Article by Stefaan G. Verhulst: “Since 2016, the FAIR principles — specifying that data should be Findable, Accessible, Interoperable, and Reusable — have served as the foundation for responsible open data management. Especially within the open science community, FAIR has shaped how we publish, share, and reuse scientific and public data. It brought a common language to a fragmented ecosystem.
But as artificial intelligence transforms how knowledge is produced and decisions are made, FAIR alone may no longer be enough. We now face a new question:
What does it mean for data to be AI-ready — and ready for what kind of AI?
Earlier this year we sought to provide an answer to that question by proposing the FAIR-R Principles and Framework. Last week, Frontiers, released its own FAIR² data management platform. Both seek to extend FAIR, but they diverge in focus and method. FAIR-R introduces a conceptual expansion; FAIR² adds operational guidance. Together, they reveal how our understanding of data readiness is evolving in the age of AI…(More)”
