Reproducible data science: How hard can it be?

The ability to reproduce the research that other scientists have done to see whether the same results are obtained (or the same conclusions are reached) is an integral part of the scientific process, but are we doing it right and how difficult is it to do? This week, Ed is joined by Dr Kirstie Whittaker and Dr Sarah Gibson for a discussion about the reproducibility of scientific research, why this is such an important topic and what The Alan Turing Institute is doing to promote best practices in reproducible data science. Kirstie is the Programme Lead for Tools, Practices and Systems at The Alan Turing Institute and Sarah is a Research Software Engineer at the Institute who is also a fellow of the Software Sustainability Institute. Check out some of the projects mentioned in the interview such as The Turing Way at https://the-turing-way.netlify.app/ and Binder at https://mybinder.org/