This post was originally published on Medium.
Read the full article on MediumThis guide took roots from the ethos of Open Science. In the first post of this three-part series on reproducibility in academic research, I argued that FAIR principles and stable computational environments are essential to a reproducible research. The current post delves into building a practical research workflow that relies on stable computational environments and adheres to FAIR principles.
As a disclaimer, I make a distinction between reproducibility and replicability. For a more precise look at what reproducibility means, Nature has dedicated in 2018 a special archive on the Challenges in Irreproducible Research. For technical aspects, you...