Artifacts longevity/sustainability

Tier 1 · Available - Bronze recommended

The package is meant to stay usable after publication: the authors commit to preserving data and code for a stated period and keep them runnable as software and dependencies change, for example by maintaining the code or rebuilding the environment.

Rating

Met

The package is deposited in a repository that commits to preserving it for a stated period (e.g. at least five years after publication), AND the README states how the code will stay runnable over time, e.g. an archived computing environment (container image), a maintenance plan, or reliance on free/open-source software whose versions remain obtainable.

Partially met

The package is preserved (e.g. in a trusted repository), but nothing is done to keep it runnable as software changes (no archived environment, no maintenance plan, reliance on software versions that may disappear); or a maintenance plan exists but the files sit in a place without a preservation commitment (e.g. a personal GitHub account or website only).

Not met

No preservation commitment and no provision for future executability, e.g. files only on a personal website or ‘available upon request’.

Based on: #3 persistence/longevity, #42 >=5-year commitment, #44 ‘active maintenance’ plan, #38 rebuild containers regularly, #139 FOSS, #143 deprecated library versions.

Not applicable

Never.

Prerequisites

Check order: — (no prerequisite links coded)

Builds on

No core prerequisites.

Prerequisite for

No criterion builds on this one.

In the corpus

Sources	Injunctive	Descriptive	Tacit	Automatable	Manual check	Automation unclear	LLM sources
9	100%	0%	0%	0%	0%	100%	0

Text evidence (9 quotes)

Show quotes

#3 Reproducing statistical results · injunctive

“Curation: Where are code and data available? With what expected persistence and longevity? Is there a way to access future updates, for example, a version-control repository of the code base?” (p. 11)

#38 Ten simple rules for writing dockerfiles for reproducible data science · injunctive

“if you use a container daily, it is good practice to rebuild that container every 1 or 2 weeks; this helps identify breaking changes early and prevents multiple issues compounding on each other” (p. 20)

#42 AEA data and code availability policy · injunctive

“authors must commit to preserving data and code for a period of no less than five years following publication” (p. 818)

#44 Active maintenance: a proposal for the long-term computational reproducibility of scientific results · injunctive

“we propose that researchers dedicated to computational reproducibility should have a plan in place for ‘active maintenance’ of their analysis code” (Abstract/p. 462)

#48 Challenges of curating for reproducible and FAIR research output · injunctive

“Uncertainty about whether the reproducibility package will still work in the future” (p.21)

#54 WORCS: a workflow for open reproducible code in science · injunctive

“it is important to consider that all solutions have a limited shelf life… all code requires some maintenance if you want to reproduce it in the future” (p. 34)

#119 “Works on my machine”: a case study of replicability challenges inComputational humanities research · injunctive

“these projects must necessarily concern themselves with the question of sustainability, as software, and software libraries especially, may change over time and the stability of their interfaces or functionality is typically not guaranteed” (p.143)

#139 PRIMAD-LID: a developed framework for computational reproducibility · injunctive

Akhlaghi et al.’s eight criteria for longevity include “free/open-source software (FOSS)” (p. 13) and “Longevity emerged from recognising that experiments must remain reproducible well beyond their initial creation, tackling challenges such as software decay, deprecated dependencies, or lost data.” (p. 9)

#143 What is Computational Reproducibility? · injunctive

The use of external libraries and tools, which may update or deprecate over time, can also hinder reproducibility. If the specific version of a library used in the original study is no longer available, reproducing the exact computational environment becomes challenging. (p. 5).