| About this Abstract |
| Meeting |
TMS Specialty Congress 2025
|
| Symposium
|
Joint Sessions of AIM, ICME, & 3DMS
|
| Presentation Title |
Modular and Interoperable Materials Data Science Ontology (MDS-Onto) for Knowledge Graphs and Semantic Reasoning |
| Author(s) |
Erika I. Barcelos, Balashanmuga Priyan Rajamohan, Quynh D. Tran, Van D. Tran, Kai Zheng, Nathaniel Hahn, Hayden Caldwell, Ozan Dernek, Pawan K. Tripathi, Yinghui Wu, Laura S. Bruckman, Roger H. French |
| On-Site Speaker (Planned) |
Erika I. Barcelos |
| Abstract Scope |
Research data and metadata often have non-standard terms and formats. The terms and concepts are frequently subjective and adopted based on local experience and choices of research teams, and this poses major challenges for data reusability and research reproducibility. Ontologies represent a critical component toward FAIRification of data, achieving semantic interoperability and reducing barriers for data sharing, usability, analysis and modeling. In addition, they serve as the backbone of knowledge graphs, where data and results, standardized by ontologies enabling semantic reasoning and inferences. In this work we introduce the Materials Data Science Ontology(MDS-Onto), a low-level, interoperable, ontology built on a modular framework that simplifies ontology alignment by mapping MDS-Onto concepts to midlevel ontologies such as the Platform Material Digital Core Ontology (PMDco) and the Quantities, Units, Dimensions and Types (QUDT) Ontology terms. It encompasses over 20 domains in materials data science and provides a common foundation for semantic triples of the Resource Description Framework (RDF) data model. These RDF triples, or RDF statements, when stored in a graph database such as Ontotext’s GraphDB, form knowledge graphs, over which people and machines can perform semantic reasoning using SPARQL queries. Knowledge graphs enable machines to reason over ing enables can span. These knowledge graphs enable machines to reason over billions of RDF statements, representing for materials data science the ability to reason over historical data and results at scale. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |