Materials Data Infrastructure and Ontology Development for Exemplary Reference Dataset

The development of new engineered materials relies on high-quality reference data and material standards. Especially mechanical properties at high temperatures, such as creep resistance, are crucial for potential structural applications of new alloys. Within NFDI-MatWerk, the exemplary reference dataset uses data from creep experiments on a single crystal Ni-based superalloy with benchmark material properties, along with a detailed experimental description and relevant information on material provenance and condition. The FAIR (Findable, Accessible, Interoperable, and Reusable) principles are applied when distributing the reference datasets along with their metadata. FAIR Digital Objects (FDOs) are created to support machine readability and accessibility using Persistent Identifiers (PIDs). Our proposed workflow highlights two aspects: creation of FAIR DOs and ontology development. The experimental data generated is stored in repositories, such as Coscine or published on, for instance Zenodo. We develop a data schema to define a structured approach for collecting all the required information on a creep experiment. The entries are grouped according to their content and summarized under respective headlines, thereby forming a hierarchy of concepts. ... mehrBased on this schema we create FDOs to make the reference dataset and its metadata interpretable for the external material scientists’ community. Moreover, we develop a semantic description in the form of an ontology and a metadata schema to make the information explicit, and to enable interoperability between databases, automated analysis, and integration into simulation workflows. The reference dataset ontology (RDO) provides a formal description of concepts, which define reference data, e.g., standard, validation, curation, etc. and are based on the exemplary reference dataset. Thus, classifies the RDO as a top-level ontology with universal concepts. The experimental workflow and material characteristics, which are important for the interpretation of research data, must be described in an application-level ontology or mapped to other related ontologies, e.g., PMD (Platform Material Digital) Application Ontologies. This approach ensures the FAIRness of the data and accelerates research in the field of Material Science and Engineering by providing high-quality reference datasets and material standards for the development of new alloys for high-temperature applications. The workflow, part of an overarching framework for management of reference data, has been successfully implemented for an example use case and will be supported by easy-to-use tools in the future.