Guest post by Alastair Dunning1, Susanna-Assunta Sansone2, Marta Teperek1
(authors listed alphabetically by surname)
1 Delft University of Technology, the Netherlands; 2 Oxford e-Research Centre, Department of Engineering Science, University of Oxford, UK
Science is living in the era of data – the reuse of other people’s data can drive new research questions and products, and inspire new scientific discoveries. This was the motivation behind the FAIR Principles (published in 2016), which provide researchers with a framework to improve the quality of their research: making their data more Findable, Accessible, Interoperable and Reusable. To turn these aspirational principles into reality, however, we need to provide researchers with FAIR-enabling tools and services that make frictionless the (complex) technical machinery of (meta)data standards and identifiers that underpins FAIR. Service providers, librarians, journal publishers and funders, among others, are actively working to deliver the next generation framework for FAIR data, which is collaborative, interdisciplinary and sustainable. FAIR has also become the (core) mission of a growing number of initiatives – especially in Europe, USA and Australia – encompassing R&D projects and programmes, institutional, national and global service provision, alliances and societies, training and educational efforts. In particular, numerous policy makers from around the world have articulated a vision of global open science and embraced FAIR as the driving principles. In Europe, for example, the vision is being realised through the ambitious European Open Science Cloud (EOSC) programme, across all disciplines. Continue reading →