FAIR data in mechanical testing of polymers: Implementation of the full-notch creep test ontology (OntoFNCT)

The ongoing digitalization trend has fostered a significant shift in polymer science and engineering towards increased utilization of digital methods. The integration and reuse of data across materials synthesis, production, characterization, and modeling leads to enhanced innovation. Recognizing the importance of FAIR data principles, OntoFNCT is introduced as an ontology specifically tailored to represent data from full notch creep tests (FNCT) in the interoperable RDF format. FNCT is a method for assessing polymer material behavior under defined stress and environmental conditions. OntoFNCT is aligned with the corresponding ISO 16770 standard and enriches FNCT data with Semantic Web technologies (SWT). Using OntoFNCT, data exchange among stakeholders is facilitated while enhancing speed, precision, and reliability in material evaluation and quality control processes. The integration with higher-level ontologies promotes interoperability and reusability of FNCT data across diverse sources. Additionally, an automated Python-based analysis workflow tailored to FAIR RDF graph data obtained through SPARQL queries was developed to determine FNCT characteristic values. Its usability was successfully demonstrated through its application to real FNCT datasets.