted in response to this solicitation.

If an individual exceeds this limit, the first TWO proposals received within the deadline will be accepted based on the earliest date and time of proposal submission.  No exceptions will be made. V.

Proposal Preparation And Submission Instructions A. Proposal Preparation Instructions Full Proposal Preparation Instructions : Proposers may opt to submit proposals in response to this Program Solicitation via Research. gov or Grants.

gov. Full Proposals submitted via Research. gov: Proposals submitted in response to this program solicitation should be prepared and submitted in accordance with the general guidelines contained in the NSF Proposal and Award Policies and Procedures Guide (PAPPG). The complete text of the PAPPG is available electronically on the NSF website at: https://www.

nsf. gov/publications/pub_summ. jsp?

ods_key=pappg . Paper copies of the PAPPG may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-8134 or by e-mail from nsfpubs@nsf. gov .

The Prepare New Proposal setup will prompt you for the program solicitation number. Full proposals submitted via Grants. gov: Proposals submitted in response to this program solicitation via Grants.

gov should be prepared and submitted in accordance with the NSF Grants. gov Application Guide: A Guide for the Preparation and Submission of NSF Applications via Grants. gov .

The complete text of the NSF Grants. gov Application Guide is available on the Grants. gov website and on the NSF website at: ( https://www.

nsf. gov/publications/pub_summ. jsp?

ods_key=grantsgovguide ). To obtain copies of the Application Guide and Application Forms Package, click on the Apply tab on the Grants. gov site, then click on the Apply Step 1: Download a Grant Application Package and Application Instructions link and enter the funding opportunity number, (the program solicitation number without the NSF prefix) and press the Download Package button.

Paper copies of the Grants. gov Application Guide also may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-8134 or by e-mail from nsfpubs@nsf. gov .

In determining which method to utilize in the electronic preparation and submission of the proposal, please note the following: Collaborative Proposals. All collaborative proposals submitted as separate submissions from multiple organizations must be submitted via Research. gov. PAPPG Chapter II.

E. 3 provides additional information on collaborative