For scientists, data is the lifeblood of research. Collecting, organizing and sharing data both within and across fields drives pivotal discoveries that make us better off and more secure.
Making data open and available, however, only answers part of the question about how different scientists — often with very different training — can draw useful conclusions from the same dataset. In order to promote and guide the cultivation and exchange of data, researchers have developed a set of principles that could make the data more findable, accessible, interoperable and reusable, or FAIR, for both people and machines.
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