Implementing a FAIR-by-Design Approach for Process Management in Nanoscience Foundries -Application in the CNR-ISMN cleanroom

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