We build for people
who build on data.
Behind every useful dataset is someone’s work: collecting information, checking records, resolving differences, and keeping it up to date.
We’re building Commons so that work can go further: so another team can use it, another organization can build on it, and a useful dataset can become the starting point for something neither its publisher nor its first users imagined.
We started with the record.
Then followed where it went.
Commons is built by Dhiway. With MARK Studio and CORD we answered one practical question: can you verify who issued a digital record, and that nobody has altered it?
Then we followed those records into the world. They were copied into services, merged into datasets, cited in reports, used in decisions. The source kept changing. New people kept depending on them.
Verifying a record was the first problem.
Keeping it useful as it changes is the next one.
Sharing should make the next use easier.
You shouldn’t have to replace your systems to share information. You should be able to build on data someone else has prepared. And receiving a dataset should be the beginning of a connection, not the end of one.
Commons is our response: publish from the systems you already run, use data locally, and stay connected to published changes and retained history.
The goal isn’t to bring everyone onto one platform. It’s to let independent organizations work together with less repeated effort and a clearer picture of the information they use.
What guides us.
Four commitments, each with the everyday situation it comes from.
Let the work decide the infrastructure.
Organizations should decide where their data is collected, held, and used. Commons is built to work across data centers and laptops, with mobile support planned, so the infrastructure can fit the workflow rather than the workflow having to fit one deployment model.
Make useful work reusable.
Preparing a dataset takes knowledge and effort. More people should be able to build on that preparation instead of rebuilding it for every application or partnership.
Preserve the story behind the latest record.
Today’s value is only part of the picture. Earlier versions, corrections, and source references show what changed and let people revisit what they relied on, including applications and AI.
Let real workflows shape the infrastructure.
The test is what gets easier for the people doing the work: where updates stall, which integrations need constant attention, what it takes to explain an earlier result.
Built with the people who know the problem.
Commons is in early access. Our initial focus is public-data ecosystems: the agencies, programs, providers, and organizations that publish, prepare, and use shared information.
We’re interested in the whole relationship around a dataset, from the people contributing records to the teams building services and AI tools on top of them.
The starting point doesn’t need to be a big transformation.
Bring the data problem you know best.
Tell us what you publish, what you depend on, and where the work repeats. Help shape a better way to keep shared data connected.