Guide for Collaboration

This guide covers topics related to effective and inclusive collaboration.

Data science is defined by its interdisciplinarity. Our work can only reach its highest potential if there are diverse teams of people involved in designing and delivering the research or product.

An iceberg's tip is labelled with the project related technical terms, and a few divers are exploring a huge part of iceberg underwater which are labelled with community oriented collaborative terms

Fig. 61 There is more to collaboration than we see. The Turing Way project illustration by Scriberia. Used under a CC-BY 4.0 licence. DOI: 10.5281/zenodo.3332807.

There are many different skills required to work well in groups with a wide range of expertise. In this guide, we welcome contributions in developing guidance on following (but not limited to) topics:

  • Designing a project that welcomes contributions

  • Distributed collaboration on GitHub

  • Reviewing team member’s contributions

  • Remote working

  • Running an inclusive event

  • Chairing a meeting

  • Defining explicit expectations

  • Participatory co-creation

Check out our contributing guidelines to get involved.