AIRBDS: Quantifying AI-readiness in bioscience data

A practical question keeps surfacing: how ready is our data for AI in the first place? In this session, Charlie Harrison from AIBIO-UK introduces AIRBDS-core, a metric for quantifying the AI-readiness of bioscience data. The talk walks through the methodology and the aims behind constructing the metric, and opens the floor for feedback and contributions from the community ahead of the project’s soon-to-be-released publication.

This is an accessible session for anyone who works with life sciences data and wants to understand what “AI-ready” actually means in practice.

What to expect

The session will start with a talk introducing AIRBDS-core: what it measures, the methodology behind it, and the aims that shaped its design. After that, we’ll open a discussion – questions, feedback and contributions are all warmly welcome, and this is a genuine chance to influence the work before it’s published.

Who it’s for

This call is aimed at data stewards, data leads, RDM professionals and researchers supporting or producing life sciences data. It will also be useful for anyone curious about AI-readiness, FAIR data, or how the two connect – well-managed, FAIR data is much of what makes data AI-ready in the first place.