Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix

Rumbold, John M. M. and Pierscionek, Barbara K. (2018) Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix. JMIR Medical Informatics, 6 (4). e47. ISSN 2291-9694

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Official URL: https://doi.org/10.2196/medinform.7096

Abstract

Background: The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research. Objective: We propose a matrix for setting different standards, which is responsive to context and public expectations. Methods: The law and ethics applicable to anonymization were reviewed in a scoping study. Social science on public attitudes and research on technical methods of anonymization were applied to formulate a matrix. Results: The matrix adjusts anonymization standards according to the sensitivity of the data and the safety of the place, people, and projects involved. Conclusions: The matrix offers a tool with context-specific standards for anonymization in data research

Item Type: Journal Article
Keywords: anonymization matrix, big data, data protection
Faculty: Faculty of Health, Education, Medicine & Social Care
Depositing User: Ian Walker
Date Deposited: 15 Feb 2021 22:12
Last Modified: 09 Sep 2021 18:56
URI: https://arro.anglia.ac.uk/id/eprint/706278

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