Improvement of data and metadata quality in catalysis research: A use case-driven methodology

The goal of the NFDI4Cat project is to establish a National Research Data Infrastructure for catalysis research in Germany that ensures the data and metadata collected and shared by researchers are of high quality and adhere to established standards. To achieve this goal, a comprehensive use case (UC) collection methodology has been developed. The methodology is based on the collection and analysis of use cases for research workflows and data therein provided by the researchers working in the field of catalysis. The proposed methodology includes detailed guidelines for the information collected within a particular UC, ensuring that it is relevant, accurate and complete. The collected UC data are then evaluated based on established criteria for data and metadata quality. Any identified issues are addressed through the collaboration with the respective researchers, to ensure that the use cases meet the required standards. The collected use cases are then standardized, which in particular includes mapping the data and metadata to relevant ontologies and vocabularies, as well as ensuring consistency across different use cases. The standardization process is coupled with a semantic representation of metadata within the Resource Description Framework (RDF) followed by appropriate extension of the ontology being developed. The semantic framework allows for easy integration and cross-referencing of data. It ensures that the data are machine-readable, linked, and can be easily integrated with other datasets, making it more discoverable and useful for the catalysis research community. Within the project, special attention is paid on the collection of UCs from different fields, including biocatalysis, homogeneous catalysis, and heterogeneous catalysis. This will provide a comprehensive representation of the metadata related to catalysis. The proposed methodology serves as a valuable resource for the catalysis research community, promoting adherence to established standards and ensuring that the data and metadata shared by researchers are of high quality.