The NASA Air Traffic Management Ontology

The NASA Air Traffic Management Ontology (atmonto)

Release dated March 2018

This version:
Latest version:
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Richard M. Keller, Intelligent Systems Division, NASA Ames Research Center
Related Ontologies: contains the core class and property definitions used by this ontology extends this ontology by adding sample instances associated with flight, weather, and air traffic advisories in the New York area during July 2014

Documentation: auto-generated, browsable documentation for classes and properties
NASA Technical Memo #2017-219526: comprehensive, hand-written documentation and illustrations

This work is licensed under the terms of following agreement.


The NASA ATM (Air Traffic Management) Ontology describes classes, properties, and relationships relevant to the domain of air traffic management, and represents information pertinent to a broad and diverse set of interacting components in the US and the global airspace, including flights, aircraft, manufacturers, airports, airlines, air routes, facilities, air traffic advisories, weather phenomena, and many others. Three different variants of the ATM Ontology are provided: atmontoCore, atmonto, and atmontoPlus. The atmonto variant extends the core ontology by adding instances corresponding to key infrastructure components of the US National Airspace System (NAS). (See Ontology Variants, below, for descriptions of the other two variants.)

Table of Contents

1. Introduction back to ToC

The US National Aeronautics and Space Administration's (NASA) Air Traffic Management (ATM) ontology was developed as a key component of a semantic data integration system built to support integration, query, and search over multiple sources of heterogeneous ATM data, including data from the US Federal Aviation Administration (FAA), the US National Oceanic and Atmospheric Administration (NOAA), NASA, and other non-governmental providers (see acknowledgements for a complete listing of data providers). In this data integration system, the ATM Ontology is used to bridge multiple types of aviation data models and enable cross-datasource querying; the ontology serves as a backbone upon which to overlay data from multiple sources. The ontology data model is scoped sufficiently broadly to interconnect data from several different aviation realms, including flight, traffic management, aeronautical information, weather, and carrier operations. Representative entities modeled within the ontology include the following:

2. Ontology Variants back to ToC

There are three interrelated ontologies in the ATM Ontology suite: atmontoCore (URI:, atmonto (URI:, and atmontoPlus (URI:

3. Ontology File Organization, Description, and Download back to ToC

Ontology files can be imported into an Ontology Development Environment (ODE) by loading any one of the three ontology URIs listed in Section 2. Individual ontology files, as well as a zipped folder of all ontology files, can be downloaded from links in the following subsections. All of the ontology files use the key namespace definitions shown in Table 1.

Table 1 : ATM Ontology Namespaces

3.1 atmontoCore Files

The atmontoCore ontology defines the core, foundational concepts and properties of the ATM Ontology. (No instances are included in atmontoCore.) The ontology file and its associated import files are shown in Table 2.

Table 2:  atmontoCore ontology file plus imported core files
Defines the atmontoCore ontology, which imports the other files listed in this table
NAS Defines concepts related to the structure of the US National Airspace System (NAS) rdf
Defines specific air traffic management concepts used in aircraft navigation through the NAS rdf
Defines concepts related to airport status, including weather, forecasts, and airport operations rdf
Defines aircraft models, aircraft systems / subsystems, and aircraft characteristics rdf
Defines temporal / spatial concepts and general-purpose datastructures rdf

3.2 atmonto Files

The atmonto ontology makes certain infrastructure components of the NAS concrete by including instances of all major NAS structures (ATCCC, ARTCCs, TRACONs, sectors, fixes, routes, airports, etc.), along with information about the airlines and aircraft manufacturers that utilize the NAS. The atmonto ontology imports atmontoCore, plus the instance files in Table 3.

