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arXiv · 2006.03018

Toward Long-Term and Archivable Reproducibility

Mohammad Akhlaghi·Raúl Infante-Sainz·Boudewijn F. Roukema·Mohammadreza Khellat·David Valls-Gabaud·Roberto Baena-Gallé
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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).

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Mohammad Akhlaghi, Raúl Infante-Sainz, Boudewijn F. Roukema, Mohammadreza Khellat, David Valls-Gabaud, Roberto Baena-Gallé. 2020-06-04. Toward Long-Term and Archivable Reproducibility. https://doi.org/10.1109/mcse.2021.3072860

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