Abstract
Researchers across nearly every discipline seek to leverage ontologies for knowledge discovery and computational tasks; yet, the number of machine readable materials science ontologies is limited. The work presented in this paper explores the Processing, Structure, Properties and Performance (PSPP) framework for accelerating the development of materials science ontologies. We pursue a case study framed by the creation of an Aerogel ontology and a Battery Cathode ontology and demonstrate the Hel** Interdisciplinary Vocabulary Engineer for Materials Science (HIVE4MAT) as a proof of concept showing PSPP relationships. The paper includes background context covering materials science, the PSPP framework, and faceted analysis for ontologies. We report our research objectives, methods, research procedures, and results. The findings indicate that the PSPP framework offers a rubric that may help guide and potentially accelerate ontology development.
This work is supported by NSF-OAC 2118201, NSF-IIS 1815256.
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This work is supported by NSF-OAC 2118201, NSF-IIS 1815256.
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Greenberg, J. et al. (2023). Materials Science Ontology Design with an Analytico-Synthetic Facet Analysis Framework. In: Garoufallou, E., Vlachidis, A. (eds) Metadata and Semantic Research. MTSR 2022. Communications in Computer and Information Science, vol 1789. Springer, Cham. https://doi.org/10.1007/978-3-031-39141-5_18
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