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Phil Diegmann
All work

Data infrastructure, co-author

Trace data pipeline for open-source coordination research

8 open-source projects, 1,169,489 actions, 93 major releases, prepared as time-ordered event sequences. Published in MIS Quarterly (2024).

Context and problem

Open-source projects coordinate through commits, issues and releases. These trace records show what happened, not why. The study needed clean, time-ordered event sequences from many repositories before any model could run.

Approach

  • Pulled commit and release data from the GitHub platform API.
  • Reconciled actors and events so they could be ordered in time.
  • Loaded the result into event sequences for relational event modelling.
  • The research team chose relational event modelling early in the project. I designed, built and ran the data collection and preparation pipeline, and worked closely with the team on interpreting what the results said about developer behaviour.

Result

The study, The Entrainment of Task Allocation and Release Cycles in Open Source Software Development, appeared in MIS Quarterly in 2024. I am fourth of five authors.

Transfer

Major releases are events around which open-source communities self-organise. The same pipeline could be re-run as planned work, once algorithmic contributors such as bots and AI reviewers enter the population.