Public-private funding models in open source software development: A case study on scikit-learn

Governments are increasingly funding open source software (OSS) development to support software security, digital sovereignty, and national competitiveness in science and innovation, amongst others. However, little is known about how OSS developers evaluate the relative benefits and drawbacks of emergent governmental funding for OSS. This paper explores this question through a case study on scikit-learn, a popular Python library for machine learning, which has been funded by public research grants, commercial sponsorship, micro-donations, and a 32 million euro grant announced in France's artificial intelligence strategy. Through 25 interviews with scikit-learn's maintainers and funders, this study makes two key contributions to research and practice. First, it contributes novel empirical findings on the effective design and implementation of a public-private funding model in an OSS project, as well as how the maintainers of scikit-learn have designed and employed governance protocols to balance the diverse interests of their funders and to safeguard their community ethos. Second, it offers practical lessons on funding in community-led OSS projects and makes recommendations to practitioners. The paper concludes with a discussion of the key recommendations.