Building Data Commons¶

Communities are what communities build together. Google Earth Engine (GEE) is powerful not only because of what it can compute, but because of who gathers around it — a community that iterates in the open, shares its code, and learns in public. The Awesome GEE Community Catalog began as an attempt to give that spirit a home for data: a place where anyone could contribute a dataset and everyone could find one.

How it started¶

The catalog started with a single question. A user asked where to find Facebook's high-resolution population density maps — a dataset the official GEE catalog didn't carry. Hosted by Columbia University and resolving population down to 30 meters, it was exactly the kind of valuable, hard-to-reach layer that fell through the cracks. Rather than treat that gap as a dead end, we treated it as an experiment: what if the community itself maintained the datasets it needed?

That Facebook dataset became the first entry in the catalog — and, fittingly, one of its most frequently updated. The full origin story is captured in the foundational blog post.

The guiding principle¶

The catalog is built on an old idea about shared resources. Elinor Ostrom's Nobel-winning work on the governance of commons showed that communities can steward shared resources sustainably when they agree on the norms for using them — the same principle that carried open-source projects like Linux and collaborative knowledge bases like Wikipedia. What works for a physical commons, we believed, could work for a digital one.

So we set out to build a Community Data Commons: the Awesome GEE Community Catalog.

Why it matters¶

Earth Engine democratized access to planetary-scale processing. The catalog aims to do the same for the data — lowering the barrier to a growing, curated collection of public datasets so that finding the right layer is no longer the hard part of a project.

The real challenge, and the reason a commons model fits, is scale in both directions: the catalog has to serve continental datasets and one-off community contributions with equal care. It works because the Earth Engine ecosystem already runs on learning, adaptation, and iteration. The catalog simply gives that culture a shared shelf — a bridge between the people who publish data and the people who need it.

It is, and will remain, a collaborative effort. Its continued growth depends on the community that builds it. Contribute a dataset and help the commons grow.

Catalog Assistant