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Normative challenges in data governance: insights from global health research
Mathew Mercuri1,2,3,4,5, Claudia I Emerson6,7,8
1Institute on Ethics & Policy for Innovation, McMaster University, L.R. Wilson Hall, Room 3011, 1280 Main Street West, L8S 4K1, Hamilton, ON, Canada. mercurmd@mcmaster.ca.
None:
Many important questions in health professions education require datasets that are built from several sources, in some cases using data collected for a different purpose. In building and maintaining these datasets, project leaders will need to make decisions about the data. While such decisions are often construed as technical, there are several normative concerns, such as who should have access, how the data will be used, how products resulting from the data will be shared, and how to ensure privacy of the individuals the data is about is respected, etc. Establishing a framework for data governance can help project leaders in avoiding problems, related to such matters, that could limit what can be learned from the data or that might put the project (or future projects) at risk. In this paper, we highlight several normative challenges to be addressed when determining a data governance framework. Drawing from lessons in global health, we illustrate three kinds of normative challenges for projects that rely on data from multiple sources or involved partnerships across institutions or jurisdictions: (1) legal and regulatory requirements, (2) consent, and (3) equitable sharing and fair distribution.
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