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I look at this whole idea another way: if your results are so fragile that they need a docker container (with all the caveats others are mentioning about versio

I look at this whole idea another way: if your results are so fragile that they need a docker container (with all the caveats others are mentioning about versions etc), it's not really "reproducible" just because someone can re-run your code. Real reproducibility would come from having discovered some objective fact that shows itself again when similar work is attempted. Reproducibility =/= generality which is a much more important aspect of research.

one-punch 6y ago
While I agree that science should aim for replicability (same result for similar methods on the same scientific question) instead of reproducibility (same methods) [1], it does not hurt to let others to reuse part of your research pipeline. I think we can in fact test and improve replicability if the whole pipeline is published. We should aim for allowing others to change certain parameters or data in the pipeline. That is, the result should be robust with respect to minor changes in the pipeline, which could be more easily tested by others with a published, fully specified pipeline. Referring to my other comment [2], Guix or Nix really shine in allowing others to change part of the pipelines, due to their functional approach to composing components. [1]: https://phys.org/news/2019-05-replicability-science.html https://phys.org/news/2019-05-replicability-science.html [2]: https://news.ycombinator.com/item?id=25866651 https://news.ycombinator.com/item?id=25866651