ABR is proud to present volume 11, issue 3 of September 2019, consisting of the Ethics Framework for Big Data in Health and Research, developed by the SHAPES Working Group on Big Data Ethics, and papers that illustrate the practical application of this framework in six specific contexts.
In 2018–2019, Singapore’s National Medical Research Council funded the Science, Health and Policy-relevant Ethics in Singapore (SHAPES) Initiative at the NUS Centre for Biomedical Ethics (CBmE), to establish an international Working Group on Big Data Ethics.
The topic of big data is of course not new. The potential arising from the use of big data in health and research is widely recognised, as are the challenges posed in this fast-paced dynamic field. However, despite a wealth of literature, there is a lack of practical guidance for decision-making in the form of a framework that considers the ethical issues that arise from the use of big data in a variety of health and research contexts. The framework is intended for a wide range of professional audiences including biomedical researchers, clinician-researchers, data scientists, policymakers, those involved in the governance of big data activities in health and research, and data controllers. Beyond these professionals, the framework may also be useful to lay people with an interest in big data, patients and research participants.
The framework, like all decision-making frameworks, does not present solutions to ethical issues raised. Rather, it provides insight into how underlying values ought to occupy a central position in the decision-making process and how values can be balanced to reach justifiable decisions. The framework differs from other decision-making tools as it articulates specific values and provides extensive analyses demonstrating how values and relevant issues are to be considered and thought through. This is the strength of this Framework, as it can function as a practical tool for those working in numerous fields employing big data. The variety and number of cases and examples considered in the various papers provide a model for users and offer ample opportunity to draw on the analyses provided when making decisions.
All articles in this special issue are ‘Open Access’, i.e. freely accessible, even without subscription to ABR.
Delivering a Practical Framework for Ethical Decision-making involving Big Data in Health and Research
Editorial by Graeme T. Laurie and E Shyong Tai, on behalf of the SHAPES Working Group
doi: 10.1007/s41649-019-00098-y
An Ethics Framework for Big Data in Health and Research
Vicki Xafis, G. Owen Schaefer, Markus K. Labude, Iain Brassington, Angela Ballantyne, Hannah Yeefen Lim, Wendy Lipworth, Tamra Lysaght, Cameron Stewart, Shirley Sun, Graeme T. Laurie and E Shyong Tai
doi: 10.1007/s41649-019-00099-x
Openness in Big Data and Data Repositories:
The Application of an Ethics Framework for Big Data in Health and Research
Vicki Xafis and Markus K. Labude
doi: 10.1007/s41649-019-00097-z
Precision Medicine and Big Data:
The Application of an Ethics Framework for Big Data in Health and Research
G. Owen Schaefer, E Shyong Tai and Shirley Sun
doi: 10.1007/s41649-019-00094-2
Real-world Data to Generate Evidence about Healthcare Interventions:
The Application of an Ethics Framework for Big Data in Health and Research
Wendy Lipworth
doi: 10.1007/s41649-019-00095-1
AI-assisted Decision-making in Healthcare:
The Application of an Ethics Framework for Big Data in Health and Research
Tamra Lysaght, Hannah Yeefen Lim, Vicki Xafis and Kee Yuan Ngiam
doi: 10.1007/s41649-019-00096-0
Big Data and Public-Private Partnerships in Healthcare and Research:
The Application of an Ethics Framework for Big Data in Health and Research
Angela Ballantyne and Cameron Stewart
doi: 10.1007/s41649-019-00100-7
Cross-sectoral Big Data:
The Application of an Ethics Framework for Big Data in Health and Research
Graeme T. Laurie
doi: 10.1007/s41649-019-00093-3
Asian Bioethics Review 