OpenSky Network

OpenSky Network
Name	OpenSky Network
Formation	2013
Type	Non-profit research project
Headquarters	Zurich, Switzerland
Region served	Global
Leader title	Directors
Parent organization	University of Zurich

OpenSky Network OpenSky Network is a collaborative research-driven initiative that operates a large-scale sensor network for airborne surveillance based on Automatic Dependent Surveillance–Broadcast (ADS‑B) and related data. It aggregates and curates multilaterally sourced flight data to support academic studies, industrial analyses, and public-interest reporting while interfacing with institutions in Zurich, ETH Zurich, University of Zurich, Swiss Federal Institute of Technology, and international partners in United States, Germany, and United Kingdom.

Overview

OpenSky Network maintains a distributed receiver network that collects ADS-B transmissions, Mode S, MLAT position estimates, and other aircraft-derived messages. The project serves researchers in air traffic management, aviation safety, transportation research, computer science, and networking by providing historical and live datasets, analysis tools, and an open data policy. Its platform underpins studies involving stakeholders such as International Civil Aviation Organization, European Union Aviation Safety Agency, Federal Aviation Administration, and commercial operators including Boeing and Airbus.

History and Development

The initiative was formally organized in 2013 by academics and engineers from institutions including ETH Zurich and University of Zurich to address limitations in access to high-fidelity flight data used in prior studies like those at MIT and Stanford University. Early development drew on prior community efforts around Mode S and hobbyist receiver projects tied to organizations such as FlightAware and Flightradar24. Over successive funding rounds and pilot deployments the network expanded through collaborations with research groups at TU Delft, Imperial College London, Massachusetts Institute of Technology, and national research labs in Germany and France.

Data Collection and Infrastructure

Sensors in the network capture squitters and transponder replies transmitted by aircraft, including ADS‑B 1090ES and UAT formats used in regions like United States and Australia. Receivers, often based on low-cost software-defined radio hardware such as RTL-SDR, forward data to centralized ingestion systems hosted at research data centers associated with University of Zurich and cloud partners. Time synchronization for multilateration relies on Network Time Protocol servers and GPS-disciplined clocks used by nodes colocated near institutions like DLR research centers and university observatories. The dataset includes 24/7 streams of position, velocity, flight identification, and Mode S interrogation metadata that together support MLAT solutions, corroborated with public flight schedules from operators such as Lufthansa, Delta Air Lines, American Airlines, and cargo carriers including FedEx.

Services and Tools

The project exposes programmatic access via APIs and bulk download mechanisms tailored for academic usage, with interfaces compatible with analysis environments developed at CERN and repositories common to Zenodo and GitHub. Tools developed by contributors include visualization dashboards, anomaly-detection scripts, and enrichment pipelines that integrate public aeronautical information from EUROCONTROL and ICAO datasets. Community software plugins interoperate with mapping services developed by OpenStreetMap contributors and geospatial toolkits from Esri-compatible ecosystems. Researchers can query historical trajectories, perform sector-load analyses referencing standards from IATA and Aviation Week, and replay traffic scenarios used in simulation testbeds at NASA and academic labs.

Research and Applications

Data from the network has been cited in studies of aircraft surveillance reliability, trajectory prediction models, studies intersecting with airspace design conducted with Eurocontrol Experimental Centre, and policy analyses involving transponder equipage trends examined by ICAO and EASA. Applications span anomaly detection endorsed by safety investigators at national authorities, emissions and fuel-burn analyses tied to work by International Civil Aviation Organization committees, and resilience assessments used by NATO research programs. Interdisciplinary projects have leveraged the corpus for machine learning benchmarks created in collaboration with teams at ETH Zurich and TU Munich, resulting in publications in venues such as IEEE Transactions on Intelligent Transportation Systems and ACM SIGCOMM.

Governance and Funding

Governance is maintained through an academic steering board with representatives from partner institutions including University of Zurich, ETH Zurich, and external collaborators from TU Delft and Imperial College London. Funding sources combine competitive grants from national research agencies such as the Swiss National Science Foundation, European research programs like Horizon 2020, and donations or service contracts with corporate research partners including Airbus and Boeing Research & Technology. Data access policies balance open-science principles with privacy and regulatory considerations influenced by directives originating in European Union policymaking and guidance from international bodies including ICAO and EUROCONTROL.

Category:Aviation