About
Why Found in Space exists.
Found in Space is an open educational project. It exists to help people move from a compelling scientific view into the evidence, assumptions and code behind it. Data and models are materials to think with: things you can inspect, question and use to make something new.
What this project is
The project begins with open astronomical measurements and derived data — starting with ESA's extraordinary Gaia mission, and adding other catalogues where they help complete the story — and makes that material explorable through interactive visualisations, guided questions and clear explanations.
It does not stop at presenting a finished view. The whole pipeline is on display: how to find and download stellar catalogues, how to clean and process them, how to analyse and index them for the browser, and how to turn them into something you can actually explore. The project code is open on GitHub: the data pipeline, spatial indexing, viewer runtime, and website can all be inspected and built on.
The site is part exhibit, part classroom, part lab. It might show you a constellation and then pull the stars apart to reveal the depths behind the flat pattern. It might ask you a question instead of giving you an answer, because the best way to understand something is often to work it out for yourself.
Why Gaia?
Gaia has mapped around 1.8 billion astronomical sources, giving positions and brightnesses across the sky, and parallaxes and proper motions for a huge subset of them. That scale, precision, and openness make it an extraordinary foundation for teaching and exploration.
Gaia is the starting point, not the boundary. Found in Space already draws on other catalogues, distance estimates and carefully documented manual overrides. The longer-term aim is to let observations, derived quantities, models, simulations and illustration play different roles while keeping those roles clear.
Questions over answers
A lot of educational material tells you facts and asks you to remember them. Found in Space tries something different: it sets up situations where curiosity can do the work. Why do these stars look different colours? What happens to a constellation when you leave Earth behind? How far away is "nearby" in astronomical terms?
The hope is that by exploring data directly — rotating a star field, comparing measurements, following a guided journey — ideas click in a way that reading alone can't quite achieve.
Open everything
All the code behind Found in Space is published at github.com/Found-in-Space: the data pipelines, the spatial indexing, the streaming formats, the interactive viewer, and the website itself. If you want to see how a visualisation works, you can read the source. If you want to build on it, you can fork it.
This isn't openness for its own sake. It's because the process of turning raw measurements into something people can explore is itself a lesson worth sharing. When the sources, assumptions and limits remain visible, a finished view becomes something people can question and build on.
Who's behind this
Found in Space is built by Kaj Siebert, who trained as an astrophysicist before spending two decades in data science and technology. The project brings those threads back together: astronomy, data, code, visualisation, and a long-standing interest in how people actually learn.
Kaj has spent the last decade running science outreach with CERN through The Big Bang Collective, and has always believed that the best learning happens through play. Found in Space carries that same spirit: serious data, but never a dry lecture. The aim is to build something people can wander through, get curious about, and genuinely enjoy.
