Towards Long-term and Archivable Reproducibility

Mohammad Akhlaghi; Raul Infante-Sainz; Boudewijn Roukema; Mohammadreza Khellat; David Valls-Gabaud; Roberto Baena Galle
Referencia bibliográfica

Computing in Science & Engineering

Fecha de publicación:
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 paper is itself written with Maneage (project commit 925091e).