GO FAIR is a ‘bottom up’ initiative that aims at making fragmented and unlinked (research) data Findable, Accessible, Interoperable and thus Reusable (FAIR).
These FAIR principles actually have a much broader scope than just handling the research data tsunami. In principle, they encompass all data-related sectors. They form the basis of a trusted environment where researchers, innovators, companies, and citizens can publish, find, and re-use each other’s data and tools for research, innovation, and educational purposes.
Towards a common environment for data-driven research and innovation around the world
There is a rapidly growing, world-wide consensus among scientists, science funders, and policy makers that the transition to truly data-driven Open Science can only be achieved when we collectively build a globally interoperable research infrastructure.
In Europe (EOSC), the United States (The Commons), Australia (AORC), and Africa (ADIRC) efforts to works towards an Internet of FAIR Data and Services (IFDS) are already under way. In context of the European Open Science Cloud (EOSC) the appointed High Level Expert Group recommended to realise such an infrastructure
• as a federated environment for scientific data sharing and re-use,
• based on existing and emerging elements in the Member States,
• with lightweight international guidance and governance, and
• with a large degree of freedom regarding practical implementation.
These recommendations are GO FAIR’s point of departure.
The GO FAIR implementation approach
The core of GO FAIR is a federation of existing topical networks of excellence that collectively commit to the FAIR principles in terms of standards, protocols, and best practices. Thus, GO FAIR follows the recommendation of the EOSC High Level Expert Group to ‘federate the gems’.
The GO FAIR implementation approach is based on three interactive processes: building the technical infrastructure (GO BUILD) is complemented by a change programme involving relevant stakeholders (GO CHANGE) and training the data stewards capable of providing FAIR data services (GO TRAIN).
France, Germany and the Netherlands have established an internationally operating office to support and coordinate the establishment of a series of so-called “Implementation Networks” (INs) in European Member States and beyond.
An overview of current Implementation Networks can be found here.
GO FAIR’s Implementation Networks have been established or are under development with resonance not only in Europe but also in other regions like the United States, Australia, Latin America, and Africa.
Expected impact and benefits
The expected impact and benefits are substantial. Users will be able to search and analyse linked FAIR data sources much more efficiently, in turn supporting and enabling more effective research, the potential to discover unexpected associations and developments, and ultimately to expedite innovation. The increased speed and efficiency of data usage will also facilitate the rapid validation of hypotheses and evaluation of treatment methods.
At this point, it is hard to estimate the actual economic impact and added value of the GO FAIR initiative, but it is highly likely the implementation cost will be substantially lower than the long-term impact of the efficiency increase in a world progressively dominated by largely unmanageable and partially actionable ‘Big Data’.