Easy-to-use RDF-compliant metadata templates for subject-specific metadata with the AIMS Metadata Profile Service

High-quality subject-specific metadata is a key requirement for FAIR research data and thus also the comprehensibility and reproducibility of research. Within the context of NFDI4ING and the Applying Interoperable Metadata Standards (AIMS) project, we have developed an approach to create subject-specific RDF-compliant metadata profiles (in the sense of SHACL shapes) that enable precise and flexible documentation of research processes and data. Our developed approach enables domain experts to employ the advantages of existing linked data technologies in the context of developing metadata profiles that are machine-interpretable and that allow the semantic encoding and validation of metadata and data. A hierarchical inheritance approach in combination with relatively simple modular profiles enables the modelling of complex setups while keeping the individual profiles highly reusable in different contexts. This increases the interoperability of both the profiles and the resulting data. In addition, the approach gets by with low- and medium-specificity ontology terms that can be assumed to be available for many disciplines, and still achieves sufficient precision for typical scientific applications via their context-specific use and combination. To facilitate the modelling process and make it accessible to users with only limited knowledge about ontologies, we have developed a web service that provides a graphical user interface for creating metadata profiles. The metadata profile service is open source and allows the integration into other tools, such as the RDM platform Coscine. Its frontend allows searching for suitable terms from existing terminologies and adding them to a profile along with restrictions on the permitted value nodes, allowing setting expected data types, classes, or nodetypes as well as the cardinality of attributes. This allows users without knowledge in SHACL to create metadata profiles, which can be used to create, display and browse profile conformant RDF metadata by using tools like the SHACL Form Generator. In order to support communities with the development of metadata profiles, the service also supports their curation. In particular, profiles can be submitted for approval by a scientific community. If a profile is approved, it receives a corresponding tag, making it possible for users to find peer-reviewed profiles recommended by their community. In the follow-up project AIMS 2, we will apply the previously developed modelling approach to new scientific disciplines: Materials Science and Surface Physics. This includes the integration of metadata profiles into electronic laboratory notebooks (ELNs) as common tools used to document research data. Using the open source ELN eLabFTW as an example, we will implement the use of profiles within the documentation of experiments to support researchers in documenting all necessary information. In conjunction with an option to export semantic RDF data from the ELN, this allows eLabFTW-users to record semantic metadata without changing their existing workflows. In addition, we will improve the option to explore and display profile conformant metadata in the metadata profile service and facilitate the creation of interdependent metadata profiles, which makes it easier to adhere to a modular and hierarchical modelling approach that improves the reusability of the created profiles.