Almost all research, whether it’s conducted in the field or in a lab, includes a substantial amount of work that’s done on the computer. This includes data processing, statistical analyses, data visualization and presentation, and production of research outputs (e.g. publications). Some research is of course exclusively conducted on computers. The bottom line is that computer-based work forms a key and substantive part of all research workflows.
Given that this work is done on computers (which are entirely controllable), it should be able to be reproduced exactly. This is known as computational reproducibility: an independent researcher should be able to access all data and scripts from a study, run those scripts, and get exactly the same outputs and results as reported in the original study.
In this tutorial you’ll start gaining relevant experience and skills by producing a reproducible lab report.
A workflow refers to the the steps you take when conducting your day-to-day work - say, on a term project, for example. Having a well-designed workflow improves efficiency, and when done right, reproducibility. It includes, for example, how you create, access, and manage files on your computer (or in the cloud).
Following best practices for naming and organizing your files and directories on your computer will help ensure that you can spend more time doing the important work, and less time fiddling and trying to remember what you did and where you saved your work. It will also help your future self, when labs and assignments in upper year courses request that you use R and R Markdown for analyses and reports.