This article used an open-source python repository for its analysis. It is well-suited for reproduction as more literature evolves on the intersection of urban planning and climate change. The adapted code is published alongside the article.
This article was meant to be entirely reproducible, with the data and code published alongside the article. It is however not embedded within a container (e.g. Docker). Will it past the reproducibility test tomorrow? next year? I'm curious.
Metadata annotation is key to reproducibility in sequencing experiments. Reproducing this research using the scripts provided will also show the current level of annotation in years since 2015 when the paper was published.
I guess it could be a cool learning experience. The paper is written with knitr, uses a seed, is part of the R package it describes, was openly written using version control (SVN, R-Forge) and is available in an open access journal (@up_jors).
It uses the drake R package that should make reproducibility of R projects much easier (just run make.R and you're done). However, it does depend on very specific package versions, which are provided by the accompanying docker image.