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Revolutionize the data industry with open source principles

For decades, the data industry has operated under a similar model, vertically integrated silos with data licensing between parties. While we've built incredible technology under this model, we have yet to fully capture the opportunity of open source innovation. The open source software movement has shown that there is a different, more powerful way to build productive digital goods. The data business is waiting to be disrupted, just as software has been since the 1990's.

Bringing sustainable funding to public goods by revenue-sharing towards dependencies

Over 2024, OSO's technical architecture went through several major iterations to get to where it is now. There are so many different ways to architect data infrastructure, that the choices can be overwhelming. Every platform will say they provide what you think you need, and none of them will do everything you actually need. In this post, we'll share the choices that OSO made along the way and the pros and cons of each decision.

We’ve been thinking a lot about advanced metrics lately. We want to get better at measuring how specific types of interventions impact the public goods ecosystem.

For example, we frequently seek to compare the performance of projects or users who received token incentives against those who did not.

However, unlike controlled A/B testing, we’re analyzing a real-world economy. It's impossible to randomize treatment and control groups in a real-world economy.

Instead, we can use advanced statistical methods to estimate the causal effect of treatments on target cohorts while controling for other factors like market conditions, competing incentives, and geopolitical events.

This post explores our early experiments with synthetic controls and causal inference in the context of crypto network economies.

One of our primary goals at Kariba (the team behind Open Source Observer) is to build a network of Impact Data Scientists. However, “Impact Data Scientist” isn’t a career path that currently exists. It’s not even a job description that currently exists.

This post is a first step in changing that. In it, we discuss:

1. Why we think the Impact Data Scientist is an important job of the future
2. The characteristics and job spec of an Impact Data Scientist
3. Ways to get involved if you are an aspiring Impact Data Scientist

One important caveat. This post is focused on building a network of Impact Data Scientists that serve crypto open source software ecosystems. In the long run, we hope to see Impact Data Scientists work in all sorts of domains. We are starting in crypto because there is already a strong culture around supporting open source software and decentralizing grantmaking decisions. We hope this culture of building in public and experimenting crosses over to non-crypto grantmaking ecosystems. When it does, we’d love to help build a network of Impact Data Scientists in those places too!