Toward Long-Term and Archivable Reproducibility
Abstract
Analysis pipelines commonly use high-level technologies that are popular when created, but are unlikely to be readable, executable, or sustainable in the long term. A set of criteria is introduced to address this problem: Completeness (no execution requirement beyond a minimal Unix-like operating system, no administrator privileges, no network connection, and storage primarily in plain text); modular design; minimal complexity; scalability; verifiable inputs and outputs; version control; linking analysis with narrative; and free and open source software. As a proof of concept, we introduce "Maneage" (Managing data lineage), enabling cheap archiving, provenance extraction, and peer verification that has been tested in several research publications. We show that longevity is a realistic requirement that does not sacrifice immediate or short-term reproducibility. The caveats (with proposed solutions) are then discussed and we conclude with the benefits for the various stakeholders. This article is itself a Maneage'd project (project commit 54e4eb2).
Cite
@article{arxiv.2006.03018,
title = {Toward Long-Term and Archivable Reproducibility},
author = {Mohammad Akhlaghi and Raúl Infante-Sainz and Boudewijn F. Roukema and Mohammadreza Khellat and David Valls-Gabaud and Roberto Baena-Gallé},
journal= {arXiv preprint arXiv:2006.03018},
year = {2022}
}
Comments
Published version. The downloadable source (on arXiv) includes the full/automatic reproduction resources (scripts, config files and input data links). Git repository: https://git.maneage.org/paper-concept.git (also on Software Heritage), Zenodo: https://doi.org/10.5281/zenodo.3872247