TY  - JOUR
AU  - Villamar, Jose
AU  - Kelbling, Matthias
AU  - More, Heather
AU  - Denker, Michael
AU  - Tetzlaff, Tom
AU  - Senk, Johanna
AU  - Thober, Stephan
TI  - Metadata practices for simulation workflows
JO  - Scientific data
VL  - 12
SN  - 2052-4436
CY  - London
PB  - Nature Publ. Group
M1  - FZJ-2025-02769
SP  - 942
PY  - 2025
AB  - Computer simulations are an essential pillar of knowledge generation in science. Exploring, understanding, reproducing, and sharing the results of simulations relies on tracking and organizing the metadata describing the numerical experiments. The models used to understand real-world systems, and the computational machinery required to simulate them, are typically complex, and produce large amounts of heterogeneous metadata. Here, we present general practices for acquiring and handling metadata that are agnostic to software and hardware, and highly flexible for the user. These consist of two steps: 1) recording and storing raw metadata, and 2) selecting and structuring metadata. As a proof of concept, we develop the Archivist, a Python tool to help with the second step, and use it to apply our practices to distinct high-performance computing use cases from neuroscience and hydrology. Our practices and the Archivist can readily be applied to existing workflows without the need for substantial restructuring. They support sustainable numerical workflows, fostering replicability, reproducibility, data exploration, and data sharing in simulation-based research.
KW  - Information Retrieval (cs.IR) (Other)
KW  - FOS: Computer and information sciences (Other)
LB  - PUB:(DE-HGF)16
C6  - 40473681
UR  - <Go to ISI:>//WOS:001503948500006
DO  - DOI:10.1038/s41597-025-05126-1
UR  - https://juser.fz-juelich.de/record/1043152
ER  -