PaNOSC are working toward and accessibility of Open Science and a PaN Data Commons serving the PaN community of scientists
Photon and Neutron (PaN) facilities are instrumental in scientific research, utilising powerful X-ray and neutron beams to analyse samples and generate high-resolution images at the nano-scale
The data produced by PaN facilities, amounting to petabytes of high-value datasets, hold immense potential for advancing our understanding of matter and biological processes.
The growing volume of data and data fragmentation is being considered by the European Commission, who now have proposed the European Open Science Cloud (EOSC) in 2015.
This visionary concept aims to make scientific data FAIR (Findable, Accessible, Interoperable, Reusable) across facilities and scientific domains, granting scientists access to data, software, and services from various European scientific sources.
In the long-run, PaNOSC envisions the availability and accessibility of a PaN Data Commons serving the PaN community of RIs and scientists.
PaNOSC: Driving Open Science and FAIR data
The PaN community is deeply committed to Open Science, FAIR data, and the EOSC. To facilitate collaboration and ensure the adoption of best practices, the PaNOSC science cluster was established.
This science cluster represents all European PaN Research Infrastructures (RIs) and works towards developing and providing data-related strategies and services for the scientific community, fostering connections with the EOSC. The PaNOSC science cluster is one of five science clusters in Europe collaborating to promote FAIR data and Open Science.
FAIR data services include:
- A PaN e-learning platform and a training catalogue
- A single AAI (Umbrella ID) enabling users to login to multiple applications and websites with one single set of credentials
- A federated search API for PaN data catalogues
- An Open Data Portal for searching and downloading data
- A standard protocol to enable third-party EOSC aggregators to harvest PaN open data and metadata
- The Virtual Infrastructure for Scientific Analysis – VISA, allowing access to data, software and services for data analysis and simulation using remote desktops and/or Jupyter notebooks in the browser
- A PaN software catalogue of packages relevant to the user community
- A framework for a common metadata schema, including an ontology of PaN techniques
- A standard data format (NeXus)
Initiatives: PaNOSC and ExPaNDS
The inception of the science clusters was supported by EC-financed projects aimed at jump-starting the development of the EOSC through collaborations with scientific communities.
Two notable projects, PaNOSC (2018-2022) and ExPaNDS (2019-2023), brought together the majority of PaN facilities in Europe and focused on incorporating FAIR practices into their workflows.
Through these projects, common policies, strategies, and solutions were devised to facilitate Open Science across European PaN facilities, ensuring the accessibility and openness of data for the EOSC.
Following the conclusion of the aforementioned projects, the PaNOSC science cluster continues to prioritise Open Science. The LEAPS and LENS data strategies reflect this commitment, emphasising the importance of FAIR and open data.
As experimental data becomes increasingly larger and complex, enabling reproducibility and facilitating data analysis for users becomes paramount. Additionally, opening facility data archives for reanalysis, including the utilisation of Machine Learning techniques, supports the discovery of new insights.
The FAIR implementation framework
To guide PaN facilities in achieving FAIR data practices, an updated FAIR implementation framework has been made available. This framework serves as a practical toolkit, providing guidance and tools for facilities to evolve their systems and processes to deliver FAIR data as it leaves the facility.
Facilities are encouraged to update their policies to align with the framework, which covers various aspects, including establishing FAIR data policies, implementing metadata standards for data annotation, adopting tools and processes for data management by both humans and machines, employing suitable persistent identifiers (PIDs) for research entities, developing active data management plans (DMPs), and conducting FAIR self-assessments.
Photon and Neutron (PaN) facilities stand as crucial contributors to scientific progress across multiple research domains.
By embracing Open Science, FAIR data, and the European Open Science Cloud, the PaN community and the PaNOSC science cluster have fostered collaboration, developed common policies, and provided essential strategies and services for the adoption of FAIR data practices.
As facilities prioritise FAIR data and open access, they pave the way for reproducibility, enhanced data analysis, and groundbreaking discoveries.