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  • 26 - Towards Adaptive Governance in Big Data Health Research

  • from Section IIA - Private and Public Dimensions of Health Research Regulation
  • Edited by Graeme Laurie, University of Edinburgh, Edward Dove, University of Edinburgh, Agomoni Ganguli-Mitra, University of Edinburgh, Catriona McMillan, University of Edinburgh, Emily Postan, University of Edinburgh, Nayha Sethi, University of Edinburgh, Annie Sorbie, University of Edinburgh
  • Book:
    The Cambridge Handbook of Health Research Regulation
    Published online:
    09 June 2021
    Print publication:
    24 June 2021, pp 257-265
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  • Summary

    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.