Active Travel Podcast - data in active travel, part one

Big data is a big issue right now - and we are perhaps about to realise just how much information Google and Apple have on us. Data is hugely important in understanding how we travel, but while we've been very good at measuring car traffic, how we measure cycling and walking is far more primitive.

David McArthur, at Glasgow University's Urban Big Data Centre, is trying to change that. Using Strava Metro data, and 'spare' CCTV camera capacity he was busy trying to work out who cycles and walks where - until the COVID crisis hit. Now his work is being turned to measure some of the changes we are facing around how we move around, and the new importance active travel is playing in the new normal.

Most methods of measuring active travel only give us part of a picture, however - and while the granular data on our lives is held by tech companies like Apple and Google, we might be glad that data isn't more widely available.

No one method of can capture everyone, though. Is there a way of making sure we are all visible in the right ways, in this new big data world? Is a national data centre for active travel the answer? And where on earth does government cycling data come from?

You can find out more about the Urban Big Data Centre, and David McArthur's work, here: https://www.ubdc.ac.uk/

Transcript

David McArthur interview FINAL MP3.mp3

Laura Laker [00:00:00] Hi and welcome to the active travel podcast. A brand new podcast brought to you by the Active Travel Academy, which is an academic think tank on all things cycling, walking and micro mobility. It's part of the University of Westminster in London and works in collaboration with folks from inside and outside the university. That's people like me. I'm Laura Laker an active travel journalist working with the Active Travel Academy on this podcast. Amongst other projects, and this is the first of a two part on data in active travel.

Laura Laker [00:00:28] The Active Travel Podcast is joined by David McArthur, who is a senior lecturer in urban studies at the University of Glasgow. David is with us today to talk about two pieces of research. The first is using crowdsourced data from Strava Metro to establish cycling patterns. And the second is using spare CCTV capacity to identify pedestrian volumes and movement, which is not as 'Big Brother' as it seems. David assures me so. Welcome, David. Nice to have you with us.

David McArthur [00:00:56] Thank you very much. Pleasure to be here.

Laura Laker [00:00:58] So you specialise in big data around transport and urban analytics. Can you just tell us a bit about how that works?

David McArthur [00:01:05] I'm based at the Urban Big Data Centre. So this was a center funded a few years ago with the idea that the UK wasn't making the most of the big data revolution. Our job was to try to establish ways in which new forms of data could be used to address substantial social science questions. So my stream of work was in transport. We've tried to look at what datasets are out there, what can they tell us about our transport network and how to improve our cities and what make the limitations of this sort of data. People were quite it was the hype curve where people were very excited it was going to change the world. We were trying to be a bit critical to those ideas.

Laura Laker [00:01:44] And people get very excited about new tech developments as shiny new toys kind of. But it's not always as wonderful as you might think. So can you tell us where transport data is right now and where it's going and presumably focusing on active travel?

David McArthur [00:01:59] It's quite interesting. There is amazing data out there. It's not always accessible, though. One thing we tried to do in the center was to price it out of the hands of data owners. But that's not always so successful. Sometimes there's legal regulatory licensing issues with the data. So if some local authority has used the commercial product or ordinance survey data, they can't necessarily share that data with a third party afterwards. There's also issues of perhaps it's commercially sensitive. So with a deregulated bus network, for instance, the data may be helped by the operator of a bus service. So it might not be available easily to outside researchers, which is a shame because it would be nice to have better data on who takes the bus and where do they go, but it's commercially sensitive information. So there's lots of great data, but the governance issues tend to pose far more challenges than the technical issues of analysing it.

Laura Laker [00:02:55] Obviously, there's going to be pri