News

A unique dataset for researchers of 12 million commercial flights

20 October 2020

This covers

Air navigation services performance review

Artificial intelligence

Innovation, research and simulation

Network performance

New EUROCONTROL R&D Data Archive launched.

EUROCONTROL’s new R&D Data Archive gives a huge boost to AI and machine-learning applications, providing researchers with access to detailed flight data of 12 million commercial flights across the European network spanning a four-year period.

The EUROCONTROL R&D Data Archive gives researchers and data scientists access for the first time to access enormous European aviation datasets. Drawing on the EUROCONTROL Network Manager’s unique data repository, the Archive offers the best possible air traffic management picture available, covering data from airlines, aircraft and air navigation service providers on flight plans filed, aircraft used, actual routes flown, ground-air communications, radar tracking, market segments, and so on.

“Even the very smallest dataset in each quarterly bundle of data – such as a list of flights, with details of aircraft type, market segment and operator – will be hugely interesting to economics and business students. Yet in every gigabyte of quarterly data, such data comprise barely 3% of the total: data scientists, AI researchers can benefit from enormous volumes of data on routes flown, helping research into flight sustainability and environmental impacts, among other aspects.”

Denis Huet Head of Aviation Intelligence Unit, EUROCONTROL

Four 1-month releases of all commercial flights are provided per year, covering the months of March, June, September and December. The first data are from March 2015, running up to September 2018; the next tranche of 1-month of full flight data will be released in January 2021 covering December 2018 data (this respects a 2-year delay in data release agreed with aviation stakeholders).

EUROCONTROL expects these data to prove invaluable for researchers looking to use artificial intelligence/machine learning applications to analyse flight sustainability and environmental impacts, as well as business and economics students looking to understand the aviation sector in more detail