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The anonymisation decision-making framework 2nd Edition: European practitioners' guide

The anonymisation decision-making framework 2nd Edition: European practitioners' guide
The anonymisation decision-making framework 2nd Edition: European practitioners' guide
The need for well-thought-out anonymisation has never been more acute. The drive to share data has led to some ill-conceived, poorly-anonymised data publications including the Netflix, AOL, and New York taxi cases, underlining how important it is to carry out anonymisation properly and what can happen if you do not.

UKAN publishes the Anonymisation Decision Making Framework (ADF) to address a need for a practical guide to GDPR-compliant anonymisation that gives more operational advice than other publications such as the UK Information Commissioner’s Office’s (ICO) valuable Anonymisation Code of Practice. At the same time, we are concerned to be less technical and forbidding than the existing statistics and computer science literature.

The Guide is primarily intended for those who have microdata that they need to anonymise with confidence, typically in order to share it for some purpose in some form compliant with GDPR and the UK Data Protection Act (2018). Our aim is to furnish practical understanding of anonymisation so you can utilise it to advance your business or organisational goals. The Guide comes with some specific tools and templates to capture and evaluate your data situation and these we hope should help render most problems more tractable. The ADF is designed to control the risk of unintended re-identification and disclosure, and therefore its principles are universally applicable.
Anonymisation, Privacy, Confidentiality, Personal data, Data protection, Data situation, Data environment, Functional anonymisation, Data sharing, GDPR
UKAN
Elliot, Mark
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Mackey, Elaine
af6056dc-c825-4e41-8d44-94827d046f3d
O'Hara, Kieron
0a64a4b1-efb5-45d1-a4c2-77783f18f0c4
Elliot, Mark
85d9b4c3-51ff-44c1-91a9-04ee84132082
Mackey, Elaine
af6056dc-c825-4e41-8d44-94827d046f3d
O'Hara, Kieron
0a64a4b1-efb5-45d1-a4c2-77783f18f0c4

Elliot, Mark, Mackey, Elaine and O'Hara, Kieron (2020) The anonymisation decision-making framework 2nd Edition: European practitioners' guide , Manchester. UKAN, 119pp.

Record type: Book

Abstract

The need for well-thought-out anonymisation has never been more acute. The drive to share data has led to some ill-conceived, poorly-anonymised data publications including the Netflix, AOL, and New York taxi cases, underlining how important it is to carry out anonymisation properly and what can happen if you do not.

UKAN publishes the Anonymisation Decision Making Framework (ADF) to address a need for a practical guide to GDPR-compliant anonymisation that gives more operational advice than other publications such as the UK Information Commissioner’s Office’s (ICO) valuable Anonymisation Code of Practice. At the same time, we are concerned to be less technical and forbidding than the existing statistics and computer science literature.

The Guide is primarily intended for those who have microdata that they need to anonymise with confidence, typically in order to share it for some purpose in some form compliant with GDPR and the UK Data Protection Act (2018). Our aim is to furnish practical understanding of anonymisation so you can utilise it to advance your business or organisational goals. The Guide comes with some specific tools and templates to capture and evaluate your data situation and these we hope should help render most problems more tractable. The ADF is designed to control the risk of unintended re-identification and disclosure, and therefore its principles are universally applicable.

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More information

Published date: November 2020
Keywords: Anonymisation, Privacy, Confidentiality, Personal data, Data protection, Data situation, Data environment, Functional anonymisation, Data sharing, GDPR

Identifiers

Local EPrints ID: 445373
URI: http://eprints.soton.ac.uk/id/eprint/445373
PURE UUID: 042815cd-f844-4cf5-91ca-cbaa7f92e0e6
ORCID for Kieron O'Hara: ORCID iD orcid.org/0000-0002-9051-4456

Catalogue record

Date deposited: 04 Dec 2020 17:32
Last modified: 17 Mar 2024 02:52

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Contributors

Author: Mark Elliot
Author: Elaine Mackey
Author: Kieron O'Hara ORCID iD

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