SciCat
SciCat is a database and web application for managing scientific datasets and their associated metadata according to FAIR principles (findable, accessible, interoperable, reusable). At the Franklin, we have multiple scientific instruments which generate data that is being automatically indexed by SciCat to enable data capture and sharing. This benefits our scientific users by giving them a single location for discovering scientific data generated at the Franklin, downloading it and sharing it with partners.
We are contributing to the SciCat community both contributing to the technical core and taking part in shaping the policy and governance of the project. We regularly attend the development meetings and the annual SciCatCon. We have contributed to testing the software and refining new features, most recently surrounding the migration of the backend to a new technology stack and testing authentication with Keycloak OpenID Connect (OIDC) for single sign-on. We are also contributing to the related PySciCat project, a Python interface, which underpins much of our associated tooling. We have recently created a tool for exporting key metrics from SciCat (such as number and size of datasets by user, instrument and principal investigator) on an ongoing basis, built as a Prometheus exporter. We are contributing to making SciCat more scalable by developing Kubernetes manifests.
Currently, we are moving it to a microservices architecture that will support the large volume of scientific data being generated at the Franklin to enable more datasets to be accessible by the scientific community and the public.
