Urban science as a software

Martin Fleischmann

2025-04-15

Who’s this guy

researcher

developer

Developing reproducible, computational urban science

Open by default

Use (and nurture) the existing OSS infrastructure

Treat research artifacts as OSS from Day 1

Only “stay closed” when there is a good reason

Reproducible research

Transparent
Accessible
Transferrable

Show me

Methodological foundation of a numerical taxonomy of urban form

I knew what needs to be done but there were no tools to do it. So, I created my own.

In 2019, I have joined the development team of the GeoPandas project.

GeoPandas is the core package in the Python ecosystem for spatial data science.

Geographical characterisation of British urban form and function using the spatial signatures framework

We had to scale up the analysis but tools were not ready. So, we improved the tools.

And created some new.

Understanding Urban Form - Hierarchical Morphotope Classification based on Gradually Loosening Spatial Restrictions

entering WIP zone

Some unresolved needs were left out in previous research. So we fixed them in existing and new tools

Generic framework for geographically-weighted modelling

What about openness and transparency when using restricted data?

Infrastructure

Ensure others can use the same

Reproducible environments

Containers / lock-files

Data

Standard (formats) better than niche

Open better than proprietary

Static better than database

The takeaway

Release early, release often

Make open a feature, not a bug

Do what is best, not what system wants