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FAIR and Structured Data: A Domain Ontology Aligned with Standard‐Compliant Tensile Testing

本体论 领域(数学分析) 极限抗拉强度 拉伸试验 计算机科学 材料科学 复合材料 数学 哲学 数学分析 认识论
作者
Markus Schilling,Bernd Bayerlein,Philipp von Hartrott,Jörg Waitelonis,Henk Birkholz,Pedro Dolabella Portella,Birgit Skrotzki
出处
期刊:Advanced Engineering Materials [Wiley]
卷期号:27 (8) 被引量:14
标识
DOI:10.1002/adem.202400138
摘要

The digitalization of materials science and engineering (MSE) is currently leading to remarkable advancements in materials research, design, and optimization, fueled by computer‐driven simulations, artificial intelligence, and machine learning. While these developments promise to accelerate materials innovation, challenges in quality assurance, data interoperability, and data management have to be addressed. In response, the adoption of semantic web technologies has emerged as a powerful solution in MSE. Ontologies provide structured and machine‐actionable knowledge representations that enable data integration, harmonization, and improved research collaboration. This study focuses on the tensile test ontology (TTO), which semantically represents the mechanical tensile test method and is developed within the project Plattform MaterialDigital (PMD) in connection with the PMD Core Ontology. Based on ISO 6892‐1, the test standard‐compliant TTO offers a structured vocabulary for tensile test data, ensuring data interoperability, transparency, and reproducibility. By categorizing measurement data and metadata, it facilitates comprehensive data analysis, interpretation, and systematic search in databases. The path from developing an ontology in accordance with an associated test standard, converting selected tensile test data into the interoperable resource description framework format, up to connecting the ontology and data is presented. Such a semantic connection using a data mapping procedure leads to an enhanced ability of querying. The TTO provides a valuable resource for materials researchers and engineers, promoting data and metadata standardization and sharing. Its usage ensures the generation of finable, accessible, interoperable, and reusable data while maintaining both human and machine actionability.
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