The article introduces the FAIR Guiding Principles for scientific data management and stewardship, emphasizing the need to improve the infrastructure supporting the reuse of scholarly data. The principles, Findability, Accessibility, Interoperability, and Reusability (FAIR), aim to enhance the reusability of data holdings by both humans and machines. The authors highlight the importance of good data management in facilitating knowledge discovery and innovation, and address the challenges of data discovery and reuse in the current digital ecosystem. They provide examples of FAIR implementations in various data repositories and platforms, such as Dataverse, FAIRDOM, ISA, Open PHACTS, and wwPDB, demonstrating how these principles can be applied to different types of data and research objects. The article also discusses the significance of machines in data-rich research environments and the role of FAIR principles in achieving machine-actionability. Finally, it calls for all stakeholders to adopt and implement the FAIR principles to improve the management and stewardship of scholarly data.The article introduces the FAIR Guiding Principles for scientific data management and stewardship, emphasizing the need to improve the infrastructure supporting the reuse of scholarly data. The principles, Findability, Accessibility, Interoperability, and Reusability (FAIR), aim to enhance the reusability of data holdings by both humans and machines. The authors highlight the importance of good data management in facilitating knowledge discovery and innovation, and address the challenges of data discovery and reuse in the current digital ecosystem. They provide examples of FAIR implementations in various data repositories and platforms, such as Dataverse, FAIRDOM, ISA, Open PHACTS, and wwPDB, demonstrating how these principles can be applied to different types of data and research objects. The article also discusses the significance of machines in data-rich research environments and the role of FAIR principles in achieving machine-actionability. Finally, it calls for all stakeholders to adopt and implement the FAIR principles to improve the management and stewardship of scholarly data.