Indeed, in the past we have defined integration methods, developed standards, created technologies, software and tools. So, we now have tools: what next in data integration?
We need to provide targets for developers, targets for data producers, metrics to assess their achievement.
Hence, our data need to be FAIR: Findable, Accessible, Interoperable and Re-usable!
A great interest on the implementation of the FAIR concept is presently shown at the decision level.
The European Council adopted Open Science and the reusability of research data as a priority.
In the context of the European Open Science Cloud (EOSC), FAIR principles are a core component of the EOSC Declaration.
The Directorate General for Research and Innovation of the European Commission started the FAIR Data EG Consultation.
The National Institutes of Health has launched the Big Data to Knowledge (BD2K) initiative.
Science Europe has adopted FAIR principles as the basis for sharing administrative data on funding.
The ELIXIR Research Infrastructure has released its statement on FAIR Principles.
IMI released a call for FAIRification of EFPIA datasets.
In order to make the FAIR concept a reality, we need to answer many questions, like: What is FAIRness? How to make FAIR data a reality? How to facilitate the translation to FAIR data? How to measure it?
On these topics, there are many on-going projects, like the EOSCpilot, FAIRmetrics, FAIRsharing, GO-FAIR.
So, it seems that now is the perfect time to discuss on these topics and related actions. All interested actors, with different levels of involvement and expertise, are invited to join forces and promote a common effort towards the implementation of a FAIR environment.