Design refinement and commissioning of a FAIR-by-design integrated data management system for an STM laboratory

In recent years, the ever-growing volume and complexity of scientific data have made traditional data management practices inadequate. To address this issue, a new set of guiding principles for data management has emerged, asserting that high-quality research data must be F.A.I.R. — Findable, Accessible, Interoperable, and Reusable. This thesis initiates the adoption of FAIR practices in the STRAS laboratory at CNR-IOM in Trieste, Italy, specifically focusing on data produced through Scanning Tunnelling Microscopy (STM). Several solutions were developed to support the FAIR data transition. A workflow was designed within the electronic laboratory notebook eLabFTW to improve the organization, annotation, and traceability of research metadata. Additionally, a Python-based graphical user interface, named Meerkat, was created to assist researchers in preliminarily processing STM data, automating (meta)data management in eLabFTW, and visualising STM data. To ensure interoperability of the experimental data, STM output files were mapped onto the NXstm schema proposed by FAIRmat and prepared for conversion into the NeXus format, in order to facilitate their subsequent upload to the NOMAD data management platform. Despite the goals achieved during this thesis, the FAIR-ification process at STRAS remains ongoing. This work lays the basis for embedding FAIR principles into the laboratory’s daily practices, enabling more open, reproducible, and efficient scientific research.