On the awareness of the dynamism pertaining to data and its processing, this paper investigates the problem of having two mutually exclusive definitions of personal and non-personal data in the legal framework in force. The taxonomic analysis of key terms and their context of application highlights the risk to crystalize the whole system upon which the digital single market is built, suffocating its future development. With this premise, the paper discusses the extent of the two main data processing tools provided by the GDPR, questioning the ex-ante categorization of data and its outcome, supporting stakeholders in overcoming this issue.
Podda, E., Palmirani, M. (2021). Inferring the Meaning of Non-personal, Anonymized, and Anonymous Data. Heidelberg : Springer, Cham [10.1007/978-3-030-89811-3_19].
Inferring the Meaning of Non-personal, Anonymized, and Anonymous Data
Podda, Emanuela
;Palmirani, Monica
2021
Abstract
On the awareness of the dynamism pertaining to data and its processing, this paper investigates the problem of having two mutually exclusive definitions of personal and non-personal data in the legal framework in force. The taxonomic analysis of key terms and their context of application highlights the risk to crystalize the whole system upon which the digital single market is built, suffocating its future development. With this premise, the paper discusses the extent of the two main data processing tools provided by the GDPR, questioning the ex-ante categorization of data and its outcome, supporting stakeholders in overcoming this issue.| File | Dimensione | Formato | |
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