The de-identification decision-making framework
The de-identification decision-making framework
We’ve developed a practical guide to de-identification for government agencies and businesses including not-for-profit and private sector organisations. Our framework can help data custodians to identify and address the key factors relevant to their particular data sharing or release situation, including privacy risk analysis and control, stakeholder engagement, and impact management.
De-identification is not an exact science and, even using the De-Identification Decision-Making Framework (DDF), it requires complex judgement calls. The DDF is intended to help data custodians make sound decisions based on best practice, but it is not a step-by-step algorithm. We recommend that users seek expert advice on the de-identification process, particularly with the more technical risk analysis and control activities.
Anonymisation, de-identification, privacy, data protection
O'Keefe, Christine M.
69b2be22-4f9e-423a-b4bd-43b97e349cec
Otarepec, Stephanie
c3d03b1f-9714-4897-ad0d-6dd2a53ec05a
Elliot, Mark
47343e95-6142-418d-a1c2-422bdb461fbf
Mackey, Elaine
4cd949a1-18ac-4b6e-bbdc-18e2be4e4f93
O'hara, Kieron
0a64a4b1-efb5-45d1-a4c2-77783f18f0c4
October 2017
O'Keefe, Christine M.
69b2be22-4f9e-423a-b4bd-43b97e349cec
Otarepec, Stephanie
c3d03b1f-9714-4897-ad0d-6dd2a53ec05a
Elliot, Mark
47343e95-6142-418d-a1c2-422bdb461fbf
Mackey, Elaine
4cd949a1-18ac-4b6e-bbdc-18e2be4e4f93
O'hara, Kieron
0a64a4b1-efb5-45d1-a4c2-77783f18f0c4
O'Keefe, Christine M., Otarepec, Stephanie, Elliot, Mark, Mackey, Elaine and O'hara, Kieron
(2017)
The de-identification decision-making framework
,
CSIRO, 156pp.
Abstract
We’ve developed a practical guide to de-identification for government agencies and businesses including not-for-profit and private sector organisations. Our framework can help data custodians to identify and address the key factors relevant to their particular data sharing or release situation, including privacy risk analysis and control, stakeholder engagement, and impact management.
De-identification is not an exact science and, even using the De-Identification Decision-Making Framework (DDF), it requires complex judgement calls. The DDF is intended to help data custodians make sound decisions based on best practice, but it is not a step-by-step algorithm. We recommend that users seek expert advice on the de-identification process, particularly with the more technical risk analysis and control activities.
This record has no associated files available for download.
More information
Published date: October 2017
Keywords:
Anonymisation, de-identification, privacy, data protection
Identifiers
Local EPrints ID: 417646
URI: http://eprints.soton.ac.uk/id/eprint/417646
PURE UUID: ec6d89cb-a11f-4f4e-bcf4-78cf2e8363fb
Catalogue record
Date deposited: 08 Feb 2018 17:30
Last modified: 16 Mar 2024 03:20
Export record
Contributors
Author:
Christine M. O'Keefe
Author:
Stephanie Otarepec
Author:
Mark Elliot
Author:
Elaine Mackey
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics