The biggest barriers to cloud-based studies are ethical, legal, and administrative, said Benjamin Neale, associate professor in the Analytic and Translational Genetics Unit at Massachusetts General Hospital and the Broad Institute of the Massachusetts Institute of Technology (MIT) and Harvard. There is no consistent framework for what types of data should be available for what kinds of analyses, he said, and questions related to privacy and identifiability countervail against the drive to promote the use of the cloud for neuroscience research. Maryann Martone added that liability issues and legal uncertainty have become major problems for the research community, with the unintended consequence of clamping down on progress. She added that reuse of data, a central aim of the cloud, imposes burdens in data management, governance, and privacy.
These and other topics of discussion at the workshop are summarized in the following four chapters: issues related to protecting privacy in the cloud (Chapter 3); data management and promotion of interoperability (Chapter 4); considerations for assigning credit, determining ownership, and licensing data (Chapter 5); and governance, long-term funding, and sustainability of cloud-based platforms (Chapter 6).
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