2023/09/29 by Scott McClellan, Yuan An, McClellan, Scott +7 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Biomedical Text Mining and Ontologies #Digital Libraries (cs.DL) #FOS: Computer and information sciences #H.3.1 #Machine Learning in Materials Science #Semantic Web and Ontologies
paper · pdf · doi:10.48550/arxiv.2310.00078
openalex publication_date 2023/09/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Growth in computational materials science and initiatives such as the Materials Genome Initiative (MGI) and the European Materials Modelling Council (EMMC) has motivated the development and application of ontologies. A key factor has been increased adoption of the FAIR principles, making research data findable, accessible, interoperable, and reusable (Wilkinson et al. 2016). This paper characterizes semantic interoperability among a subset of materials science ontologies in the MatPortal repository. Background context covers semantic interoperability, ontological commitment, and the materials science ontology landscape. The research focused on MatPortal's two interoperability protocols: LOOM term matching and URI matching. Results report the degree of overlap and demonstrate the different types of ambiguity among ontologies. The discussion considers implications for FAIR and AI, and the conclusion highlight key findings and next steps.