  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).
