Analytics of collaborations and performance of citizen science teams during the GEAR cycle 2 of the Crowd4SDG project.

This data frame is part of the deliverable 4.2 of the Crowd4SDG project.

It contains the measured analytics of citizen collaborations using new metrics/descriptors developed during the first year of the Crowd4SDG project. 

The goal of the Crowd4SDG project is to research the extent to which Citizen Science (CS) can provide an essential source of non-traditional data for tracking progress towards the SDGs, as well as the ability of CS to generate social innovations that enable such progress. In the Crowd4SDG project, the Work Package 4 aims to develop and monitor new metrics and develop statistical models of team engagement and collaboration that contribute to the many-faceted outcomes of the citizen science projects developed within the Crowd4SDG consortium over the 3-years course of the project. Here, we share a dataframe of features collected during the GEAR cycle 2 pertaining to team composition, activity, performance and interaction dynamics. In particular, we leveraged the CoSo platform for collecting self-reported data on collaborations and task allocation structure of participating teams, as well as Slack data for measuring communication networks. The related findings are presented in the deliverable 4.4 of the Crowd4SDG project and serve as a basis for i) exhibiting the potential of using digital traces to derive measures related to team process, ii) highlighting perspectives for monitoring metrics in the next GEAR cycle.