Abstract
Current discussions of the ethical aspects of big data are shaped by concerns regarding the social consequences of both the widespread adoption of machine learning and the ways in which biases in data can be replicated and perpetuated. We instead focus here on the ethical issues arising from the use of big data in international neuroscience collaborations. Neuroscience innovation relies upon neuroinformatics, large-scale data collection and analysis enabled by novel and emergent technologies. Each step of this work involves aspects of ethics, ranging from concerns for adherence to informed consent or animal protection principles and issues of data re-use at the stage of data collection, to data protection and privacy during data processing and analysis, and issues of attribution and intellectual property at the data-sharing and publication stages. Significant dilemmas and challenges with far-reaching implications are also inherent, including reconciling the ethical imperative for openness and validation with data protection compliance and considering future innovation trajectories or the potential for misuse of research results. Furthermore, these issues are subject to local interpretations within different ethical cultures applying diverse legal systems emphasising different aspects. Neuroscience big data require a concerted approach to research across boundaries, wherein ethical aspects are integrated within a transparent, dialogical data governance process. We address this by developing the concept of “responsible data governance,” applying the principles of Responsible Research and Innovation (RRI) to the challenges presented by the governance of neuroscience big data in the Human Brain Project (HBP).
Highlights
The advancement of neuroscience is of critical global importance, with immense potential benefits for society
We provide the intellectual context for this work by reviewing the literature on big data ethics and governance, illustrating the points in the data lifecycle at which issues arise, outlining the approach and methods employed in designing big data governance frameworks using Responsible Research and Innovation (RRI) for the Human Brain Project (HBP), discuss and reflect upon the outcomes of implementing ‘‘responsible data governance,’’ and conclude with suggested directions for related research
In answering the question of how ethical issues can be integrated into approaches to neuroscience big data governance, we have contextualised and presented the development of ‘‘responsible data governance’’ to address the need for ethical governance of neuroscience big data in the HBP
Summary
The advancement of neuroscience is of critical global importance, with immense potential benefits for society. The establishment of the International Brain Initiative at the end of 2017, a partnership consisting of the largest brain projects, is evidence of the high value placed on global cooperation in neuroscience Accompanying these needs for intellectual engagement with the broader neuroscience community, increased technological reliance, and a focus on continuing innovation for the benefit of humanity is the use of big data and related analytical techniques. These analytics include descriptive, diagnostic, predictive, and prescriptive varieties, each with distinctive applications (Chalcraft, 2018). Big data analytics in biomedical contexts are perceived as an evolving necessity, sometimes framed as a change from hypothesis-driven research to data-driven research, and often viewed as leading to highly desirable outcomes such as targeted therapeutics and personalised medicine (Merelli et al, 2014)
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