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Improving the UK’s Infrastructure using DAFNI: a new free analytics platform

27 June 2019

How can research and computing power help deliver more resilient, efficient and environmentally appropriate infrastructure?

Improving the UK’s Infrastructure using DAFNI: a new free analytics platform
Using DAFNI has transformed the capabilities and speed of models to predict and forecast new rail stations in the UK

Gaining enough computing power, enough qualified data and powerful enough models to carry out analysis and scenario testing on national infrastructure projects has been a challenge researchers, policy makers and planners have been struggling with for many years.

Trying to crack this challenge has been at the heart of UK’s Data and Analytics Facility for National Infrastructure (DAFNI).

The team at the Science and Technology Facilities Council (STFC), based at the Rutherford Appleton Laboratory in Harwell near Oxford, has been working for the last two years to get to the point of having a working version of DAFNI which really demonstrates the transformative potential of infrastructure data, modelling and simulation.

Joined up national infrastructure planning

‘Data now is as important to UK Infrastructure as concrete or steel’. – Sir John Armitt speech to DAFNI.

Rapid changes have been taking place in infrastructure in the UK in recent years. The National Infrastructure Commission (NIC) has published the UK’s first National Infrastructure Assessment, which sets out a vision for national infrastructure systems that are modern, efficient, inclusive and environmentally benign.

The NIC is now studying the resilience of UK infrastructure, and has been asked by the Chancellor of the Exchequer to use DAFNI for that analysis.

Meanwhile, we're witnessing transformation of infrastructure systems because of digitisation – yet sensors, big data and smartphones will not on their own deliver better infrastructure services.

We need to bring together the right types of data, and we need models and analysis that can extract dependable knowledge. DAFNI will take the science of infrastructure data, modelling, simulation and visualisation into an entirely new space.

At the recent DAFNI conference (10-11 June 2019 in London), the four elements of DAFNI were presented:

  • NID National Infrastructure Database
  • NICE National Infrastructure Cloud Environment
  • NIMS National Infrastructure Modelling Service
  • NIVS National Infrastructure Visualisation Suite

Post-event videos and presentations can be seen on the conference website.

Computing power that transforms research: The Pilot Programmes

You’ll also be able to see, and be able to explore, hands on, some of the DAFNI Pilot Programmes which have been central to DAFNI’s development.

Each pilot provides the focus for an agile software development sprint – testing the systems design and exercising its capabilities in different ways.

  • Digital Communications Model – Mobile and Fixed: modelling to achieve future mobile bandwidth requirements
  • Agent-based Housing Model – Spatial and Non-Spatial: modelling the interactions in the transport and housing sectors for better infrastructure investment choices
  • Urban Observatory Flood-PREPARED – Real-time data: analysis of surface water flood risk
  • Automated Demand Forecasting Model – Modelling demand for new local train stations

Improving rail station modelling in DAFNI

For many years, Dr Simon Blainey, Associate Professor in Transportation at University of Southampton, has been working on developing models to forecast and predict new rail stations at any point in Wales, England and Scotland.

Two years ago with colleague Marcus Young, he reached a point where they'd developed a sophisticated model, but it could only be run by research staff, with a lot of manual intervention and computing power, so it was very time- and money-intensive and very dependent on one person.

Using DAFNI has transformed the capabilities and speed of the model: they've now managed to semi-automate the model in DAFNI so it requires minimal manual intervention.

They also have a visual interface in DAFNI meaning that non-expert users can run the model in the future.

Previously, it would take around one day to model one station. Now, they can run a scenario in just 10 to 15 minutes for multiple stations.

DAFNI origins and construction

DAFNI is one important output from a long journey that began with the UK government allocating substantial capital funds to the UK Collaboratorium for Research on Infrastructure and Cities (UKCRIC), of which DAFNI forms part, alongside city observatories and physical laboratories.

The UKCRIC funding enabled the construction of DAFNI (both its high performance hardware and its custom-built software system) to be commissioned from STFC.

When DAFNI is completed in 2021, we'll move into an operational phase for which full funding hasn't yet been secured, though we're confident that with an enthusiastic user base in universities, government and business, the convenience, economies of scale, benefits of co-locating data and models, and system security that DAFNI will provide will ensure that it becomes the ‘go-to’ place for infrastructure data analysis, modelling and simulation.

The Automated Demand Forecasting Model is one of a number of tools which will run on DAFNI, the National Platform that will provide the UK with previously unseen levels of computer performance to analyse UK infrastructure data.

These tools will provide greater insights to inform policy decisions and therefore lead the world in our ability to prepare for future extreme events.

Want to get involved or find out more?

Visit DAFNI or contact the DAFNI team through the DAFNI Partnership Manager Marion Samler

  • Samuel Chorlton, Chief Technology Officer, Redbox Mobile