Publication: Understanding Distributed Cooperative Work through Data Traces

Emerging from the International Future of Work Consortium, researchers from Utrecht University, the University of Seville, and the University of Copenhagen joined forces on a study into how distributed research teams collaborate in practice. The resulting paper: 'Understanding Distributed Cooperative Work through Data Traces'. 

The study followed a geographically distributed scientific team of four researchers (based in Spain and the Netherlands) over the course of one year, tracking their collaborative activities across tools like Overleaf, GitHub, WhatsApp, email, and calendar. Rather than relying on observations or interviews alone, the researchers introduced a novel method called Data Traces: automatically collected, time-stamped records of interactions with digital artifacts and team members, drawn from multiple sources simultaneously.

The analysis produced three key findings:

  • Temporal rhythms: Data Traces reveal clear patterns in how collaboration intensifies and shifts in character around deadlines, with different tools becoming dominant at different phases of the work.
  • Proximity matters: Whether team members were working collocated, distributed, or in a hybrid setup significantly shaped which tools were used and how. Some results were counterintuitive: for example, messaging traffic was high even when the team was physically together.
  • Invisible work: Not everything shows up in the data. Individual work styles, informal feedback, and coordination that happens off-platform remain invisible, meaning Data Traces always offer only a partial picture.

The study argues that Data Traces have real potential as a built-in feature of cooperative technologies, helping distributed teams reflect on their own collaboration patterns and build shared understanding over time.

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