Editor’s note: This guest post is authored for The Scholarly Kitchen by Fiona Murphy, Nicky Agate, Amy Price, and Stephanie Hagstrom, members of the Steering Committee for FSCI, a training and educational week taking place this year at the University of California, Los Angeles on August 5-9.
Today’s research knowledge can be harvested and data analyzed faster than has been possible in all previous generations combined. As a result, Open Research practices and outputs face a number of tensions between initial intentions and unforeseen consequences. For example, the FAIR Data Principles propose that research data should be Findable, Accessible, Interoperable, and Reusable — but nothing has prepared us for the use and misuse of personal data. Even if they start out ethically approved and safe in the researcher’s toolkit, they can later be sold to a third party in exchange for analytical services, enabling machines to identify disease states from a picture, classify your intelligence and demographic profile in four “likes” or less, or traffic organs and direct market to those that need them on social media.
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