Data Science for Social Good presents the second in a series of virtual public talks as part of the DSSGx UK programme. In this webinar, the Turing's Dr Kirstie Whitaker joins us to discuss to replicable AI and The Turing Waya handbook for best practice in academic data science, which is currently in development.

As well as leading The Turing Way project, Kirstie is Programme Lead for Tools, Practices and Systems here at the Turing.

About the event

The webinar will take place at 4pm on Friday 24 July. Registration is required. The format will consist of Kirstie's talk followed by a short Q&A session.

Reproducible research is necessary to ensure that scientific work can be trusted. By sharing data, analysis code and the computational environment used to generate the results, researchers can more effectively stand on the shoulders of their peers and colleagues and deliver high quality, trustworthy and verifiable outputs. This requires skills in data management, library sciences, software development, and continuous integration techniques: skills that are not widely taught or expected of academic researchers. Skills that are unreasonable, in fact, to expect in one individual team member. 

The Turing Way is a handbook to support students, their supervisors, funders and journal editors in ensuring that reproducible research is "too easy not to do". It includes training material on version control, analysis testing, collaborating in distributed groups, open and transparent communication skills, and effective management of diverse research projects. The Turing Way is openly developed and any and all questions, comments and recommendations are welcome at our github repository:

In this talk, Kirstie Whitaker, lead developer of The Turing Way, will take you on a whirlwind tour of the chapters that already exist and the directions in which we're continuing to develop. All participants will leave the talk knowing that "Every Little Helps" when making their work reproducible, where to ask for help as they start or continue their open research journey, and how they can contribute to improve The Turing Way for future readers.