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Title: Data protection in the age of Big Data : legal challenges and responses in the context of online behavioural advertising
Author: Chen, Jiahong
ISNI:       0000 0004 7654 2770
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2018
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This thesis addresses the question of how data protection law should respond to the challenges arising from the ever-increasing prevalence of big data. The investigation is conducted with the case study of online behavioural advertising (OBA) and within the EU data protection legal framework, especially the General Data Protection Regulation (GDPR). It is argued that data protection law should respond to the big data challenges by leveraging the regulatory options that are either already in place in the current legal regime or potentially available to policymakers. With the highly complex, powerful and opaque OBA network, in both technical and economic terms, the use of big data may pose fundamental threats to certain individualistic, collective or societal values. Despite a limited number of economic benefits such as free access to online services and the growth of the digital market, the latent risks of OBA call for an effective regulatory regime on big data. While the EU's GDPR represents the latest and most comprehensive legal framework regulating the use of personal data, it has still fallen short on certain important aspects. The regulatory model characterised by individualised consent and the necessity test remains insufficient in fully protecting data subjects as autonomous persons, consumers and citizens in the context of OBA. There is thus a pressing need for policymakers to review their regulatory toolbox in the light of the potential threats. On the one hand, it is necessary to reconsider the possibilities to blacklist or whitelist certain data uses with mechanisms that are either in place in the legal framework or can be introduced additionally. On the other hand, it is also necessary to realise the full range of policy options that can be adopted to assist individuals in making informed decisions in the age of big data.
Supervisor: Rauhofer, Judith ; Williams, Robin Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: data protection law ; big data ; online behavioural advertising ; General Data Protection Regulation ; GDPR ; regulatory model ; individualised consent ; legal framework ; policy