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.

The book is intended to be organic and we will be updating it periodically. We welcome comments on the book at any time. Just email your thoughts to: Note: we will regularly update the templates and tools available below. For the latest version always use the the standalone template rather than the one in the book itself.

The ADF Book and Summaries

ADF Tools and Templates

We will regularly update these template and tools. For the latest versions always use the documents here rather than the one in the book itself (which will be updated less regularly).

The Companion Documents

Data files for exercises