m0nster

Absolutely. They're doing a great job at UKAN!

True. For this reason, even anonymous data can usually not be shared as open data. You have to control the environment in which the data is used to control what is "reasonably likely" (see also comment by La1n above).

Also with synthetic data, there is an inherent trade-off between privacy risks and the usefulness of the data produced.

However, this trade-off can be of a different nature, resulting in advantages for synthetization, for example when protecting high-dimensional data.

In my experience, this is a question of interpretation (see e.g. Recital 26 and the question of what is "reasonably likely"). You can ask ten different experts, and you will get ten different opinions.

Unfortunately, many aspects of the GDPR are interpreted very heterogeneously, both in individual countries and by different supervisory authorities within the countries themselves.

For this reason, it is essential that more specific guidelines and certifications are developed for the use of different technologies, including anonymization.

True, Amnesia can also be run locally!

ARX (see other comment in this thread) also supports data anonymization for privacy-preserving machine learning.

If you're interested in tools such as Amnesia, you might also want to take a look at ARX, which supports much more anonymization methods, including Differential Privacy:

https://arx.deidentifier.org

https://github.com/arx-deidentifier/arx

Disclosure: I'm the main author of ARX.

ARX [1, 2] is an open source software that (among other features) supports most of the methods mentioned in this thread. Full disclosure: I'm one of the developers of ARX.

[1] Website: http://arx.deidentifier.org

[2] Source: https://github.com/arx-deidentifier/arx

While data de-identification surely has its limits, it is useful in many contexts.

If someone is interested in tools for data de-identification, ARX [1, 2] is an open source software that (among other features) supports exactly the set of methods used in this study.

Full disclosure: I'm one of the developers of ARX.

[1] Website: http://arx.deidentifier.org

[2] Source: https://github.com/arx-deidentifier/arx