| About this Abstract |
| Meeting |
TMS Specialty Congress 2025
|
| Symposium
|
8th World Congress on Integrated Computational Materials Engineering (ICME 2025)
|
| Presentation Title |
Customizing the NIMS RDE System for Optimal Data Management |
| Author(s) |
Takuya Kadohira, Jun Fujima, Hideki Yoshikawa, Satoshi MInamoto |
| On-Site Speaker (Planned) |
Takuya Kadohira |
| Abstract Scope |
The preparation of FAIR data is crucial in AI research. While basic research on materials has successfully applied FAIR principles to simulation data, applying these principles to experimental data is challenging due to quality differences; the simulation conditions are fully known, unlike the experimental ones. The NIMS RDE system, a part of the Materials Data Platform, addresses FAIRness at data submission through input and ETL functions that are customizable for different experiments. This flexibility theoretically supports the management of experimental results as FAIR data, enhancing reproducibility and reducing redundant experiments. However, the extensive customization flexibility can be challenging, as it requires identifying how much customization is truly necessary and finding ways to minimize the effort involved in such customization. Balancing this challenge involves developing a data model that identifies essential FAIRness aspects for data utilization and provides a framework for function customization. |
| Proceedings Inclusion? |
Undecided |