Have you ever experienced befuddlement when you dust off a data analysis that you ran six months ago? Ever gritted your teeth when your collaborator invalidates all your hard work by telling you that the data set you were working on had “a few minor changes”? Or panicked when someone running a big meta-analysis asks you to share your data?
If any of these experiences rings true to you, then you need to adopt the philosophy of reproducible research.
Reproducible research refers to methods and tools developed by large software development teams but which can help you keep a sense of order in your data, analysis programs, and results.