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Advances in science and technology have led to the creation of large amounts of data—data that could be harnessed to improve productivity, cure disease, and address many other critical issues. Consensus in the scientific community is growing that the transition to truly data-driven and open science is best achieved by the establishment of a globally interoperable research infrastructure.
A number of projects are looking to establish this infrastructure and exploit data to its fullest potential. Several projects in the United States, Europe, and China have made significant strides toward...
A number of projects are looking to establish this infrastructure and exploit data to its fullest potential. Several projects in the United States, Europe, and China have made significant strides toward this effort. The goal of these projects is to make research data findable, accessible, interoperable, and reusable, or FAIR. The expected impact and benefits of FAIR data are substantial. To realize these benefits, there is a need to examine critical success factors for implementation, including training of a new generation of data experts to provide the necessary capacity. On November 1, 2017, the National Academies of Sciences, Engineering, and Medicine organized a symposium to explore these issues. This publication briefly summarizes the presentations and discussions from the symposium.