Data science and research 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 products. Effective methods of collaboration are crucial to the success and sustainability of research projects and communities.

The Turing Way is an open-source, community-led book project that aims to bring together diverse contributors and collaborators to share resources and practices that make data science reproducible, ethical and inclusive. The project is developed and maintained on an online project repository (https://github.com/alan-turing-institute/the-turing-way) and invites contributions to its 5 guides, including the Guide for Collaboration.

We believe that to make our project widely beneficial and comprehensive we need to collaborate with individuals and groups with diverse skills, backgrounds, lived experiences and domain knowledge. Our community members currently include over 270 contributors on GitHub, as well as thousands of users worldwide who write, read, review, enhance and promote best practices in data science and research (in academia, industry, open communities and public sector).

In this session, we will introduce the Guide for Collaboration to discuss good practices for effective and inclusive collaboration. We will demonstrate The Turing Way guides to prompt discussions on developing inclusive engagement pathways and setting Community-led projects that are open for contributions from people with diverse skills. Through this discussion, we will highlight the importance of designing projects for inclusion 1 and distributed collaboration. Participants will leave this session having discovered skills around reviewing team member’s contributions, remote working, running inclusive events/meetings, defining explicit expectations, and participatory co-creation