This morning, the new Master in Data Management and Curation specialization course started, organized by CNR-IOM, Area Science Park and SISSA as part of the activities of the NFFA-DI and PRP@CERIC projects.

The Master, in its first edition, is designed to provide in-depth training in the management, curation, cataloguing and analysis of research data, skills that are increasingly crucial in the scientific world. The Master's program is in line with the needs of the European Commission and other funding bodies, which require that data be processed according to the FAIR principles. These principles guarantee that data are Findable (easily available), Accessible (accessible to anyone who needs it), Interoperable (integrable with other data and usable by different applications) and Reusable (reusable for new research)

The course, lasting nine months, is divided into a teaching phase of 166 hours of theoretical lessons and a seven-month practical phase to be carried out at the laboratories of the institutions from which the participants come. The structure and program of the Master are totally innovative in the national and international panorama, with a specific focus on the implementation of FAIR-by-design processes during the months of internship in the laboratory.

FAIR-by-design is a native management of research data: it concerns the management of research data from their creation, ensuring that they are treated according to FAIR principles until their publication. To realize FAIR-by-design, it is essential to design and implement an automated chain of hardware and software connections. This chain includes research instrumentation, data annotation software to obtain metadata (additional information about the data) and data analysis programs. The adoption of FAIR-by-design involves a significant reduction in human intervention during all phases of the data life cycle, while ensuring high quality and integrity. This approach requires considerable effort and use of resources in the initial design phase, but represents a strong point for research infrastructures that adopt it, significantly improving the management and quality of data in experimental and computational laboratories.

At the end of the course, researchers will have acquired theoretical and practical skills in Open Science Methodologies, FAIR-by-design data management, use of tools and software for the acquisition and enrichment of metadata and tools and methods for the analysis of scientific data.

Each of the NFFA-DI operational units is represented by one or more participants in the Master, who during the months of internship will operate as a DataSteward in the various nodes of the project, contributing to the construction of an interoperable and integrated nanoscience data management infrastructure across the national territory.