| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | April 30, 2024 |
| Latest Amendment Date: | April 30, 2024 |
| Award Number: | 2340034 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Sorin Draghici
sdraghic@nsf.gov (703)292-2232 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2024 |
| End Date: | September 30, 2029 (Estimated) |
| Total Intended Award Amount: | $600,000.00 |
| Total Awarded Amount to Date: | $198,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
5801 S ELLIS AVE CHICAGO IL US 60637-5418 (773)702-8669 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
5801 S ELLIS AVE CHICAGO IL US 60637-5418 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Info Integration & Informatics |
| Primary Program Source: |
01002526DB NSF RESEARCH & RELATED ACTIVIT 01002627DB NSF RESEARCH & RELATED ACTIVIT 01002728DB NSF RESEARCH & RELATED ACTIVIT 01002829DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Data is the predominant economic asset of our time, valued for its role in informed decision-making, product, and service development, and the derivation of novel scientific insights and knowledge. Sharing data yields transformative effects in multiple areas, including improving healthcare through patient data sharing, banks improving fraud detection via transaction data sharing, and epidemiologists optimizing public policy interventions by sharing data. But sharing data is hard. Four challenges get in the way: compliance, incentives, preparation, and execution. Current sharing solutions often address these challenges independently, resulting in either partial solutions or complex systems that are difficult to construct, maintain, and reuse. Consequently, the complexity and high costs hinder realizing data-sharing opportunities and their associated value. In this project data-sharing applications are treated as data markets, which paves the way for designing reusable sharing infrastructure. Data markets promise to distribute the value of data to more people and sectors than ever, across both public and private organizations. As data markets garner influence in our lives, methodologies that detect potential problems early are essential. This project introduces both novel techniques to account for the value of data and new theories, algorithms, and systems for designing and implementing data-sharing markets. While data sharing is currently mostly ad-hoc and hard-to-control, this project will enable judicious design and implementation of data markets geared towards reaping the value of data. The project will contribute to knowledge about existing and future data markets, and the research and education objectives of the project will contribute to a better understanding of techniques to gain value from data.
Despite the value of data, currently, data sharing is hard. This project addresses this issue by proposing the concept of programmable data-sharing markets, which permits market designers to implement data-sharing market applications through a programming framework and deploy those applications in a data escrow, a system with computational support for controlling dataflows. The project's technical activities include designing and implementing the data-sharing programming framework, analyzing and deriving constraints, invariants, and impossibilities of dataflow control, thus aiding in designing and implementing data markets, and evaluating the technical contributions. The dissemination activities include organizing technical workshops, including dataflow control topics on classes and open source content, and generating written articles for both technical and general audiences that elucidate the value of data and techniques to reap that value.
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.
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