Links that may be useful

[olexandr-konovalov]

A collection of potentially useful links:

• Template for publishing reproducible experiments in Python Jupyter notebooks runnable on Binder and Azure Notebooks: https://github.com/rse-standrewscs/python-binder-template

• Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks https://doi.org/10.1371/journal.pcbi.1007007

• Preprint on reproducible research: "Case Studies and Challenges in Reproducibility in the Computational Sciences" https://arxiv.org/abs/1408.2123

• Credit for reproducible research: https://the-turing-way.netlify.app/credit/credit.html

• Discussion on R-words: Reproducibility vs replicability https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5778115/

• Open Science Framework: https://osf.io/

• Behaviour Change for Open Science: https://psyarxiv.com/tch4w/

• Rescience (journal to publish replications): http://rescience.github.io/

• Famous Excel error:

  • https://www.bbc.co.uk/news/magazine-22223190
  • Reinhart-Rogoff: https://en.wikipedia.org/wiki/Growth_in_a_Time_of_Debt
  • https://theconversation.com/the-reinhart-rogoff-error-or-how-not-to-excel-at-economics-13646: "The most serious was that, in their Excel spreadsheet, Reinhart and Rogoff had not selected the entire row when averaging growth figures: they omitted data from Australia, Austria, Belgium, Canada and Denmark. In other words, they had accidentally only included 15 of the 20 countries under analysis in their key calculation."

[olexandr-konovalov]

Also, a number of blog posts on the Software Sustainability Institute website: https://www.software.ac.uk/ssisearch?search_api_fulltext_1=reproducibility