Narrative
Research at the University of Manchester (UoM) has developed new approaches, methods and algorithms to improve the statistical confidentiality practices of data stewardship organisations (DSOs), such as the UK’s Office for National Statistics. The research and its products have had significant impacts on data dissemination practice, both in the UK and internationally, and have been adopted by national statistical agencies, government departments and private companies. The primary beneficiaries of this work are DSOs, who are able to both disseminate useful data products, and protect respondent confidentiality more effectively. Secondary beneficiaries are respondents, whose confidentiality is better protected, and the research community, as without ‘gold standard’ disclosure risk analysis, data holders can be overcautious.Impact date | 2014 → 2020 |
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Category of impact | Economic impacts, Societal impacts, Legal impacts |
Impact level | Benefit |
Research Beacons, Institutes and Platforms
- Cathie Marsh Institute
Related content
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Research output
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The research use of large-scale integrated data: An ethical quagmire?
Research output: Contribution to journal › Article › peer-review
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Differential correct attribution probability for synthetic data: An exploration
Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review
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A Measure of Disclosure Risk for Tables of Counts
Research output: Contribution to journal › Article › peer-review
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A measure of disclosure risk for microdata
Research output: Contribution to journal › Article › peer-review
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Data environment analysis and the key variable mapping system
Research output: Chapter in Book/Conference proceeding › Chapter › peer-review
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Practical Privacy Controls when Re-using Medical Data for Research
Research output: Contribution to journal › Article › peer-review
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Are ‘pseudonymised’ data always personal data? Implications of the GDPR for administrative data research in the UK
Research output: Contribution to journal › Article › peer-review
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A computational algorithm for handling the special uniques problem
Research output: Contribution to journal › Article › peer-review
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Scenarios of attack: the data intruder's perspective on statistical disclosure risk
Research output: Contribution to journal › Article › peer-review
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A Study of the Impact of Synthetic Data Generation Techniques on Data Utility using the 1991 UK Samples of Anonymised Records
Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review
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Measuring Disclosure Risk and Data Utility for Flexible Table Generators
Research output: Contribution to journal › Article › peer-review
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Principles- versus Rules-Based Output Statistical Disclosure Control in Remote Access Environments
Research output: Contribution to journal › Article › peer-review
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The Anonymisation Decision Making Framework
Research output: Book/Report › Book › peer-review
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Projects
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Administrative data service
Project: Research