Further to the Shakespeare Review which used TfL’s open data activity as a case study in 2013, we asked Deloitte to carry out a more comprehensive study on the value of open data to our customers, users and London overall.
We’re holding a consultation into our Transparency Strategy, and we’d love to hear from you about how we can improve.
The Strategy covers our open data products, so we want to hear from the developer community about our Unified API and open data. We want to know how we can improve our products to give you regular, up to date and useful information, as well as the formats in which this data should be published.
We’re also keen to hear how you think this data should be grouped or presented on the TfL website, and whether we need to give further support to developers, stakeholders and researchers who use it.
The consultation is running for six weeks, from 18 September to 29 October.
While we always encourage comments to these blog posts, to make sure your voice is heard visit our Consultation website to have your say.
It’s great to see so many customer-facing apps using TfL’s open data. With over 600 apps in areas of public transport, active travel and healthier streets, we are continually focused on releasing new data.
There are lots of people involved in the ecosystem, ranging from app developers and start-ups to accelerator programmes.
We are excited to launch our new TfL Oyster app on iOS and Android, which allows customers to top up their Oyster cards, purchase Travelcards and view their journey history. The app was launched last week, and has already received lots of great feedback. We wanted to offer you more insight into how we developed it.
An API – or application programming interface – is a set of subroutine definitions, protocols and tools for building application software¹. We already have a wide range of public APIs, which provide information such as line status, bus status and journey information. To build a mobile application allowing customers access to their Oyster card data through, we needed to write a new API to support this.
Back in March I posted this blog about Nitrous and their accelerator programme, which was focusing on some key transport challenges, and asking for applications to the programme. This short video looks at some of the participants in the accelerator programme, filmed at the event at City Hall on Thursday 22 June, as guests were treated to an evening of presentations and networking.
As you may already know if you’re following this blog, we recently released the TfL TravelBot on Facebook Messenger. If you haven’t read them yet, Steven and Charul’s posts will give you a bit of background.
Check out TravelBot here or search for TfL TravelBot in the messenger application. In this post I will explore the reasons for introducing a conversational bot and our learnings around the design of conversation.
Diverse backgrounds, cultures and lifestyles mean that we all use different words to talk about things. This can become frustrating when you’re trying to find something on a website.
In our team, we try to label things in a way that most users will understand, but are well aware of the fact that we will never be able to cater for everyone. This means that some users have to change the way they think to match what they are looking for.
The Blackwall Tunnel (A102) is one of the busiest places on London’s road network. In recent years, journey times have increased and drivers can expect delays to their journey at some times of day. We’ve released this data to the open data community, to enable developers to build the information into their products.
What our data shows
1) The busiest time in the northbound tunnel on a weekday is from 07:00 – 07:30. In heavy traffic conditions, drivers’ journeys could be 15 minutes quicker if they travelled between 06.30-07.00 instead of 07:00 – 07:30.
2) The busiest time in the northbound tunnel on a weekend is from 13.30 – 15.00. In heavy traffic conditions, drivers’ journeys could be 15 minutes quicker if they travelled between 12.00-13.00 instead of 13.30- 15.00.
We have made this data available to the open data community so you can use it to create products which display the busiest times at the tunnel, allowing drivers to choose to travel outside of these periods or create products for planning quicker and more reliable journeys.
Tell us what you think
We encourage the community to provide feedback on our new data sets to help us continue to enhance and improve our open data products. Please let us know your thoughts in the comments section below or on our tech forum.
We recently launched our first ever Chatbot – the “TfL TravelBot” on Facebook, which uses artificial intelligence to help answer customer queries expressed in everyday language. The bot was launched just two weeks ago and we have already received lots of great feedback. We wanted to offer you more insight into the thinking behind the TravelBot, and shed some light on how we developed it.
Why the TfL TravelBot?
Millions of people already use our website to help them get around London, and we’re constantly seeking new channels to make the process even easier. Research indicates that more than half of the world’s population is now online, and more than 50% of those online are active social media users*. Facebook is comfortably the biggest social media platform, and hence we wanted to take the opportunity to provide them with information via their channel of choice.
Instant messaging has emerged as the primary platform for communication these days**. With the advent of digital solutions making it easier to provide conversational platform, we felt it was the right time for us to enter the world of bots. We pride ourselves on being early adopters of technology, and wanted to leverage the potential of existing solutions to come up with a product which is one of the first of its kind in the world of travel.
How was it made?
We designed the logic behind the chatbot and it is hosted in the cloud. Every customer message passes through our logic, and the bot then seeks to deliver the best response. We use artificial intelligence enabled by the machine-learning framework to process the customer messages (Natural Language Processing). It works by understanding intent rather than phrases. Once the message is processed, the bot replies with either a response from our unified API or a friendly retort. The bot is intelligent and has the potential to learn over time.
How does it help?
Apart from being the channel of choice for receiving information, our bot will help the customers in many ways. It will help our customers get the information in the quickest possible time with a 100% response rate. For instance, queries like ‘When is my next bus due?’ can be easily automated, saving customers time and meaning they don’t need to wait for a customer services agent to get a response. In the case of more complex queries, the chatbot can prompt you to speak with an agent.
As a business, this frees up the time of our customer service agents and helps them focus on more complex customer queries. We are also be able to handle many more queries in the same time, therefore improving our response rate.
We’re constantly looking for feedback to improve our products. If you haven’t it tried yet, search for ‘TfL TravelBot’ on the Facebook Messenger app or go to http://m.me/tfltravelbot on your desktop/laptop. More details on how to use the bot can be found in our previous blog.
Please keep your feedback coming in the comments section below. We know there are more things you would like us to include, and we’re really keen to hear from you.
It was great to be part of London Tech Week through the excellent Hack Day on Friday June 16, put together by the teams at Ticketmaster and Transport for London. With over 600 apps powered by our data in the market place, I always look forward to these events as it allows me to raise awareness of TfL’s open data approach providing the opportunity for organisations and individuals to develop their own creative solutions.
This has helped to form new businesses, create jobs and launch new customer-facing travel products, giving customers more choice on their devices. A great part of this process is that this type of event is open to everyone at no cost, so we saw students, corporate professionals, freelancers, academics and participants from other sectors.
We’re proud to introduce our Facebook Messenger TravelBot, which has the ability to provide updates on bus arrivals as well as Tube and bus status updates.
Through our two Facebook pages – the main TfL page and the London Underground page – we deal with a huge number of queries every day, and we wanted to make it even easier for customers to get our information on the Facebook platform in a way that’s fast and straightforward. With the open data in our Unified API already helping to provide live information on many services like third-party apps and Twitter alerts, we hope this will be another big step towards enabling customers to quickly and easily access the information they need via social media.