Conservation and ecology research underpin management decisions that directly impact biodiversity. Yet, growing concern about the irreproducibility of many published results means the credibility of research and the reliability of decisions they inform may be questioned. Researchers can overcome these concerns by making their research reproducible. The aim of this workshop is to teach ecology researchers using the language R best practices for making their research computationally reproducible – meaning the ability to rerun an analysis and reproduce the same results. Making your analyses more reproducible has many benefits, including fewer mistakes, less duplication, more interpretable analyses, and better collaboration. Ultimately, reproducible code is likely to be more organised, more easily shared, and to support more robust and reliable research.
This one-day session will introduce our top strategies for increasing the reproducibility of your work in R. The workshop is best suited for those who are already using R and looking to upskill their coding techniques.
