In the context of the National Research Infrastructure Swiss CAT+ at EPFL (West Hub) and ETHZ (East Hub) initiated by the ETH-RAT in 2021 for the development of a state-of-the-art autonomous and data-driven chemistry laboratory for the discovery and optimization of new catalysts, the need for highly structured data generation and management was immediately recognized. The Swiss CAT+ team turned to the Swiss Data Science Center (SDSC) at EPFL to design a data management system for this new research infrastructure. The project has since produced two cornerstone components.The first is a comprehensive, FAIR-compliant Matryoshka file format designed to represent complex chemical experiments. This “Matryoshka” format supportsdigital chemistry by capturing experimental data and metadata in a structured way, thereby enabling broader scientific data interoperability. The second is the research data infrastructure (RDI), a Kubernetes-compatible platform developed to serve the generated data to the research community. The RDI was conceived from the ground up to embody the principles of FAIR: Findability, Accessibility, Interoperability and Reusability. Data are made findable through a user interface with advanced search functionality. Accessibility is ensured by offering public download options for data sets stored inan S3-based system). Interoperability is achieved by mapping metadata to a defined ontology expressed in the Resource Description Framework (RDF), incorporating established chemical ontologies such as the Allotrope Foundation Ontology. Reusability is ensured through standardized metadata annotation and advanced query tools based on SHACL, which enable researchers to navigate the database efficiently and retrieve data in a transparent way that supports cross-disciplinary adaptability. In addition to FAIR, the system places a strong emphasis on reproducibility. Reproducibility is one of its key advantages, made possible by the automation and standardization of both the data generation and metadata annotation with Argo workflows . This approach ensures that identical workflows can be reliably reproduced in other laboratories adopting similar infrastructure. Overall, this entire initiative emphasizes reusable, domain-agnostic components that extend well beyond chemistry, offering a foundation that can be adapted to a wide range of scientific and industrial domains. In doing so, it contributes directly to the advancement of ORD practices in Switzerland and internationally.