Collaborate and analyse

Research is often conducted in teams, and these can operate nationally or even internationally. Establishing (and documenting) appropriate data management processes before project start is key. This includes setting up a data management resources library, defining roles and responsibilities, and tracking data carefully. In collaborative projects, file sharing takes a front seat and complicates how you deal with active data storage, too.

Assigning roles and responsibilities appropriately during a project is also important. This includes, e.g. putting someone in charge of a dataset and its maintenance. They will have to document the methods of analysis and the conventions used, so as to enable collaborators to reuse the data smoothly.

We believe that this lifecycle step makes our journey through research data management clearer. You can now start seeing how good data management planning leads to successful collaborations and analysis: the more you think about research data management initially, the smoother your pathway to impact will be.