Reproducibility

I already made a case for why reproducible research is important. So now lets define the term and see if we can’t come up with a set of criteria that encompasses its meaning. Reproducibility …

… [is a] set of procedures that permit the reader of a paper to see the entire processing trail from the raw data and code to figures and tables ¹.

Or according to the U.S. National Science Foundation (NSF)…

… refers to the ability of a researcher to duplicate the results of a prior study using the same materials as were used by the original investigator ².

These are straightforward, yet broad, definitions. For example, we could apply these definitions to laboratoratoy techniques, field sampling methods, and so on. Rather than trying to cover all forms of reproducible research, lets focus on steps we can take to make the data portion of our science reproducible. Basically, we are ignoring how we got the data and instead focusing on what we did with the data. Some of the material presented here has been covered in previous lessons but I would like to capture all of these ideas in one place; so please pardon the repetition. These are best practices recommendations and it is up to you whether or not to implement them.

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