The multiscale nature of materials as well as the various methods of investigation, leads to Material Science and Engineering (MSE) data to be highly heterogeneous in terms of its structure and size. Data documentation and the methods to generate them are typically application-specific, so when (re-)using data from different applications, metadata and semantics are often misaligned and used inconsistently. Also, metadata is frequently stored in an unstructured manner, lacking interoperability and machine understandability. The NFDI-MatWerk consortium aims to address these issues, through the development of a comprehensive set of tools and services within specific infrastructure use cases. The result is a decentralized data infrastructure where (meta)data quality is improved. Nonetheless, many solutions are implemented on local infrastructure and behind institutional walls, limiting the findability, and thereby re-usability.

The MSE Knowledge Graph (MSE-KG) [1] is developed as a central knowledge base containing interconnected data enriched with semantics. By linking the metadata of the dissociated infrastructural components, it acts as “semantic glue” connecting developments into a central searchable data space. The semantic backbone of the MSE-KG is the MatWerk ontology (MWO) [2] which provides the key concepts necessary for finding data in the MSE domain and extends concepts from the NFDI-core ontology [3]. The MSE KG currently contains more than 8K triples, representing 1893 entities in a highly interconnected fashion (1.48). Represented are (i) community: researchers, research projects, universities, and institutions; (ii) infrastructure: software, workflows, controlled vocabularies, instruments, facilities, educational resources and events; and (iii) data: repositories, databases, publications, datasets, and reference data.

Aligning local data infrastructure semantics to the MSE-KG will allow establishing (meta)data feeds to the MSE-KG. Wide coverage of the MSE metadata landscape will result in a utility that can be used to query and exchange data across domain boundaries, without data providers having to forfeit governance of their own data. This will increase the overall visibility and accessibility of resources in the MSE field and pave the road to innovation in MSE.

References
[1] https://go.fzj.de/mse-kg
[2] http://purls.helmholtz-metadaten.de/mwo/
[3] https://github.com/ISE-FIZKarlsruhe/nfdicore