In spite of a 7.9% increase in traffic, 2017 was the safest year in aviation history. During the next 15 years we can expect even higher demand and increase (doubling) of air traffic. Maintaining or improving the safe Aviation record and ensuring the fair, safe and secure integration of UAS business will require more Data & Services. Addressing this challenge, the workshop “DATA DRIVEN ATM: GOING DIGITAL!” described the state of the art and debated the areas of interest and key technologies needed to be developed in the future, regarding the use of Information Networking and Big Data techniques in the Air Traffic Management area.

Discussions took place within a panel that presented and debated the trends and issues relevant to the different organisations. The general feeling is that information networking—and along with it, data science—is leading us into the third transformation of the airspace and ATM. Along this path, the panel discussed a large number of ideas (such as the development of predictive systems based on data science), focusing more on these five:

  • Data Science is based on the availability of data; perhaps this is the reason that Data Sharing was one of the most discussed topics. Sharing data not only requires the development of a secure environment, it also requires the existence of a common information model that facilitates access to the information. Furthermore, sharing data implies the existence of a business model that ensures that everybody in the supply chain (from the data provider to the information user) gets something in return. During the discussions, ideas such as the creation of a third party, independent business entity in charge of the data or the creation of a “data space” were raised. All ideas acknowledged the need to have a secure environment, in which access was granted only to the people authorised to have it.
  • Using data science to increase the efficiency of the operations of both providers and clients. Ongoing work in the different organisations is already leading to increases on efficiency in aspects such as crew management, in-flight path optimisation, prediction of the required landing requirements or decision support tools for non-time critical systems. Efficiency will not be limited “just” to do things better, but to create and exploit better the information of the ATM system
  • Supporting the use of data science applications through the definition of appropriate business models. Data is not free. There are costs associated to its collection, its cleansing, its transformation into information and its exploitation. We need to know who pays for the processing of data into information and we need to be able to identify clearly how value can be accrued and costs recovered. Business models will ensure that the value of the tools and applications will be shared amongst those that contribute to its generation.
  • Developing knowledge and insight of the ATM system through the application of data science will lead to smarter processes that will support increased collaboration and innovation. Furthermore, smarter process will support higher infrastructure elasticity leading to a better use of available resources.
  • Implementing a seamless passenger experience. Data science can support the transition of the passenger between the different stages of her/his trip. Data science can also provide insightful information on the airport, the departure / arrival times, travel arrangements, etc. This information will be based on data acquired automatically (once authorised by the passenger) from different sources such as electronic boarding passes, mobile phones, etc.

As the panel discussions showed, there is a strong call for cooperation between R&D organisations and ATM industries in projects with mutual added value; R&D organisations need access to ATM data and ATM industries (both ground and airborne) need improvements in decision support tools, visualisation of complex data…

Information Networking and Data science have come to stay. We need to move forward and stimulate research and development in these areas to ensure that our companies and organisation create the value that society expects from us.

Please find in the following links the presentations shown during the workshop focused on DART:

  • DART overview: goals & objectives, approach, data sources and achievements [click here].
  • Visual Analytics in future data-driven ATM environment [click here].

Leave a Reply

Your email address will not be published. Required fields are marked *