Firstly, a massive apology for not posting in some time. Life has been a bit full on over the last year or so, so the blog has taken a back seat. My apologies especially go to those comments that have remained unmoderated for 6 months. My bad. 😦
Also, just to let you know that while I will touch on the Streetgeekery stuff every now and then, this blog will take on a more transport technology and futures focus. I will still remain true to its original intent, just less about street lamps and tactile paving. Besides, there are loads of great blogs covering that. Anyhow, on with the post.
If you think about the UK’s contribution to the transport world you will no doubt think of the likes of Brunel, George Stephenson, maybe even maritime (the whole Britannia rules the waves thing). But one area where the UK has made an undervalued contribution is transport data. While Detroit may have led the way with four-stage modelling, and Lowry’s model of Metropolis form the basis of modern transport modelling, the early work of the Transport Research Laboratory set the standard for data collection, and standards required of its quality.
Now, this blog has been critical of models in the past (and boy has it been), but they are and are likely to remain a useful tool on which to inform transport decisions. But the data collection game to inform these models, and the data collection requirements of transport professionals, are changing in a digital world.
The sheer amount of devices that can collect data on transport (there are over 83 million mobile phones in the UK alone) but tracking movements isn’t enough. There is an ever-expanding sea of personal information willingly shared out there, with an exploding number of things to collect it, and even more opportunities that it brings. Businesses like transportAPI are finding new ways of manipulating this data, and generating new business models from it. The shift is taking place where simply collecting and modelling transport data isn’t enough. Transport professionals need to understand that data creates value outside of major scheme business cases or informing a purely transport decision.
Let me put it this way, and this is something that may be uncomfortable to many. The best users of transport data are not transport professionals.
That sounds nuts doesn’t it?
Ok, perhaps i’ll clarify a bit. If you want someone to use transport data for a specific transport purpose, to a modeller you must surely go. But there are many more companies using open transport data that, frankly, none of us could have thought of. Want proof? Try CityMapper for one – transport data repackaged into something usable. Or how about how Transport for London’s open data now powers over 200 apps?
Transport data courses need to be so much more than building spreadsheet models and regression analyses. It needs to be something more fundamental – how transport data can create value outside of transport, and our responsibilities as professionals to not just rigorous data quality for our clients but to making this data available for the common good. That means going outside our comfort zone, and facing challenge from outside the industry on how this data is used.
A report from the Transport Systems Catapult (yeah, its a work plug, so sue me) is intended to be the first step on this journey. It’s not the entire story but I’ll say one thing: the days of only collecting data from manual counts, and putting into simple spreadsheet models to form the basis of transport decisions are numbered.