Reproducible Research with Python

Scientific Computing Research


Compilation of ideas for reproducible research

Still under construction…

What do we mean by reproducible research

The scientific methodology is mostly about studies than can, potentially, be reproduced. Given the same conditions, the results could be reproduced again. This aspect is something that usually we try to teach to our students when laboratory experiments are conducted or when the history of science is described. As nowadays the studies are complex, with a combination of datasets, code and data analysis, to be able to made our research reproducible, the scientictis aims to create a reproducible workflow which demostrates the correctness of the results when needed but also track all the process and begin again the research at any possible point. So in general there are two main reasons to implement reproducible research tools on your research workflow,

  • Be able to prove that your results are correctly obtained
  • Be able to implement on other research projects the methods, datasets and workflow.

This is clearly described in this blog

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