The Turing Way is everything you could ask for in a guide for reproducible science. It’s open source. It’s community-driven. It’s inclusive. And it’s a global collaboration of people working at research institutes and universities, government departments, and industry. Martina Vilas will share her experience as a core contributor and maintainer of The Turing Way, where she provides infrastructure support for the project.
A bit about Martina Vilas
Martina Vilas is a PhD student at the Neuroscience Department of the Max-Planck-Institute AE in Frankfurt, Germany. For the past year she has been a core contributor to the Turing Way project: an open source community-driven guide to reproducible, ethical, inclusive and collaborative data science. Her current work focuses on understanding how the brain represents abstract knowledge, and how it uses this type of information to make predictions about future events. More broadly, she’s focused in the development of computational methods that probe the format and structure of neural representations. She loves programming, and believes that research software development is an integral part of science. In her free time Martina Vilas likes contributing to open-source projects related to data science, and mentoring first-time contributors that belong to underrepresented groups in technology.
There’s a bit more about Martina’s talk in Brainhack Donostia in her abstract below!
Reproducible research is necessary to ensure that our scientific output can be independently verified and built upon in future work. But conducting reproducible research requires software development skills that are not usually taught or expected of academic researchers. The Turing Way is an open-source, community-led handbook that supports this knowledge (among others) in an accessible and comprehensible form for everyone. Its moonshot goal is to make reproducible research “too easy not to do”. This talk will guide you through the best practices in computational reproducibility outlined by The Turing Way. I will show you how to version control your code, how to improve its quality, how to test its functionality, and how to make it open-source, using Python as an example. I will also demonstrate how to capture and share your computational environment, and how to incorporate continuous integration techniques into your coding workflow.