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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.
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.
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.
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