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Towards Adaptive Governance in Big Data Health Research

Authors :
Vayena, Effy
Blasimme, Alessandro
Laurie, Graeme
Ganguli-Mitra, Agomoni
McMillan, Catriona
Postan, Emily
Sethi, Nayha
Sorbie, Annie
Source :
Cambridge Law Handbooks, The Cambridge Handbook of Health Research Regulation
Publication Year :
2021
Publisher :
Cambridge University Press, 2021.

Abstract

In recent times, biomedical research has begun to tap into larger-than-ever collections of different data types. As a consequence, the notion of health data – data that are of relevance for health-related research or for clinical purposes – is expanding to include a variety of non-clinical data, as well as data provided by research participants themselves through commercially available products such as smartphones and fitness bands. To date, most scholarship and policy on these issues has focused on privacy and data protection. Less attention has been paid to addressing other aspects of the wicked challenges posed by big data health research and even less work has been geared towards the development of novel governance frameworks. In this chapter, we make the case for adaptive and principle-based governance of big data research. We outline six principles of adaptive governance for big data research and propose key factors for their implementation into effective governance structures and processes.<br />Cambridge Law Handbooks<br />The Cambridge Handbook of Health Research Regulation<br />ISBN:978-1-108-47597-6<br />ISBN:978-1-108-62002-4

Details

Language :
English
ISBN :
978-1-108-47597-6
978-1-108-62002-4
ISBNs :
9781108475976 and 9781108620024
Database :
OpenAIRE
Journal :
Cambridge Law Handbooks, The Cambridge Handbook of Health Research Regulation
Accession number :
edsair.doi.dedup.....4f9d058682d901cb33f1fe85f82a6a1f