Characterizing Semantic Ambiguity of the Materials Science Ontologies

TL;DR

This paper analyzes semantic ambiguity in materials science ontologies within the MatPortal repository, highlighting challenges for interoperability and implications for FAIR principles and AI applications.

Contribution

It provides a detailed characterization of semantic ambiguity and overlap among materials science ontologies, informing future ontology development and interoperability efforts.

Findings

Significant overlap exists among ontologies, but ambiguity varies.

Different types of semantic ambiguity impact interoperability.

Results inform strategies to improve ontology alignment and reuse.

Abstract

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.