The DOI matches its Crossref record.
Identifiability and the applicability of data protection to big data
Abstract
Big data is the present and the future. It holds the potential to make corporations create big revenues, to let scientists solve vital issues and to help governments make informed policy decisions. Yet the massive collection and use of personal data also raises a host of issues, particularly for individuals’ privacy and data protection rights.1 In Europe, data protection regulation is widely regarded as the answer to these issues. Through regulating data flows and providing individuals control over their personal data, some of big data’s possible undesired effects may be prevented. Yet upon closer scrutiny, it is uncertain whether European data protection legislation suffices to address these negative consequences. The practices in big data projects and the threshold for data to fall within the material scope of EU data protection legislation raise doubts about data protection’s applicability to big data. ... This article discusses the scope of application of EU data protection law to show the potentials and limitations of data protection law to come to terms with big data. It starts by clarifying what big data is, as big data is more than just the collection of large data sets. In this article, big data is explained as a three-phase process. This helps to illuminate what is new about big data and structures big data’s legal analysis. On the basis of this three-phase process view, the legal part of the article sets out when EU data protection law applies and analyses which el…
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“The GDPR also covers processing before the actual release of the model, i.e., for training purposes [23].”
From Generative AI in EU law: Liability, privacy, intellectual property, and cybersecurity (2024) · cites this paper as [23]
Citations
Cited by
Generative AI in EU law: Liability, privacy, intellectual property, and cybersecurity
Novelli, C., Casolari, F., Hacker, P., Spedicato, G., & Floridi, L. (2024) · Computer Law & Security Review · doi:10.1016/j.clsr.2024.106066 · Cited by 124
Generative Ai in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity
Novelli, C., Casolari, F., Hacker, P., Spedicato, G., & Floridi, L. (2024) · doi:10.2139/ssrn.4821952 · Cited by 57
Metadata
- Authors
- Oostveen, M.
- Venue
- International Data Privacy Law
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-09-07
- Volume
- 6
- Issue
- 4
- Pages
- 299-309
- ISSN
- 2044-3994
- 2044-4001
- Cited by
- 12
- References
- 0
- Language
- en
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- CoChat. (2026). Citation check: Identifiability and the applicability of data protection to big data. https://app.cochat.ai/papers/10.1093/idpl/ipw012
- The paper
- Oostveen, M. (2016). Identifiability and the applicability of data protection to big data. International Data Privacy Law. https://doi.org/10.1093/idpl/ipw012
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.