Scientific data analysis pipelines commonly use high-level technologies that were popular when they were created, only providing an immediate solution which is unlikely to be sustainable or reproducible in the future. We have implemented "Maneage" (Managing data Lineage), a solution which stores the project in machine-actionable and human-readable plain-text, enabling version-control, cheap archiving, automatic parsing to extract data provenance, and peer-reviewable verification. We show that requiring longevity and reproducibility from scientific data analysis pipeline is realistic, without sacrificing immediate or short-term reproducibility and discuss the benefits of the criteria for scientific progress. For more, see Akhlaghi et al. (arXiv:2006.03018).