Data jewels

Opal – the recent ticketing overhaul for transport services in NSW has been greeted with a warm welcome from the state’s weary commuters. The concept of one electronic ticket appeals to the masses for its convenience across multi-service travelling (ferry, buses, and trains). But what I find really interesting, and an exciting prospect for the ‘big data’ world, is the sheer volume and granular nature of data that is being captured.

Commuters are required to tap on and tap off, at first glance this seems a simple and almost pre-existing habitual exercise for your frequent travellers. However, upon closer investigation, it begs the question of: what data is being captured? And more importantly, what are the implications?

Well for starters, any given individual with an opal card can login to the opal website and see the location and time of travel for all their given trips.

So there is some supporting evidence for telling your boss that the traffic was truly the reason why you were late and not sleeping in.

Moreover, on a serious note, this has far reaching implications. For one, the transport body can look to investigate trips which are running late, and the periods that they are running the most poorly. This data could not only help in monitoring traffic flows on given days, specific routes and during certain times, but allow for better planning and improving services.

Done correctly and coupled with some basic statistical assumptions, transport could be monitored to see areas that require more services and those areas which are being underutilised, such an analysis would have significant implications in ensuring tax payer money is being maximised and allocated efficiently. Despite still being in its infancy, I remain quite excited at the tantalising prospect of what my simple ‘tapping on and off’ could eventually lead to having a faster trip home.


5 thoughts on “Data jewels

  1. The data could help direct funds to transport lines that require an upgrade, (i.e. service line may have reached current capacity limits). The data can also be used for future transport infrastructure planning purposes. Very quickly, it becomes obvious there is value in “harvesting” the data from the Opal card.

  2. I would be interested to see how marketing will be tailored for those who frequent certain destinations as their profile and demographics could be captured along with the locations, much like what iPhone and other social media services are doing. I also look forward to having an integrated payment system where you can use one device i.e. your phone or credit/debit card for your transportation needs as well as other products and services.

  3. To take it further, if the travel data gets analysed on a geographical level it can also bring further insights. For example a group of friends or colleagues may find that it is actually cheaper or quicker for them to take a cab instead of the train ride (where a cab driver would pick them up one by one as it goes) if they travel to the same destination on particular days of the week, say a weekend football game

  4. The data available will be really valuable. I would love to know how many people are taking “phantom” rides to get to the limit in a week when further trips are free.

  5. Brilliant thinking. There are other metropolitan cities that have implemented a similar system. For example, Seoul with its 10 million population, operates its trains and buses with T-money which was introduced 8 years earlier than Sydney. Lots of learning opportunities for Sydney.

Add a comment