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New IUCrJ paper: FAIR data – the PaN communities move together towards Open Science

Data storage, traceability, and data use and reuse in the years following experiments is an increasingly important topic in Europe and worldwide. Following the FAIR principles in the whole research data life cycle has also become a requirement of the EC and other funding agencies, for both EU-funded projects and experiments at EU-funded RIs.

The white paper titled FAIR data – the photon and neutron communities move together towards open science* – recently published on the International Union of Crystallography, IUCr Journal – addresses the imperative of adopting FAIR (Findable, Accessible, Interoperable, Reusable) data principles within photon and neutron (PaN) research infrastructures (RIs).

The paper, which will be presented to ESRF users during a tutorial on Monday, February 10th, 2025, emphasises the need for open and transparent scientific data management, and serves as a starting point for a common user and RI approach on the European scale to achieve FAIR data.

What are the main challenges in Implementing FAIR Principles?

As outlined in the paper, PaN facilities support a diverse array of scientific investigations across disciplines such as physics, chemistry, and biology, and generate substantial data volumes, sometimes reaching up to 1 petabyte daily. Ensuring that all this data adheres to FAIR principles necessitates significant efforts, including:

  • Expanding data storage capacities, and developing and deploying effective data storage solutions.
  • Establishing comprehensive metadata schemes.
  • Implementing efficient data pipelines tailored to individual experiments.

Additionally, considerations related to the carbon footprint of large-scale data storage, user authentication, access rights, and cybersecurity are integral to this transformati

After summarising the current status of implementation of FAIR principles in PaN RIs and communities, the document makes a proposal of how the process can be accelerated and streamlined in the future, also outlining best practice in data handling and responsibilities with the aim to motivate a large number of European users to contribute to the development and to make best use of FAIR principles.

Risks and benefits of FAIR Data

One risk associated to the implementation of FAIR data is the limited effectiveness of reaching a FAIR data platform despite best efforts due to the rich and complicated range of experiments carried out across the community. This risk needs to be mitigated through cooperation across the communities and RIs but requires a financial basis for development and maintenance of the tools as well as for data storage and curation.

On the other hand, adhering to FAIR principles offers numerous advantages:

  • Enhanced scientific rigor: Ensures data is consistently findable and accessible in the long-term.
  • Facilitated data sharing: Simplifies data exchange and reuse, promoting collaborative research.
  • Increased data findability even after the original researcher departs, with clear documentation lowering barriers for reuse.
  • Support for advanced applications, such as machine learning and digital twinning applications, enabling new predictions and discoveries.

In the process towards full FAIR data adoption, RIs should commit to developing and communicating data policies, providing tools and training for FAIR data practices, and ensuring data storage and accessibility, while users are expected to engage in proper experimental design, provide comprehensive metadata, curate data during experiments, and adhere to best scientific practices, including citing data DOIs in publications.

A collaborative Effort

Role and responsibilities of the RIs

Large-scale RIs provide users with guidance, training, and resources to ensure FAIR-aligned experiments. Many users seek preparation guidelines, and RIs support them by offering best practices in data handling, modern tools and applications, and continuously updated FAIR data policies covering acquisition, storage, security, and accessibility.

To implement FAIR principles effectively, RIs must establish standardised procedures across experiments, ensuring uniform metadata catalogues, structured logbooks, optimised storage, and interoperable data formats across PaN facilities. While facilities manage instrument metadata, users contribute through documentation and collaboration.

For long-term data reuse, RIs must ensure standardised access policies, providing storage, computational resources, and software for up to 10 years, with permission-based access and a default three-year embargo. They should also generate DOIs for raw and published data while assessing the environmental impact of data storage.

However, the paper emphasises that RIs cannot achieve this transformation in isolation, and outlines the roles and responsibilities of both RIs and users, highlighting their shared accountability in achieving FAIR data standards. Active collaboration with user communities is essential, who should engage in creating and utilising tools that facilitate FAIR data practices.

Roles and responsibilities of the users

Users of PaN facilities are essential, too, in implementing FAIR principles, working closely with RIs to establish common set of standards and tools required for a FAIR data research data lifecycle that is appropriate and robust. Their responsibilities span from experiment design to data publication, ensuring transparency, quality, and accessibility.

Throughout the research process, users must provide accurate information, maintain detailed logbooks, and curate metadata, including sample details, workflow steps, and analysis methods. They are responsible for distinguishing essential data from setup-related or erroneous information while ensuring proper documentation and storage. During and after experiments, users analyse data, verify results, and optimise parameters, with all findings systematically recorded. To support Open Science, they must follow standardised data formats, contribute to metadata ontologies, and ensure that experimental workflows and analysis methods remain accessible for reproducibility. Publications should cite DOIs for archived data, and authorship must be properly recorded using ORCID identifiers.

By actively engaging with RIs and adhering to best practices, users thus help create a structured, transparent, and interoperable research data ecosystem that enhances scientific collaboration and long-term data usability.

Current Initiatives and Frameworks

Several organisations and initiatives are guiding the implementation of FAIR principles:

  • LEAPS (League of European Accelerator-based Photon Sources) and LENS (League of advanced European Neutron Sources): These bodies guide FAIR implementation in PaN RIs.
  • ESUO (European Synchrotron and Free Electron Lasers User Organization) and ENSA (European Neutron Scattering Association): These organisations represent European users and facilitate collaboration with RIs.
  • DAPHNE4NFDI Consortium: In Germany, this consortium brings together PaN user representatives to work with RIs in achieving FAIR open data.

Conclusion

Implementing FAIR principles is a significant step toward Open Science. Given that research at PaN facilities is publicly funded, the resulting data should be accessible to the public. The paper calls for a concerted effort from both RIs and user communities to embrace FAIR data practices, ensuring that scientific data is managed responsibly and remains a valuable resource for future research.


*B. M. Murphy, A. Götz, C. Gutt, C. McGuinness, H. M. Rønnow, A. Schneidewind, S. Deleddah and U. Pietschd, FAIR data – the photon and neutron communities move together towards open science, in IUCrJ, 2024, DOI: https://doi.org/10.1107/S2052252524011941

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