Hashed Linkages for Administrative Datasets: A Technical How-To Guide
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| Title: | Hashed Linkages for Administrative Datasets: A Technical How-To Guide |
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| Language: | English |
| Authors: | Samantha Fu, Charles Davis, Jesse Rothstein, Aparna Ramesh, Evan White, California Policy Lab (CPL) |
| Source: | Grantee Submission. 2022. |
| Peer Reviewed: | Y |
| Page Count: | 17 |
| Publication Date: | 2022 |
| Sponsoring Agency: | Institute of Education Sciences (ED) National Science Foundation (NSF) |
| Contract Number: | R305A220451 2024283 |
| Document Type: | Guides - General |
| Descriptors: | Data Use, Research Methodology, Researchers, Privacy, Information Security, Public Agencies, Technology, Data Collection, Coding |
| Abstract: | Linking data together can be a powerful way for governments and researchers alike to tackle vexing public policy research problems. However, for researchers, finding ways to link data directly between two departments can often be more challenging than even obtaining the data in the first place. Even when a researcher develops the necessary relationships and trust with multiple government agencies, traditional linking requires each agency to share identified data, sometimes resulting in privacy and security concerns, and also requires the agencies to work together in ways that are not always easy to accomplish. We discuss these issues at greater length in another report that covers the logistical, statutory, and technological considerations for implementing privacy-preserving linkages. This how-to guide focuses on the linkage process itself, and aims to serve as a technical handbook for parties interested in linking datasets that have been de-identified using cryptographic hashing methods. |
| Abstractor: | As Provided |
| IES Funded: | Yes |
| Entry Date: | 2024 |
| Accession Number: | ED653103 |
| Database: | ERIC |
| Abstract: | Linking data together can be a powerful way for governments and researchers alike to tackle vexing public policy research problems. However, for researchers, finding ways to link data directly between two departments can often be more challenging than even obtaining the data in the first place. Even when a researcher develops the necessary relationships and trust with multiple government agencies, traditional linking requires each agency to share identified data, sometimes resulting in privacy and security concerns, and also requires the agencies to work together in ways that are not always easy to accomplish. We discuss these issues at greater length in another report that covers the logistical, statutory, and technological considerations for implementing privacy-preserving linkages. This how-to guide focuses on the linkage process itself, and aims to serve as a technical handbook for parties interested in linking datasets that have been de-identified using cryptographic hashing methods. |
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