In today's data-driven scientific research landscape, the management of vast amounts of data, together with loweffort search capabilities, easy access and retrieval of acquired data is crucial for enabling successful
collaborations, empowering all stakeholders to contribute to data enrichment and fostering scientific advancement. Metadata catalogues, where fields are extracted from datasets and inserted into a searchable database, are pivotal in accessing scientific data in such a landscape. Data FAIRness qualities have become more and more important as an increasing number of publishing entities require transparency in published results and their provenance. Metadata catalogues help facilitate FAIR principles by enabling findability, and accessibility. With careful curation of metadata fields, they can play a vital role in interoperability.
We present SciCat a metadata catalogue designed to meet the needs of the community of scientists carrying out experiments and measurements. SciCat offers a scalable and flexible solution that empowers researchers to effectively manage, share, publish, and discover scientific datasets, thereby fostering collaboration, increasing data visibility and accelerating scientific progress.