The exponential growth of data generated in nanoscience research demands
robust frameworks for data management, sharing, and reusability. This thesis
investigates the implementation of a FAIR-by-design approach specifically
tailored for process management within nanoscience foundries, emphasizing
its application at the CNR-ISMN cleanroom facility.
In this context, the NFFA-DI (Nano Foundries Fine Analysis - Digital
Infrastructure) initiative plays a pivotal role by aiming to create a centralized
and FAIR-by-design ecosystem for managing experimental data across a
network of nanoscience laboratories. Such an infrastructure is crucial to
ensure standardized data practices, foster interoperability, and maximize the
scientific value of research outputs.
Starting from the foundational FAIR principles, the work addresses the
challenges associated with standardizing process documentation in nanofabrication. A comprehensive hierarchical taxonomy was developed, combining
international standards and community-defined terminologies to foster semantic clarity and interoperability across laboratories. Furthermore, an
existing laboratory management system, CAMS, was adapted to produce
FAIR-compliant data outputs through structured JSON reports, facilitating
seamless integration with external repositories.
The research culminated in the creation of a specialized plugin for the
NOMAD repository, enhancing its capability to handle nanofabrication data
effectively. The implemented solution supports detailed metadata extraction and promotes automated, standardized data sharing practices. This
integration not only improves data visibility and reusability but also sets a
foundation for ongoing refinement and community collaboration, thus significantly advancing the FAIR principles within nanoscience infrastructur
