Enhancing FAIR Data Management in Materials Science and Engineering (MSE): Integrating FAIR Digital Objects into the MSE Knowledge Graph

The Materials Science and Engineering Knowledge Graph (MSE-KG) [1] serves as a central knowledge base for integrating and structuring research data within the NFDI-MatWerk [2]. It provides a semantic backbone that connects datasets, research outputs, institutions, and infrastructures, ensuring interoperability and enhanced data discovery. The MSE-KG facilitates a unified and structured approach to manage heterogeneous data. Despite its structured approach, challenges remain in ensuring that research objects remain machine-actionable, persistent, and interoperable across different domains. To address these challenges, the integration of FAIR Digital Objects (FDOs) has been proposed as a solution for enhancing machine-actionability and interoperability of digital research assets in the MSE domain. In the context of NFDI-MatWerk, with the integration of FDOs into the MSE-KG we aim to enhance the findability, accessibility, interoperability, and reusability of research data. This work investigates the representation of FDOs within the knowledge graph, addressing key questions such as the availability of FDOs, their association with datasets, provenance records, and licensing terms. By linking datasets, publications, and software to their respective FDOs, the MSE-KG provides structured access to research objects and ensures their long-term usability. The study further explores how FDOs are referenced within the knowledge graph via PIDs (Persistent Identifiers) and the implications of integrating semantic descriptions for enhanced machine-actionability/machine-interpretability. References [1] https://msekg-nfdi-matwerk-02.web.vulcanus.otc.coscine.dev/matwerk/ [2] NFDI-MatWerk Project: https://www.nfdi-matwerk.de