Learn & build with the data

Move from seeing the stars to working with the data behind them.

Start with a guided lesson, create a small bright-star sample, or inspect the open pipeline that turns Gaia and Hipparcos catalogues into browser-ready 3D star maps.

Start learning Create starter data Inspect the pipeline

Use the data

Build something visible first.

Start with a small bright-star query, understand the columns, and make a chart, notebook, simple 3D scene, or classroom visualisation before tackling the full catalogue.

Start with the data guide

Learn concepts

Pair astronomy with data thinking.

Each topic is designed to teach both what the universe is doing and how measurements, selection effects, and assumptions shape what you see.

Browse the lessons

Inspect the machinery

Open the pipeline when you are ready.

Follow the route from raw catalogues to cleaned Parquet, spatial indexing, streaming cells, and the browser viewer.

Read the technical overview

What each topic teaches

Every topic has an astronomy idea and a data idea.

This is the bridge between wonder and understanding: a star map becomes more powerful when students also learn how the map was made, where it is reliable, and where it needs to be questioned.

Constellations

Astronomy: sky patterns vs physical space

Data: projection and perspective

Parallax

Astronomy: measuring distance

Data: viewpoint and triangulation

HR diagram

Astronomy: stellar evolution

Data: sampling bias and absolute vs apparent quantities

Star clusters

Astronomy: stellar age and formation

Data: natural laboratories and controlled comparisons

Radio bubble

Astronomy: scale and light-speed limits

Data: model assumptions and detectability

Astrophage

Astronomy: local stellar geography

Data: nearest-neighbour paths through real data

Builder path

Three levels of depth.

Beginner

Create a starter sample

Start small: a bright-star query, readable columns, and enough structure to make a chart, classroom prompt, or simple visual experience.

Pipeline

Rebuild the data

Install the open pipeline, download source catalogues, merge Gaia with Hipparcos, and produce the Parquet outputs used by the site.

Machinery

Understand the viewer

Learn how a spatial index lets a browser stream what it needs instead of downloading a billion-row star table.

Open questions

Ready for an investigation?

Try a research brief that asks whether a visible structure is physical, a consequence of measurement geometry, or an artefact of the way the data is rendered.

Browse research questions