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.
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.
The City of London Corporation are planning essential major maintenance works to Tower Bridge. The work will require a full closure of the bridge to all vehicle and cyclist traffic for three months. The closure will be in place 24 hours a day, 7 days a week from Saturday 1 October to Friday 30 December 2016.
As part of our open data policy, we’re releasing a full data set of the closure to allow developers to easily incorporate this data into their apps, helping Londoners to plan their journeys while the works are ongoing.
Chirdeep Chhabra from Digital Catapult gives an update on the Transport and Mobility Challenge, including an extended deadline for those taking part.
As previously posted on this blog, London Data City | Data Nation was launched on 12 April, with a series of 6 month-long challenges being undertaken by teams in London and Singapore.
The first in the series of challenges is the Transport and Mobility challenge, which is now underway and runs until Monday 16 May.
At the launch event for the challenge Rikesh Shah, Lead Digital Relationship Manager at TfL, introduced our open data policy and set the scene for the challenge. Following up on the launch event, Rikesh has a message for the participants with some handy extra info:
I hope you’re all enjoying the challenge.
At the launch of the Data Nation challenge I promised that I would provide more information about TfL, with a particular focus on customer insight. So, I am delighted to provide a link to some useful information.
In particular, have a look at Chapter 7 which focuses on Customer Experience.
All the best,
Transport for London
The London Data City | Data Nation challenge was launched on the morning of Tuesday 12 April at an event hosted by Digital Catapult. The launch event outlined the context and details of the 6 month-long challenge being undertaken by teams in London and Singapore, starting with the Transport and Mobility challenge that runs until Monday 16 May.
In partnership with TfL, the Greater London Authority and Ford, Digital Catapult are setting challenges based around 2 key questions:
Public Transport Challenge
How can we accurately identify, filter and characterise transportation delay events across large-scale, dynamic, multi-modal transportation systems?
Enabling users to make seamless progress towards their destination. People need help to very quickly identify breaks in the system and need greater help for decision making in case the system breaks and when to abandon their plans for a better option. Participants need to choose data sources (from sandbox or beyond) to achieve the end goal.
Road Network Challenge
How can we enhance customer service and experience across London’s road network?
Through Data City | Data Nation we intend to deliver new technology solutions that help understand and predict events on London’s road network and go about enhancing the overall customer experience whilst travelling that network. TfL will provide SCOOT traffic data (described in more detail here) to participants of the challenge that is not yet publicly available.
We’ll update this blog as key milestones in the challenge are met, and will of course announce the winners in May. Good luck to all taking part!
Setting the scene for the challenge
There were many expert speakers setting the context and details of the challenge, and their presentations are summarised below.
Introduction – Chirdeep Chhabra, Digital Catapult
- Digital Catapult’s 4 main areas of focus: Sharing of data between organisations, personal data, content and licensed data and data generated across the Internet of Things
- Data City | Data Nation overview: Brings together London and Singapore and private sector closed data in a sandbox for innovation, 6 months duration for the whole challenge. Transport and Mobility starts today
- Aim is to produce new insight into public services and private products
- Email firstname.lastname@example.org for more info
As previously outlined in our post on March 30 on this blog, the Traffic Data Hack Day was hosted by Amazon Web Services on April 6. The event was attended by TfL employees, academics working within this subject area, data scientists, transport app developers and data visualisation developers.
Another key event in our engagement with those working with our open data, the day was split into two areas, with one focussed on visualising TfL data and the other on extracting data from the source and providing it for analysis.
I’ve not attended a hackathon or hack day before, so it was really interesting to see how they work and to meet participants from all sorts of backgrounds, including universities, consultancies, government agencies and other parts of TfL.
At the beginning of the day we split the focus into two areas; ‘EMR (Elastic Map Reduce)’ where the group was looking at ways to improve the feed of, access to and processing of the SCOOT data and ‘Redshift’ where the group made use of data that had been uploaded to the system and was ready to analyse.