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

Balashanmuga Priyan Rajamohan1,2, Alexander C Harding Bradley1,2, Van D Tran2,3

  • 1Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA.

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Summary
This summary is machine-generated.

We developed a unified framework for creating standardized Materials Data Science ontologies. This framework enhances data interoperability and simplifies term matching for better scientific data management.

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Area of Science:

  • Materials Science
  • Data Science
  • Semantic Web Technologies

Background:

  • Ontologies are increasingly used to standardize scientific data terminologies.
  • Current Materials Science ontologies lack standardization, leading to interoperability issues.
  • Existing frameworks offer limited guidance on developing consistent and reusable ontologies.

Purpose of the Study:

  • To propose a unified, automated framework (MDS-Onto) for developing interoperable and modular ontologies in Materials Data Science.
  • To establish a semantic bridge to the Basic Formal Ontology (BFO) to simplify ontology term matching.
  • To provide recommendations on ontology positioning, knowledge representation language, and publication for enhanced findability and interoperability.

Main Methods:

  • Developed the MDS-Onto framework with two core components: FAIRmaterials for ontology creation and FAIRLinked for FAIR data creation.
  • Established recommendations for semantic web integration, recommended knowledge representation languages, and online publication strategies.
  • Created exemplar domain ontologies for Synchrotron X-Ray Diffraction and Photovoltaics using the FAIRmaterials package.

Main Results:

  • The MDS-Onto framework offers a standardized approach to Materials Data Science ontology development.
  • FAIRmaterials facilitates the creation of bilingual ontologies, improving accessibility and usability.
  • The exemplar ontologies demonstrate the framework's practical application and potential for enhancing data interoperability.

Conclusions:

  • The proposed framework addresses the need for standardized, interoperable, and modular ontologies in Materials Data Science.
  • Implementing MDS-Onto, FAIRmaterials, and FAIRLinked can significantly improve the findability, accessibility, interoperability, and reusability (FAIR) of materials data.
  • This work provides a foundation for more consistent and collaborative ontology development within the materials science community.