Materials Data Science Ontology(MDS-Onto): Unifying Domain Knowledge in Materials and Applied Data Science

Authors

Balashanmuga Priyan Rajamohan, Case Western Reserve University
Alexander C. Harding Bradley, Case Western Reserve University
Van D. Tran, Case Western Reserve UniversityFollow
Jonathan E. Gordon, Case Western Reserve UniversityFollow
Hayden W. Caldwell, Case Western Reserve UniversityFollow
Redad Mehdi, Case Western Reserve UniversityFollow
Gabriel Ponon, Case Western Reserve UniversityFollow
Quynh D. Tran, Case Western Reserve UniversityFollow
Ozan Dernek, Case Western Reserve UniversityFollow
Benjamin G. Pierce, Case Western Reserve UniversityFollow
Raymond Wieser, Case Western Reserve University
Weiqi Yue, Case Western Reserve UniversityFollow
Kiefer Lin, Case Western Reserve UniversityFollow
Jiana Kambo, Case Western Reserve UniversityFollow
Arafath Nihar, Case Western Reserve UniversityFollow
Pawan K. Tripathi, Case Western Reserve UniversityFollow
Yinghui Wu, Case Western Reserve UniversityFollow
Laura S. Bruckman, Case Western Reserve UniversityFollow
Erika I. Barcelos, Case Western Reserve UniversityFollow
Roger H. FrenchFollow

Author ORCID Identifier

Balashanmuga Priyan Rajamohan

Jonathan E. Gordon

Hayden W. Caldwell

Gabriel Ponon

Quynh D .Tran

Ozan Dernek

Pawan K. Tripathi

Erika I. Barcelos

Roger H. French

Document Type

Article

Publication Date

4-15-2025

Abstract

Ontologies have gained popularity in the scientific community as a way to standardize terminologies in organizations’ data. Although certain cohorts have created frameworks with rules and guidelines on creating ontologies, there exist significant variations in how Materials Science ontologies are currently developed. We seek to provide guidance in the form of a unified automated framework for developing interoperable and modular ontologies for Materials Data Science that simplifies the ontology terms matching by establishing a semantic bridge up to the Basic Formal Ontology(BFO). This framework provides key recommendations on how ontologies should be positioned within the semantic web, what knowledge representation language is recommended, and where ontologies should be published online to boost their findability and interoperability. Two fundamental components of the MDS-Onto framework are the bilingual package called FAIRmaterials for ontology creation and FAIRLinked, for FAIR data creation. To showcase the practical capabilities of FAIRmaterials, we present two exemplar domain ontologies of MDS-Onto: Synchrotron X-Ray Diffraction and Photovoltaics.

Keywords

research data, scientific community

Language

English

Publication Title

Scientific Data

Grant

DE-NA0004104

Rights

© The Author(s). This is an Open Access work distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Recommended Citation

Rajamohan, B.P., Bradley, A.C.H., Tran, V.D. et al. Materials Data Science Ontology(MDS-Onto): Unifying Domain Knowledge in Materials and Applied Data Science. Sci Data 12, 628 (2025). https://doi.org/10.1038/s41597-025-04938-5