Implementation of a pipeline for collecting, ingesting and transforming data into standard formats for the LAME FIB-SEM

This thesis presents the development of a FAIR-by-design data management platform for the Laboratory of Electron Microscopy (LAME) at Area Science Park in Trieste, Italy. LAME supports high-resolution materials research using techniques such as Scanning Electron Microscopy (SEM), Focused Ion Beam-SEM (FIB-SEM), and Scanning Transmission Electron Microscopy (STEM), generating large volumes of complex data that require structured, interoperable management. The platform streamlines data acquisition, metadata capture, validation, and publication in line with the FAIR (Findable, Accessible, Interoperable, Reusable) principles. Built using Django, it enables researchers to upload structured NeXusformat data through an intuitive web interface. All components are deployed within ORFEO, the centralized data center at Area Science Park, which hosts MinIO for object storage, Authentik for secure authentication, and NOMAD Oasis for FAIR-compliant internal publishing under the NFFA-DI (Nano Foundries and Fine Analysis – Digital Infrastructure) framework. Datasets are also integrated into OFED (Overarching FAIR Ecosystem for Data), ensuring standardized, traceable, cross-institutional access. The platform is aligned with NFFA-Europe standards via tools like MetaRepo and will soon be publicly hosted on ORFEO. The underlying codebase and documentation will be made openly available on GitHub to support reuse and adoption by other scientific facilities.