ABSTRACT
In this article, we examine the concept of non-personal data from a law and computer science perspective. The delineation between personal data and non-personal data is of paramount importance to determine the GDPR’s scope of application. This exercise is, however, fraught with difficulty, also when it comes to de-personalized data – that is to say data that once was personal data but has been manipulated with the goal of turning it into anonymous data.
This article charts that the legal definition of anonymous data is subject to uncertainty. Indeed, the definitions adopted in the GDPR, by the Article 29 Working Party and by national supervisory authorities diverge significantly. Whereas the GDPR admits that there can be a remaining risk of identification even in relation to anonymous data, others have insisted that no such risk is acceptable. After a review of the technical underpinnings of anonymization that is subsequently applied to two concrete case studies involving personal data used on blockchains, we conclude that there always remains a residual risk when anonymization is used. The concluding section links this conclusion to the more general notion of risk in the GDPR.
Michèle Finck and Frank Pallas, They who must not be identified – distinguishing personal from non-personal data under the GDPR, International Data Privacy Law, https://doi.org/10.1093/idpl/ipz026. Published: 10 March 2020.
First posted 2020-03-20 09:08:32
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