Provenance information are essential for the traceability of scientific studies or experiments and thus crucial for ensuring the credibility and reproducibility of research findings. This paper discusses a comprehensive provenance framework combining the two types 1. workflow provenance, and 2. data provenance as well as their dimensions and granularity, which enables the answering of W7+1 provenance questions. We demonstrate the applicability by employing a biomedical research use case, that can be easily transferred into other scientific fields. An integration of these concepts into a unified framework enables credibility and reproducibility of the research findings.
@article{arxiv.2504.11278,
title = {Towards dimensions and granularity in a unified workflow and data provenance framework},
author = {Tanja Auge and Sascha Genehr and Meike Klettke and and Frank Krüger and Max Schröder},
journal= {arXiv preprint arXiv:2504.11278},
year = {2025}
}