Privacy-Preserving Data Sharing in Practice (PDaSP)

Privacy-Preserving Data Sharing in Practice (PDaSP) is sponsored by National Science Foundation (NSF) and industry partners (Intel Corporation, VMware LLC), and federal agency partners (U.S. Department of Transportation Federal Highway Administration (FHWA), U.S. Department of Commerce National Institute of Standards and Technology (NIST)).

This program supports research and development of practically deployable and scalable technologies for privacy-preserving data sharing. It aims to accelerate scientific discovery and innovation while responsibly leveraging insights from data, particularly for training AI models.

Privacy-Preserving Data Sharing in Practice (PDaSP) | NSF - U.S. National Science Foundation Privacy-Preserving Data Sharing in Practice (PDaSP) Archived funding opportunity This document has been archived.

Important information for proposers and award recipients All proposals must be submitted in accordance with the requirements specified in the funding opportunity and in the Proposal & Award Policies & Procedures Guide (PAPPG) and its supplements . All NSF grants and cooperative agreements are subject to the applicable set of NSF award terms and conditions . NSF has updated its research security policies for NSF funded projects.

Supports the advancement of privacy-enhancing technologies and their use to solve real-world problems. Aligned with a recent executive order on AI, PDaSP will enhance the ability to privately share and analyze data for a range of use cases and applications.

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.

Updates and announcements NSF invests over $10M to advance U.S. leadership in privacy-enhancing technologies and accelerate their use for real-world solutions PDaSP resources available Questions regarding this program can be emailed to July 23, 2024 - Information Session: Privacy Preserving Data Sharing in… July 12, 2024 - Information Session: Privacy Preserving Data Sharing in… Awards made through this program Browse projects funded by this program Map of recent awards made through this program Directorate for Technology, Innovation and Partnerships (TIP) Division of Innovation and Technology Ecosystems (TIP/ITE) Directorate for Computer and Information Science and Engineering (CISE) Division of Computer and Network Systems (CISE/CNS)