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In 2016, the FAIR Guiding Principles for scientific data management and stewardship were published, laying out guideposts for scholarly data producers to make their data discoverable and usable in the future. The FAIR principles seek to ensure that data is Findable, Accessible, Interoperable, and Reusable. At the time of their publication, they articulated and centralized many points of discussion among data scientists, and since then, they have been widely referenced and utilized in academia.Of course, collaboration and data reuse are fundamental to academic research. But the ideas of FAIRness can actually bring value to any research organization, including life sciences companies with vast archives of proprietary data. For example, a pharma company may expect that its data will always stay within its own walls, but its effective management and reuse can have dramatic …