About this Abstract |
Meeting |
2025 TMS Annual Meeting & Exhibition
|
Symposium
|
Algorithms Development in Materials Science and Engineering
|
Presentation Title |
Research Data Management for Reference Data in Materials Science and Engineering Exemplified for Creep Data of Ni-Base Superalloys |
Author(s) |
Jürgen Olbricht, Luis A. Įvila Calderón, Yusra Shakeel, Angelika Gedsun, Mariano Forti, Sirieam Hunke, Ying Han, Thomas Hammerschmidt, Rossella Aversa, Miroslaw Chmielowski, Rainer Stotzka, Erik Bitzek, Tilmann Hickel, Birgit Skrotzki |
On-Site Speaker (Planned) |
Jürgen Olbricht |
Abstract Scope |
In this presentation, we introduce a methodological framework for the generation, distribution, and utilization of high-quality reference datasets, using creep testing of Ni-base superalloys as an example. The proposed framework covers multiple aspects, from the data generation, documentation, handling, storage, and sharing, to the data search and discovery, retrieval, and usage. The generation of experimental or simulated reference datasets must be accompanied by comprehensive documentation, e.g., of the material provenance, original and processed data with details on the data processing procedures, the software and hardware used, and software-specific input parameters to allow data users to independently assess the data quality prior to any usage. The presented framework can serve as a guideline to generally improve research data management practices within the materials science and engineering (MSE) community. Its individual elements ensure the functionality and usability of the data and, thus, the adherence to the FAIR principles. |
Proceedings Inclusion? |
Planned: |