Raphael Gellert

Radboud University, Nijmegen

Postbus 9108

Nijmegen, 6500 HK

Netherlands

  • Radboud University, Nijmegen

SCHOLARLY PAPERS

4

DOWNLOADS

720

SSRN CITATIONS

3

CROSSREF CITATIONS

0

Scholarly Papers (4)

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1.

Towards a Holistic Regulatory Approach for the European Data Economy: Why the Illusive Notion of Non-Personal Data is Counterproductive to Data Innovation

TILEC Discussion Paper No. 2018-029
Number of pages: 18 Posted: 28 Sep 2018
Inge Graef, Raphael Gellert and Martin Husovec
Tilburg Law School, Radboud University, Nijmegen and London School of Economics - Law Department
Downloads 331 (105,143)
Citation 3

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innovation, intellectual property, data protection law, data portability, Digital Single Market

2.

Feedback to the Commission's Proposal on a Framework for the Free Flow of Non-Personal Data

Number of pages: 6 Posted: 30 Jan 2018
Inge Graef, Raphael Gellert, Nadezhda Purtova and Martin Husovec
Tilburg Law School, Radboud University, Nijmegen, Tilburg University - Tilburg Institute for Law, Technology, and Society (TILT) and London School of Economics - Law Department
Downloads 274 (128,718)
Citation 1

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concept of personal data; identifiability; free flow of data; data economy; data portability

3.

Data Protection and Notions of Information: A Conceptual Exploration

Number of pages: 25 Posted: 09 Dec 2018 Last Revised: 04 Sep 2019
Raphael Gellert
Radboud University, Nijmegen
Downloads 98 (307,277)

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data protection, information theory, machine learning, algorithmic regulation

4.

The Concept of ‘Information’: An Invisible Problem in the GDPR

Dara Hallinan and Raphaël Gellert, "The Concept of ‘Information’: An Invisible Problem in the GDPR" (2020) 17:2 SCRIPTed 269 https://script-ed.org/?p=3885 DOI: 10.2966/scrip.170220.269
Number of pages: 51 Posted: 27 Oct 2020
Dara Hallinan and Raphael Gellert
FIZ Karlsruhe – Leibniz Institute for Information Infrastructure and Radboud University, Nijmegen
Downloads 17 (613,888)

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Data Protection, GDPR, Information Theory, Genetic Data, Artificial Intelligence, Machine Learning