Collaborative Research: Workshop to Develop a Roadmap for Greater Public Use of Privacy-Sensitive Government Data
Collaborative Research: Workshop to Develop a Roadmap for Greater Public Use of Privacy-Sensitive Government Data
批准号:
2129909
负责人:
Bradley Malin
金额:
$3.28万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-05-01 至 2022-04-30
中文摘要
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英文摘要
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, federated and split learning, 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 explore 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 and business models to enable use of technology in ways that provide appropriate levels of sharing and 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.
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RAPID: Collaborative: A Privacy Risk Assessment Framework for Person-Level Data Sharing During Pandemics
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批准号:2029651
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项目类别:Standard Grant
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资助金额:$10.0万
-
财政年份:2020
-
负责人:Bradley Malin
-
依托单位:
SCH: INT: Collaborative Research: High-throughput Phenotyping on Electronic Health Records using Multi-Tensor Factorization
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批准号:1418504
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项目类别:Standard Grant
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资助金额:$69.3万
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财政年份:2014
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负责人:Bradley Malin
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依托单位:
CT: Collaborative Research: Experience-Based Access Management (EBAM) for Hospital Information Technology
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批准号:0964063
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项目类别:Standard Grant
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资助金额:$39.5万
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财政年份:2010
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负责人:Bradley Malin
-
依托单位:
国内基金
海外基金
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