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Open Source Endowment Fund Distribution Model

This is the work-in-progress fund distribution model for the Open Source Endowment.

Work is currently happening in this repo and the following places:

High-level Overview

Principles

  1. We aim to build a transparent, measurable, and verifiable model that can be iteratively improved by the open-source community and approved by a majority of active OSE donors.

  2. It will never be a perfect model, because (1) open-source consumption cannot be measured with 100% precision, and (2) there is no ideal consensus on how to prioritize OSS grants.

Ecosystems

We aim to focus our support on the core of open-source ecosystems — roughly the ~1% of packages that account for 99% of downloads and dependencies. Our model is a data-driven approximation of global open-source supply chain usage, designed to surface its most critical yet underfunded components.

It is important to trace dependencies across ecosystem boundaries, not just within them. For instance, Pandas [Python] depends on NumPy [Python], which depends on OpenBLAS [C] (details). This cross-ecosystem view naturally elevates low-level infrastructure libraries in C/C++, Fortran, and similar languages.

Model Development

Beyond dividing grants between ecosystems, we need to prioritize individual OSS projects within each one. Our goal is to make this process transparent and quantifiable, combining automated scoring with human judgment, especially in the early stages. The model is under active development; its final form will emerge from discussions with OSE donors.

Our approach combines three stages:

Step Goal Implemented Roadmap
Value Find most important packages in ecosystems Download-weighted PageRank for Python (PyPI), Rust (crates), JS/TS (npm), C/C++ (Debian, Homebrew) based on dependency trees, covering 95% downloads in each ecosystem Community nominations, critical software lists, cross-ecosystem dependencies
Eligibility Filter to fundable projects OSS license check (63 OSI-approved) Trademark check (corporate vs community), EOL check
Risk Prioritize risky projects among most valuable Bus factor and Herfindahl--Hirschman index for contributors, complexity metrics (LOC, etc) using scc OpenSSF scorecard, active maintainers, issue activity, GitHub Sponsors

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