Open source public fund experiment - One year review

[coni2k (Serkan Holat)]

Cross-posting here as well; you can also check LinkedIn or Mastodon versions.

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One year ago, I started a small experiment about funding open source software with the following question:

If you have 100 money, how would you distribute this amount to the entire open source ecosystem?

Every month, I choose three open source projects from the Open Collective platform, calculate their score using the Criticality Score tool and distribute an amount based on the results.

My goals are to trigger more in-depth discussions on using public money to finance the open source ecosystem, how an Agile Public Fund should work, and get in touch with our open source entrepreneurs.

Feel free to check my short article for the details:

Open source public fund experiment

For now, here are some quick stats about the last twelve months

Including the test run, I invested $2646 in 39 open-source collectives, with one failed payment: Open source public fund experiment - Google Sheets

The project with the highest score is Zulip, a team chat application, with 0.7932: Zulip - GitHub

The project with the highest estimated annual budget is Qubes OS, a security-oriented operating system with ~$43K, way above the average: QubesOS - GitHub

After the first six months, the average estimated annual budget for all projects was $3667. After a year, that’s now down to $2425. Not even close to an average salary for a single month, let alone a year.

Fifteen projects had no prior donations on Open Collective; I was the first to donate.

The most used license is MIT, with 17 projects.

As a side “marketing” experiment, I used my new Twitter followers to determine the monthly investment amount. I gained ~45 new followers after one year. Considering I’m not super active, that’s not bad, but not a significant boost either. I will now include LinkedIn and Mastodon as well in the following rounds.

I hope to add extra details to the project list and see whether I can improve the Criticality Score. As usual, your feedback is priceless, so don’t hesitate!

[coni2k (Serkan Holat)]

Cross-posting; feel free to check LinkedIn or Mastodon posts.

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Open source public fund experiment - One and a half years update!

Sponsored by

First, the exciting news: I am delighted to share that I started working with the Open Source Collective and Ecosyste.ms teams on this research and the Open Source Collective is the sponsor of the following updates.

Hopefully more to come on this collaboration, so stay tuned!

Updates

I had a chance to improve the data, process, and algorithms in the last couple of weeks. You can see all the changes on the Open source public fund experiment document.

In summary, I could extend the Criticality Score algorithm with usage metrics from Ecosyste.ms API and apply it to all open source accounts under the Open Collective, so we have a new ranking now! I also made it possible to change the weights of each parameter so that you can try the algorithm by yourself.

Stats

Here are some stats based on the latest data:

• The total number of Open Collective accounts with a code repository is 4729.
• 96.32% of those accounts use GitHub as their code repository.
• However, 15.38% of the GitHub username are not valid / don’t exist, which is a massive number. It would be handy if Open Collective could add a code repository/link verification method or ask the users to update their profile details occasionally.
• 81.62% of the accounts use USD as their currency. Their yearly budget is about $15 million, and the average is $3,887 per account, probably not even one percent of the ideal figures.
• The language of almost one-third of the repositories is JavaScript. Python comes second, and PHP is third.
• MIT dominates the license list with 41.91%, of which there are 27 different licenses. 15.41% of the repositories don’t have any.
• Regarding the accounts’ countries, the United States leads the list with 11.4%. China follows with 2.9%, the United Kingdom at 2.8%, Germany at 2.7%, and India at 2.5%.
• The Ecosyste.ms search returns 1453 matches out of 3336 unique repositories. Out of this data, npm is the top ecosystem with 46.94%, go is the second with 13.35%, and PyPI is third with 9.70%.
• And last, here are the top five repositories with the highest criticality score based on Ecosyste.ms config:
  • GitHub - babel/babel: 🐠 Babel is a compiler for writing next generation JavaScript.
  • GitHub - facebook/react: The library for web and native user interfaces
  • GitHub - Automattic/mongoose: MongoDB object modeling designed to work in an asynchronous environment.
  • GitHub - typescript-eslint/typescript-eslint: ✨ Monorepo for all the tooling which enables ESLint to support TypeScript
  • GitHub - numpy/numpy: The fundamental package for scientific computing with Python.

Check the article for the “Billion dollar question” intro, detailed updates, and what’s next

Open source public fund experiment - One and a half years update

As usual, your feedback is priceless; don’t hesitate to get in touch with any comments, questions, or ideas