TfL selects Tibco on journey to exploit big data

By Sooraj Shah
03 Jul 2014 View Comments
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Transport for London (TfL) has selected Tibco's services to create its XIS platform as the organisation bids to exploit big data.

The public-sector organisation's CIO, Steve Townsend, told Computing that the firm has been busy with preparatory work around data exploitation - something that TfL hadn't been doing before.

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"We've got an awful lot of data within TfL, much of which is shared, but we don't necessarily exploit the information to the full within the organisation," he said.

Townsend suggested that this was because as an organisation TfL hasn't really got to grips with how powerful this information is, and because in the past the organisation hasn't been able to share the data freely between different departments internally.

In order for this to change, the company has selected Tibco's services to bring together all the data across the organisation.

"We want to be able to store and make it available across the organisation, whether you're looking at congestion between stations, locations of buses or activity of Oyster Card users," he said.

In the past, departments had created siloes of data, said Townsend.

"You've got people like road space management for instance, who look into capacity management in the streets, and they have never shared data with the London Underground. If these data sources are brought together it could mean we can make different decisions across the organisation," he said.

Townsend believes sharing this data internally will open up new avenues externally too for both developers and advertisers.

TfL currently shares much of its data with the London Data Store, which is popular for developers who want to create apps for smartphone and tablet devices, and it hopes that more information will enable the travelling public to make better decisions for their journeys.

And analysis of the data should mean TfL's contractors are better prepared to sell advertisements across London.

"Through analysing some of the data we've got, without knowing who it is, but how many people you have got in a particular station, travelling down a particular corridor at a particular time of day, advertisers could look at that and say we will advertise their product because we know that's a popular spot, and we can do it at different times of the day," Townsend suggested.

"If you combine that with Oyster data and data from our Wi-Fi system, we can build an accurate picture of flow, not just on the Underground but across the whole of London," he added.

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