The Turing Way: Reproducible, inclusive, collaborative data science - Poster

Poster presented by Esther Plomp for the Research Data Alliance 16th Plenary Meeting. 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 (https://the-turing-way.netlify.com) 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 (https://github.com/alan-turing-institute/the-turing-way).This work was supported by The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "Tools, Practices and Systems" theme within that grant, and by The Alan Turing Institute under the EPSRC grant EP/N510129/1