| About this Abstract |
| Meeting |
TMS Specialty Congress 2025
|
| Symposium
|
Joint Sessions of AIM, ICME, & 3DMS
|
| Presentation Title |
Ontology-Based Materials Data Management for High Temperature Alloy Oxidation Data |
| Author(s) |
Madison Wenzlick, William Trehern, Leebyn Chong, Casey Carney, Michael Gao, Richard Oleksak, Wissam Saidi |
| On-Site Speaker (Planned) |
Madison Wenzlick |
| Abstract Scope |
High quality, digitally structured data is essential for creating reliable data-driven models. However, managing materials datasets presents several challenges including variable data types, formats, and relationships. Ontology-based data management is a re-emerging tool for structuring and defining materials data. In this work, an ontology was generated and applied to high temperature alloy oxidation data collected from both open-source literature as well as in-house testing. Metadata and data attributes from each study were standardized and translated into the ontology structure. The oxidation ontology further integrates with an existing mid-level materials data ontology to support the curation of additional materials information. This framework aids in encoding the complex relationships between the data in both a machine-readable and human-readable manner, enabling the ongoing interpretability of the dataset. The ontology can further be leveraged to support the flow of data from laboratory to database and provides a resource for advanced data-driven modeling and analysis. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |