Start with a place.
Browse the map or use the table. Find a bike station, look at water levels, or explore the city’s environmental observations.
Personal project · City data
DublinData
A closer look at the city.
I wanted somewhere to explore what Dublin’s public data is actually telling us. A bike station, a river gauge, a weather observation: each is a little record of the city at a moment in time.
Explore DublinData ↗DUBLIN / FIELD NOTESIllustrative map
A station, not just a dot.
Explore bike availability and see when a station last reported.
This is a small illustrative preview. Open DublinData for the actual map, observations, timestamps, and source status.
The idea
Every reading has a backstory.
Keep the time attached.
A reading only makes sense if you know when it was taken. DublinData keeps the observation time separate from the time the data arrived.
Show the working.
Source information and available history sit behind the observations. Missing or delayed data should be visible, rather than filled in with a plausible number.
Under the map
Collect. Keep. Explore.
A separate collector gathers provider responses and keeps the evidence behind them. PostgreSQL with PostGIS and TimescaleDB stores the observations; FastAPI serves them to a Next.js interface with MapLibre.
The interesting part is making different sources understandable together without losing their context. A river gauge has its own reference level. A bike station’s availability can change in minutes. The map is the starting point for those details.
Explore the DublinData stories ↗