The goal of this workshop is to share best practices and tools for the FAIRification and the FAIR data management of internal preclinical and clinical datasets in Pharma IT.

The advent of ML / AI for pharma is very promising, however without a basic amount of metadata and smart annotation of existing data assets, the algorithms cannot make much headway.

Several years of IMI knowledge management projects, experiments with data warehouses, data lakes etc. have made it clear that proper semantic annotation of data assets is hard and is resource intensive but a very important hurdle to overcome.

In this workshop, we will focus on concrete practical approaches and tools that exist today to bring existing pharma data assets in line with the FAIR Guiding Principles.

We will evaluate key topics around the Findability, Accessibility and Interoperability of datasets, and discuss the role in this of recent developments such as Bioschemas.

A welcome buffet dinner, sponsored by The Hyve, will take place the evening before the workshop at 18:00 at The Hyve offices.