From Code to Figure: A FAIR-Aligned Data Provenance Chain for Reproducible Simulation Research in Numerical Physics
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915965461069824 |
|---|---|
| author | Uehlein, Markus Held, Tobias Seibel, Christopher Jonda, Lukas G. Rethfeld, Baerbel Weber, Sebastian T. |
| author_facet | Uehlein, Markus Held, Tobias Seibel, Christopher Jonda, Lukas G. Rethfeld, Baerbel Weber, Sebastian T. |
| contents | Computational physics increasingly depends on large simulation datasets generated by software that remains under active development for many years. In such settings, reproducibility requires not only well documented data but also explicit links between code versions, simulation inputs, generated outputs, analysis steps, and published figures. Here, we present an integrated workflow for reproducible and FAIR-aligned simulation research in numerical physics. We describe how version control, code review, automated testing, structured logging, metadata-rich output, and standardized post-processing can be combined to support traceability from software development to publication. The presented concepts demonstrated for one particular simulation framework are broadly applicable to computational physics and other data-intensive areas of scientific computing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_25944 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | From Code to Figure: A FAIR-Aligned Data Provenance Chain for Reproducible Simulation Research in Numerical Physics Uehlein, Markus Held, Tobias Seibel, Christopher Jonda, Lukas G. Rethfeld, Baerbel Weber, Sebastian T. Computational Physics Materials Science Computational physics increasingly depends on large simulation datasets generated by software that remains under active development for many years. In such settings, reproducibility requires not only well documented data but also explicit links between code versions, simulation inputs, generated outputs, analysis steps, and published figures. Here, we present an integrated workflow for reproducible and FAIR-aligned simulation research in numerical physics. We describe how version control, code review, automated testing, structured logging, metadata-rich output, and standardized post-processing can be combined to support traceability from software development to publication. The presented concepts demonstrated for one particular simulation framework are broadly applicable to computational physics and other data-intensive areas of scientific computing. |
| title | From Code to Figure: A FAIR-Aligned Data Provenance Chain for Reproducible Simulation Research in Numerical Physics |
| topic | Computational Physics Materials Science |
| url | https://arxiv.org/abs/2604.25944 |