FAIR data – the photon and neutron communities move together towards open science - B. M. Murphy; A. Götz; C. Gutt; C. McGuinness; H. M. Rønnow; A. Schneidewind; S. Deledda; U. Pietsch (IUCrJ)
The topic of data storage, traceability, and data use and reuse in the years following experiments is becoming an important topic in Europe and across the world. Many scientific communities are striving to create open data by the FAIR principles. This is a requirement from the European Commission for EU-funded projects and experiments at EU-funded research infrastructures (RIs) and from many national funding agencies. This is challenging for users of large-scale RIs such as neutron, photon, synchrotron and free-electron laser facilities. Users of photon and neutron (PaN) RIs employ a wide range of scattering, imaging and spectroscopic methods investigating the behaviour of matter with a broad scientific base across physics, chemistry and biology, including engineering, environmental, cultural heritage and medical applications. They produce large data volumes of up to 1 PByte per day in some cases. To ensure all these data are FAIR requires an enormous effort from PaN RIs. It requires not only the expansion of data storage capacity, but also the development and deployment of software for effective data storage, metadata schemes and implementation of effective data pipelines at each individual experiment across RIs. FAIR data also affect the carbon footprint related to large amounts of data and raise questions related to user authentication, rights of access and cyber security. The RIs alone cannot achieve such a transformational process. For successful open science, cooperation of the user communities is essential as they need to create and utilize existing tools to deliver FAIR data. In this white paper, the European PaN community outline and discuss the role and responsibilities of the users and RIs and their common accountability to achieve FAIR data. This paper shall serve as a starting point for a common user and RI approach on the European scale to achieve FAIR data.