Reconstructing Open Source Software Ecosystems: Finding Structure in Digital Traces

We report on the computational reconstruction of 273 open source software ecosystems, consisting of 41,388 artifacts and couplings between them, extracted from digital traces of 34.4 million software artifacts. We argue that digital traces are a new kind of data source, and propose ‘exploratory data loops’ to exploit the benefits of digital trace data in early stages of a research program. We apply this schema to systematically assess data quality, inform sample selection, and detect patterns. Empirically, we show that highly distributed networks are unlikely to follow a hierarchically modular structure, despite popular belief. As is shown visually with two examples, very distinct structures can emerge from autonomous behavior. The results indicate that different, yet similarly effective, strategies may exist to organize for distributed innovation in digital ecosystems. The paper is concluded by outlining how follow-up work will harness the reconstructed ecosystems for detecting behavioral patterns in distributed networks.

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