| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
|
| Initial Amendment Date: | April 28, 2021 |
| Latest Amendment Date: | April 28, 2021 |
| Award Number: | 2129895 |
| Award Instrument: | Standard Grant |
| Program Manager: |
James Joshi
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | May 1, 2021 |
| End Date: | April 30, 2022 (Estimated) |
| Total Intended Award Amount: | $31,713.00 |
| Total Awarded Amount to Date: | $31,713.00 |
| Funds Obligated to Date: |
|
| History of Investigator: |
|
| Recipient Sponsored Research Office: |
2550 NORTHWESTERN AVE # 1100 WEST LAFAYETTE IN US 47906-1332 (765)494-1055 |
| Sponsor Congressional District: |
|
| Primary Place of Performance: |
305 N University St West Lafayette IN US 47907-2107 |
| Primary Place of
Performance Congressional District: |
|
| Unique Entity Identifier (UEI): |
|
| Parent UEI: |
|
| NSF Program(s): |
Information Technology Researc, Secure &Trustworthy Cyberspace |
| Primary Program Source: |
|
| Program Reference Code(s): |
|
| Program Element Code(s): |
|
| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Recent events have shown the value of better data sharing; the rapidity of change in COVID-19 and the difficulty of coordinating response is a clear example. At the same time, public concern over privacy is increasing, making it more difficult to collect reliable data. Improved use of government data by a wide range of users has potential to improve research as well as day-to-day operations at a variety of levels, from local to national and global. Government data can also foster innovation, providing opportunities for small companies based on large-scale data analysis that are increasingly reserved for large organizations capable of gathering their own data (often in ways that raise privacy concerns). We are running a 2-day workshop to identify challenges and explore mechanisms (technical, legal, and procedural) to enable greater use of privacy-sensitive data held by government agencies.
Privacy technology has experienced great advances over the past decade. Breakthroughs such as fully homomorphic encryption, differential privacy, and advances in secure multiparty computation have great promise to enable broader public use of data, while maintaining individual privacy. While there have been some successes, there are many applications where there is a significant gap between what technology offers, data needs of users, and policies and procedures to ensure privacy. This includes best practices as well as research and policy challenges that limit effective use of data. This workshop explores these concerns, highlighting new research challenges based on actual user needs for government data. This covers research in underlying technologies that address real-world challenges, as well as research in policy to enable use of technology in ways that provide appropriate levels of protection for privacy-sensitive data. The outcome will be a report identifying unmet needs of data users, issues limiting broader use of government data, and technologies and policies that show promise of bridging these gaps. This will serve as a roadmap for research investment to address these challenges.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Note:
When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external
site maintained by the publisher. Some full text articles may not yet be available without a
charge during the embargo (administrative interval).
Some links on this page may take you to non-federal websites. Their policies may differ from
this site.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Government agencies collect and manage a wide range of ever-growing datasets. While such data has the potential to support research and evidence-based policy making, there are concerns that the dissemination of such data could infringe upon the privacy of the individuals (or organizations) from whom such data was collected. To appraise the current state of data sharing, as well as learn about opportunities for stimulating such sharing at a faster pace, a virtual workshop was held on May 21st and 26th, 2021, sponsored by the National Science Foundation, National Institute of Standards and Technologies, and White House Office of Science and Technology Policy, where a multinational collection of researchers and practitioners were brought together to discuss their experiences and learn about recently developed technologies for managing privacy while sharing data.
While the workshop did not arrive at a formal set of recommendations, the authors of the report captured certain key actionable items from the discussions. They are summarized as follows:
- Build a community by organizing a series of conferences and workshops where researchers and practitioners can participate, discuss the problems, and demonstrate how to deploy solutions.
- Applied and foundational research and development.
- Develop common repositories with a variety of data sharing use cases to stimulate and advance research, e.g. the Differential Privacy Synthetic Data Challenge.
- Engage with stakeholders by educating people from a variety of disciplines so that they understand the privacy issues, the data-sharing issues, and the data driven technologies they use.
- Communicate the risks, benefits, challenges, limitations, and constraints of the technologies to help build a community around particular use cases or classes of use cases to develop means to address those issues.
Details on the workshop and the discussions can be found in the workshop report, published through arXiv.org.
Last Modified: 08/01/2022
Modified by: Christopher W Clifton
Please report errors in award information by writing to: awardsearch@nsf.gov.
