Reproducible data science: How hard can it be?
Listen now
Description
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/
More Episodes
To what extent can a computer network be actively managed and defended by intelligent autonomous agents? In this episode, Ed talks to Vasilios Mavroudis and Chris Hicks explore this question and more.  Vas and Chris lead the Turing’s AI for Cyber Defence (AICD) research centre which seeks to...
Published 05/03/24
Published 05/03/24
On this episode of The Turing Podcast Bea and Anneca are joined by Lord Chris Holmes, Britain’s most successful Paralympic swimmer and an active member of the House of Lords with a policy focus on digital technology for public good. Connect with Lord Holmes on  Linked In   Explore our regular...
Published 04/16/24