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 313db0b). Appendices-Two comprehensive appendices that review the longevity of existing solutions are available as supplementary "Web extras," which are available in the IEEE Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/MCSE.2021.3072860. Reproducibility-All products available in zenodo.4913277, the Git history of this paper's source is at git.maneage.org/paper-concept.git, which is also archived in Software Heritage Heritage: swh:1:dir:33fea87068c1612daf011f161b97787b9a0df39f. Clicking on the SWHIDs in the digital format will provide more "context" for same content.