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.
According to the European Open Science Cloud (EOSC) report this should be a ‘federated, globally accessible 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’.
In Europe (EOSC), The United States (The Commons), Australia (AORC), and Africa (ADIRC), efforts to collaborate are already under way to prevent renewed silo formation and to ensure international interoperability. The EOSC is branded by the High Level Expert Group (HLEG) in its report to the European Commission as ‘The Internet of (FAIR) Data & Services’ (IFDS).
‘GO FAIR’ (short for a lightweight, international fast track approach of the Internet of FAIR data and services by Global Open FAIR Implementation Networks) is an early-mover-driven ‘bottom up’ initiative to start working on a trusted environment where public and private sector partners can deposit, find, access, exchange, and reuse each other’s data, workflows, and other research objects. This Internet-type infrastructure must put computers in the mix as a ‘first class citizen’, as the current data streams can no longer be managed and interpreted without computer-assistance throughout the entire research cycle.
The core of GO FAIR is a federation of existing topical networks of excellence that collectively commit to the FAIR approach and capitalise on their critical mass to make choices in the implementation of the FAIR principles in terms of standards, protocols, and best practices. It therefore essentially implements the recommendation of the EOSC HLEG to ‘Federate the Gems’.
The GO FAIR movement aims at making fragmented and unlinked (research) data Findable, Accessible, Interoperable and thus Reusable. These FAIR data principles actually have a much broader scope than just handling the research data tsunami. In principle, they encompass all data-related sectors.
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).
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’.
The Netherlands, in close partnership with Germany, and a growing number of additional countries is helping to coordinate the establishment of a series of such Implementation Networks in European Member States and beyond, with an additional specific priority to undertake a co-leadership role in Africa. So far (March 2017), six GO FAIR INs have been established or are under development, coordinated in four European Member States with resonance also in other regions like the United States, Australia, Latin America, and Africa.