Open the skies to big data: ATM technical and cultural challenges18 January 2016
A highly technological industry, aviation generates an enormous amount of information from its systems, and in the era of big data, there are many opportunities to derive great benefits from it. Jim Banks speaks to Simon Daykin of NATS about the technical and cultural challenges ATM must overcome to use real-time data to full effect.
Every industry is grappling with the implications of 'big data' and trying to see clearly what real benefits it could bring. The first step along that road for ATM, however, is to define exactly what the term means.
"Big data means a quantum shift in three things: volume, variety and velocity. In ATM, there has always been a large volume of data," says Simon Daykin, chief architect at NATS. "We already have over 1.5 trillion data items a year from radar, but that will rise exponentially. When it comes to variety, data is typically from specific centres such as radar, but there are opportunities in mixed media, voice data and social media. We are excited about acquiring broader data sources.
"Velocity refers to the speed at which we ingest and handle data. ATM is good at that, as it has real- time systems, yet we need to not only maintain, but also increase our ability to handle data in that way," he adds.
Handle the load
NATS is the UK's leading provider of air traffic control services, handling 2.2 million flights and 220 million passengers in UK airspace each year. It not only works with 14 UK airports and manages all upper airspace in the UK, but also provides services in more than 30 countries across Europe, the Middle East, Asia and North America. Daykin is in charge of ensuring that NATS' systems align with its operational and business strategies.
"Using big data will help us to deliver the best outcomes for passengers and users of airspace - improving the quality of services, enabling better flight profiles, increasing fuel efficiency, reducing carbon emissions and much more.
"We have already done a lot of work on solutions such as time-based separation (TBS) to improve punctuality by fusing huge amounts of historic data, such as arrivals at Heathrow, and live data from planes to analyse the wind situation. We fuse that data in real time to calculate the safe separation of aircraft," Daykin explains.
"This shows that we are already benefitting from the use of big data, but it still just a drop in the ocean. The challenge now is to broaden the applications. People can now ask questions they never could before. We can predict the future as never before and there is a big shift from using hindsight to using foresight with a high propensity for success. We have to relate the possibilities to the business benefits and allow innovation to expose new ideas."
Open minds and open systems
It is self-evident that data-gathering is the first priority when tackling big data but, in ATM, the volume of data is already vast. In similarly data-intensive industries, there is a tendency to focus on prioritising the value of data, but Daykin's message to such businesses is to be careful about getting rid of any data that does not appear immediately useful.
"People are starting to realise that it is more expensive to figure out what data to keep and what to throw away than it is to keep it all. It is actually cheaper to keep data but people don't always understand the value that some data can bring. Broaden your imagination in terms of what is possible. Let the data speak. Let it lead the way rather than using existing preconceptions to determine what data is valuable," he urges.
The first challenge, therefore, is to change people's attitude towards data. Other challenges, however, are purely technical.
"We are coming out of the data dark ages, during which time we have thrown away a lot of potentially valuable data. So, culture is very important not only in terms of how people view data, but also because the shift that is happening needs real focus. There are also technological and financial challenges. Big data needs investment and knowledge: you cannot have a science-project mentality. You need to get people who understand the historical problems to comprehend the technological capabilities and opportunities now," Daykin believes.
"For instance, at Heathrow, the headwinds have always been a problem. TBS has been a success because people, processes and technology have been brought together to solve the problem. Everyone is on board, from the regulators to the pilots."
TBS, which has been jointly developed by NATS and Lockheed Martin, will come into operation at Heathrow Airport in the near future. In the years ahead it is expected to become the industry norm for capacity constrained airfields.
Another data-driven development led by NATS is XMAN - cross border arrival management. Traditionally, NATS has only been able to influence the approach of arriving aircraft once they enter UK airspace, but with the ongoing trial of XMAN the build up of holding stacks at Heathrow will signal air traffic controllers in the Netherlands, France, Scotland and Ireland to request aircraft up to 350 miles away be slowed down, to minimise delays on arrival.
"XMAN uses a variety of data. It is a good example of what could be achieved, because it is the first real deployment of system-wide information management (SWIM) to share data between stakeholders. SWIM is mature technology used in other industries, and we are now investing heavily in the SWIM infrastructure to make data readily and quickly available to different actors in the system," Daykin remarks.
"SWIM is a big part of the operational platform that will be developed in the next five years. The mantra is to share everything in a cost-effective and accessible way. Sharing information between stakeholders is fundamentally important but it is a challenge. We need to look at new ways to share data but we recognise that data informs business decisions, so we need to explore it from the perspective of the best outcomes for the industry and let that dictate our approach to data sharing."
Ride the big data wave
Daykin sees the wave of data democratisation, in which data comes from myriad new sources, pushing against the perception that sensitive data sets should be closely guarded. He points to traffic data as an example. Once it was considered sensitive, but now it is integrated with applications such as Google Maps.
"The cultural change that is needed is about engagement in innovation: we engage people in an open process of innovation. Data storage was once seen as a big cost, but now it is relatively cheap and we can get economies of scale. In this - and in other areas - the traditional paradigm needs to change," says Daykin.
"As an industry, we are still on a journey and everyone needs to share their data more openly. People are starting to get that message, though we need to accept commercial realities. Every industry has to go on that journey, but in ATM we have TBS and XMAN really demonstrating the benefits. The next step is to liberate the value of the opportunities that lie ahead and invest in the capabilities to support big data."