Transitioning from FAIR to AI Ready Data in the Physical Sciences

In recent years, the physical sciences community has been generating increasingly large and complex datasets, at a scale that is now beyond what can be fully explored or analysed by humans alone. As a result, researchers are turning to AI and machine‑learning techniques, which have matured significantly and offer powerful new ways to extract insight from data. However, while the adoption of FAIR data principles has improved data sharing and reuse, experience is showing that FAIR does not necessarily mean AI‑ready. Many datasets remain difficult to use effectively in AI and Machine Learning models.

This interactive workshop has been co-created by the Physical Sciences Data Infrastructure (PSDI) and the AI in Chemistry Hub (AIchemy). It aims to bring together researchers, data professional and infrastructure developers to facilitate knowledge exchange and explore what it truly means to be “AI Ready”. The workshop is comprised of invited presentations, lightning talks from participants and interactive discussion sessions. The talks will share current practices, highlighting successes and challenges, and the discussion sessions will explore the practical approaches and tools for evaluating and improving AI readiness.