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

A Multifaceted Analysis of Public-Private Funding Dynamics in Open Source Software

The Dual Influence of Public and Private Funding in OSS

The sustainability of open source software (OSS) projects is a complex issue, requiring not just continuous contributions from the developer community but also financial support that can come from various sources including government grants, company sponsorships, and community donations. This study explore the scikit-learn project as a model case to explore how public and private funding sources support OSS development, revealing the nuanced interplay between differing stakeholder interests and the governance mechanisms employed to maintain a project's community ethos.

Research Aims and Methodology

The research aims to understand the roles of public and private funders in the scikit-learn project, a cornerstone Python library in machine learning. It explores how maintainers perceive these funding sources and the lessons that can be gleaned for OSS communities at large. Through 25 semi-structured interviews with scikit-learn maintainers and funders, supplemented by field visits and document analysis, the study unveils the intricacies of a successful public-private funding model.

The Scikit-learn Case: A Revelatory Example of OSS Funding

Scikit-learn stands out as a unique example in the OSS landscape. Supported by a mix of research grants, commercial sponsorship, and a significant grant from the French government, scikit-learn has managed to sustain its development and maintain its status as a critical tool in machine learning. This case study highlights how the project has navigated the benefits and drawbacks of different funding sources to ensure its long-term viability.

Key Findings

• Diverse Funding Benefits: The study finds that the scikit-learn project benefits from a diverse funding model that balances the demands and interests of both public funders like the French government and private companies. This model has allowed scikit-learn to secure financial stability while ensuring the project retains its community-driven ethos.
• Public vs. Private Funding Dynamics: Public funding, particularly from the French government, supports scikit-learn with a long-term perspective focusing on digital sovereignty and national competitiveness. In contrast, private funding from companies often targets specific technical improvements or features. Both funding types bring their particular expectations and influence, which the scikit-learn maintainers navigate using clear governance mechanisms.
• Governance Mechanisms are Key: The scikit-learn project employs several governance protocols to manage funder influence. The establishment of the scikit-learn consortium and its advisory committees enables constructive feedback from commercial sponsors without compromising the project’s independence or community values.

Implications for the Future

• For OSS Communities: The case of scikit-learn illustrates the potential of a diversified funding model in balancing the merits and drawbacks of various funding sources. Governance mechanisms play a crucial role in aligning funders' interests with the community ethos.
• For Companies: The study serves as a reminder that contributing financially or through developer sponsorships can have a significant positive impact on OSS projects.
• For Governments: The findings highlight the importance of supporting not just new innovations but also the maintenance of existing OSS projects to strengthen the digital infrastructure.

Conclusion

The scikit-learn project’s experience offers invaluable insights into the design and implementation of a successful public-private funding model for OSS projects. As governments and companies increasingly recognize the value of OSS, the scikit-learn case underscores the need for funding models that support the sustainability of these projects while respecting their community-driven nature. As the OSS landscape continues to evolve, the lessons from scikit-learn will undoubtedly inform future discussions on OSS funding models.