Abstract
This chapter offers investigators a set of decision trees with detailed case examples to help them prepare Data Management Plans (DMP) that address ethical and information protection issues in big data research projects. It opens with an explanation of the 4Rs of big data research that is, reuse, repurposing, recombination and reanalysis. The 4Rs highlight the importance of ethical provence and ethical horizon; that is, the ethical implications of the possibility that investigators using big data for human research will draw their sources from pre-existing data from multiple kinds of sources and that other investigators will use their data in subsequent studies. The DMP decision tree encourages investigators to reflect on the ethical status of any consent provided by the human subjects under consideration, if known or potentially known, for both existing data and data proposed for collection. The decision tree also encourages investigators to reflect on the range of ethical implications of their research, including potential benefits and harms as well as implications for individual and group autonomy, social justice and trust in the institution of science. We offer the DMP decision tree as a tool to help investigators and their organizations become more adept in assessing the privacy and ethical risks of big data research with human subjects and, thus, ensure the public’s acceptance and participation in the projects they plan for the future. Working through the steps of the decision trees also highlights the need for investigators to seek counsel from various institutional resources relevant to protecting human subjects and their information in big data research, particularly their organization’s Institutional Review Board, office of general counsel, and computer security staff. From this perspective, we urge caution against downgrading the role of such organizations in managing human subjects research in big data until the scientific community as a whole has more experience with its complexities.
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Collmann, J., FitzGerald, K.T., Wu, S., Kupersmith, J., Matei, S.A. (2016). Data Management Plans, Institutional Review Boards, and the Ethical Management of Big Data About Human Subjects. In: Collmann, J., Matei, S. (eds) Ethical Reasoning in Big Data. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-28422-4_10
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