Contextual anonymization for secondary use of big data in biomedical research: proposal for an anonymization matrix

Rumbold, J ORCID: https://orcid.org/0000-0002-3308-711X and Pierscionek, B ORCID: https://orcid.org/0000-0002-8661-6353, 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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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
Publication Title:	JMIR Medical Informatics
Creators:	Rumbold, J. and Pierscionek, B.
Publisher:	JMIR Publications
Date:	22 November 2018
Volume:	6
Number:	4
ISSN:	2291-9694
Identifiers:	Number Type 10.2196/medinform.7096 DOI
Divisions:	Schools > School of Science and Technology
Record created by:	Linda Sullivan
Date Added:	29 Oct 2018 13:49
Last Modified:	04 Dec 2018 11:06
URI:	https://irep.ntu.ac.uk/id/eprint/34782

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