CAREER: A FAIR-Aligned Ontology-Driven Cyberinfrastructure for Multi-Scale Materials Discovery and Design

This project aims to transform the materials innovation pipeline by developing a FAIR-aligned (Findable, Accessible, Interoperable, and Reusable) cyberinfrastructure that combines ontology-driven knowledge representation and physics-informed AI to enable integrated, intelligent, and automated materials discovery and design. The proposed research will build an open and extensible framework that integrates heterogeneous datasets, simulation platforms, and domain knowledge, supporting both machine learning and rule-based reasoning over materials systems. This project introduces a foundational, ontology-driven cyberinfrastructure that advances semantic interoperability, automated reasoning, and data integration in materials science. By developing a modular and extensible ontology tailored to multi-scale materials data—including composition, processing, structure, and properties—it establishes a formal framework for organizing and inferring materials knowledge. The infrastructure leverages semantic web technologies (RDF, OWL, JSON-LD, SPARQL) to construct a FAIR-aligned knowledge graph that unifies fragmented datasets across institutions and domains. Integrating explainable AI techniques—including rule-based inference, description logic, and physics-informed machine learning—enables transparent, logic-guided decision-making for material design and discovery. This project will create an open, reusable, and FAIR-aligned cyberinfrastructure to advance multi-scale materials discovery. It will release software tools, ontologies, and curated datasets under open-source licenses, fostering collaboration across materials science, AI, and biomedical fields. The project emphasizes workforce development by training students in semantic web, data science, and materials informatics, with support from Amazon AWS for scalable computing and reproducible research. Educational outreach will engage local and Native students through culturally relevant STEM modules co-developed with Northeastern State University and Norman Public Schools (a school district in Oklahoma). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2544484 | Program: 01003031DB NSF RESEARCH & RELATED ACTIVIT,01002627DB NSF RESEARCH & RELATED ACTIVIT,01002930DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Byeong-Min Roh | Institution: University of Oklahoma Norman Campus, NORMAN, OK | Award Amount: $300,000 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2544484 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2544484.html