Learning catalogue

Learn astronomy by questioning the data.

Each lesson connects what you can see in the viewer to the measurements behind it. The aim is not just to name a concept, but to learn how real data makes that concept visible and where the data needs care.

First lesson

The Hertzsprung-Russell diagram

One of astronomy's most powerful maps, built from real star data: temperature, luminosity, stellar populations, and the limits of what a sample can show.

Open the lesson
Best for
upper secondary, undergraduate, curious adults
Time
20-40 minutes
Astronomy idea
stellar evolution
Data idea
selection effects, absolute vs apparent quantities
Uses
interactive HR diagram and 3D viewer
Build extension
compare samples, distance cuts, or missing faint stars

Lesson

Star clusters: families of stars

Fly between real clusters, from stellar nurseries to ancient globulars, and see how age, gravity, and the galaxy shape stellar families.

Open the lesson
Best for
upper secondary, undergraduate
Time
20-35 minutes
Astronomy idea
stellar age and formation
Data idea
natural laboratories and controlled comparisons
Uses
guided 3D cluster tour
Build extension
compare cluster shapes, ages, and distances

Lesson

The radio bubble

Explore an idealised sphere of human radio signals and ask which nearby stars those signals could have reached.

Open the lesson
Best for
secondary, outreach, discussion sessions
Time
15-30 minutes
Astronomy idea
scale and light-speed limits
Data idea
model assumptions and detectability
Uses
3D radio-sphere visualisation
Build extension
change assumptions about signal strength or detectability

Fiction meets real data

The astrophage infestation

Follow an unofficial story-led exercise inspired by Andy Weir's Project Hail Mary, using real nearby stars to explore local stellar geography.

Open the lesson
Best for
public engagement, secondary upward
Time
15-30 minutes
Astronomy idea
local stellar geography
Data idea
nearest-neighbour paths through real data
Uses
story-led guided tour
Build extension
design a route or game mechanic using catalogue-derived star positions

Research questions

After the lessons, ask what the data might be hiding.

Open investigations turn observations into testable questions. They are designed for students and independent learners who are ready to compare views, check assumptions, and treat uncertainty as part of the work.

Browse investigations

Our approach

Real data, carefully questioned.

Gaia gives the site its foundation: a vast public map of the sky, with measurements that let us estimate where many stars really are in 3D. But real data is not perfect truth. It has gaps, errors, selection effects, and assumptions.

The strongest lessons use those limits as teaching material. A feature in the viewer is most interesting when you can ask whether it comes from the stars, from the sample, or from the way the data is being shown.