2025-11-15 –, Node
We take an intuition about a local school crossing and, using OSM, find data to make this feeling precise through a careful analysis, and use this analysis to advocate for local change. We hope this serves as a blueprint for other people to do the similar work in their communities.
Have you ever walked or cycled somewhere and wondered if there is a safer path to take? “Active travel” is the term used in urbanism to describe travel (for some particular purpose) by walking, wheeling or cycling. Active travel has huge benefits: for us - for our health, and for the places where we live and spend time in - on air quality, increased road safety, reduced carbon emissions... to name a few.
Most places were not designed for active travel and those of use who travel actively, we know. But putting data behind the feeling is not your average walk in the park. Is it possible to take these intuitions and convert them into data-backed analytical questions that can be answered definitively?
In this talk, we are going to try!
We show, using open-source data and tools, that we can hone in and ask, does this school have the worst intersection in Edinburgh? And in doing so, we find some data to back our intuition, resolve ours and, maybe even, other questions, and turn it into a tangible analysis we can use to promote actionable change in our neighbourhood.
python, osm, urban-planning, visualisation, schools
Noon is a programmer; originally from Australia but now living in Edinburgh. He loves reading, maths, is passionate about the climate crisis and loves collaborating with others!
Gala is an urban data scientist, the uses OSM data to run urban analytics, to better understand places. She is also the convener of Geomob Edinburgh, which she started in 2024.