The widespread standard in academia has been, and still is, to work individually for the majority of one’s time. However, if done well, working in a team can be more fun, more productive, and more effective. There are both benefits and downsides of working in teams, and the key is to work together in such a way that the advantages outweigh the disadvantages.

An illustration of 2 people who are working together and discussing a data chart.

Fig. 90 Making teamwork effective. Royalty free image from Many Pixels

Team Framework

There are many popular frameworks that provide useful guidance on how to best work in teams. Popular examples are Kanban, and Scrum, which are both practical implementations of the Agile Manifesto. There are many particularities to working in a data science setting that will make application of these frameworks challenging.

Lessons on Teamwork for Research Software Development

Teamwork for Research Software Development is a standalone tutorial with lessons on teamwork, agile and scrum framework, project board such as kanban, challenges and practical recommendations. To ensure that all team members have a shared understanding of ways of working, this can be delivered by any researcher leading a team with an understanding of these topics.

Developed by the researchers at Netherlands eScience Center, this tutorial is geared primarily towards people that create research software in an academic setting. However, teamwork practices discussed here are generally useful for anyone trying to work on a team in scientific projects.

Further Recommendations

The The Turing Way guide for Collaboration, we have also provided useful resources for facilitating remote collaboration. Especially, check out recommendations for organising, list of tools and managing remote teams.

Atlassian has a great collection of blogs for nice ideas and tips on teamwork. See for example 7 essential teamwork skills, or How to run effective meetings and thrive.