Wide-spread data sharing has started to permeate the brain imaging community from funders to researchers. However, in recent years there have also been some concerns raised regarding ethical issues related to privacy and data ownership among others. In the parent award we are leveraging and extending a privacy preserving decentralized data sharing platform called COINSTAC to perform a study of gene-by-environmental effects by pooling together data from across the world, some of which is unable to be openly shared. In this supplement we will study various bioethical issues related to different data sharing strategies. This will include calculating risk scores from existing data to evaluate the effectiveness of machine learning to potentially reidentify from similar or different data types, a detailed survey of various policy makers and stakeholders including researchers, federal employees, IRB members, and more, and finally the development of a forward looking white paper addressing both privacy, policy, and regulatory aspects which attempts to frame the various aspects that arise in the contact of the spectrum of data sharing approaches including fully open, ?trust? based via data usage agreements, privacy preserving via tools like COINSTAC, and more. The outcomes of this supplement will provide a useful guide for the field going forward and also provide initial data necessary to develop a larger scale project on these topics going forward.
The era of big data, open science, and deep learning is upon us, and data sharing can be done in various ways ranging from fully open to privacy preserving to fully closed. However bioethical issues related to risk, privacy, and data sharing strategies have not been well studied in the context of combined brain imaging, genomics, and macro-environmental data and can be especially sensitive in the context of information such as substance use. In this supplement we will quantify risk levels, survey a broad community of stakeholders, and develop recommendations for the field going forward.