Table 3: atmonto ontology file plus additional imported infrastructure-related instance files
Defines the atmonto ontology, which imports the atmontoCore ontology and the other infrastructure instance files listed in this table rdf
acManufInst aircraft manufacturers rdf
acModelInst aircraft models and types rdf ttl
airlineInst airlines rdf ttl
airportInst airports, runways, terminals, gates rdf ttl
NASinst US Air Traffic Control Command Center (ATCCC) and Air Route Traffic Control Center (ARTCC) en-route facility instances rdf ttl
ARTCCLocationInst Air Route Traffic Control Center (ARTCC) en-route facility boundary polygons and adjacency tiers rdf ttl
equipmentInst aircraft characteristics (weight class, wake category, engine type) rdf ttl
fixInst air navigation fixes rdf ttl
routeInst defined US federal air routes (airways) rdf ttl
SectorLocationInst en route airspace sector definitions, boundary polygons, and boundary layers rdf ttl
sidStarInst Standard Instrument Departure routes (SIDs) and Standard Arrival Routes (STARS) rdf ttl
TRACONinst Terminal Radar Approach Control (TRACON) facilities rdf ttl

3.3 atmontoPlus Files

The atmontoPlus ontology imports atmonto, plus the additional instance files in Table 4, representing flight data and associated contextual data for a sample of 100 flights arriving at or departing from the three major New York area airports (JFK, LGA, EWR) on 15 July 2014.

Table 4: atmontoPlus ontology file plus additional imported flight-related instance files
Defines the atmontoPlus ontology, which imports the atmonto ontology and the other flight-related instance files listed in this table rdf
flightInst flights, along with filed flight plans and the actual navigation paths traversed by the 100 sample flights rdf
acInst registration details for aircraft used in flying the 100 sample flights rdf ttl
ASPMinst hourly airport conditions for the three New York airports during July 2014 rdf ttl
dayInst days from 2012-2017 plus the 24 hours of a day rdf ttl
METARinst hourly airport weather conditions for the three New York airports during July 2014 rdf ttl
TAFinst hourly airport weather forecast for the three New York airports during July 2014 rdf ttl
TMIinst Traffic Management Initiatives (TMIs) issued by the FAA during July 2014 rdf ttl

3.4 Zipped version of all files

4. Data Sources back to ToC

The ATM Ontology incorporates selected information from the following data sources, extracted for the month of July, 2014:

5. ATM Ontology Classes and Properties back to ToC

Complete documentation for the core classes and properties defined by the ATM Ontology is published in NASA Technical Memo #2017-219526: "The NASA Air Traffic Management Ontology: Technical Documentation."

In addition, auto-generated HTML-based ontology class and property documentation can be found at

The figures below (all extracted from the abovementioned NASA Technical Memo) provide some intuition about how the classes and properties represent the structure, content, and relationships found in ATM data. Only a subset of available figures is shown here; please consult the NASA Technical Memo for additional illustrations.

Structure of the NAS

Figure 1. Structure of the NAS

An illustration of the key relationships among selected New York area airspace structure and facility instances. Sector nas:ZNYsector075 is one of the sectors located in the New York Air Route Traffic Control Center (ARTCC instance nas:ZNYcenter). Sector 075 is composed of two stacked horizontal layers of airspace, each represented by a shear-sided polygon of a certain height (only one polygon is depicted in the figure). The ZNY ARTCC has operational agreements with the FAA command center and the New York Terminal Radar Approach Control (TRACON) facility, which in turn has agreements with each of the airports in its territory. The ZNY Tier 1 structure contains all ARTCCs that directly border the ZNY ARTCC. (Note that only a small subset of instances is illustrated in order to keep the figure uncluttered and readable.)

Structure of a

Figure 2. Structure of a Flight

This figure illustrates the basic components of the ontology representation of a flight -- in this illustration, Delta Airlines flight DAL435 on 2014-07-15. The flight is associated with its departure and arrival airports; the aircraft, aircraft type, and operating carrier; and the actual and planned flight route.

Relationships among aircraft, carrier, flight, model,
              manufacturer, and related classes

Figure 3: Relationships among aircraft, carrier, flight, model, manufacturer, and related classes

This figure illustrates the relationships among instances of aircraft, carrier, flight, model, manufacturer, and other classes associated with Delta Airlines flight DAL435 on 2014-07-15 (shown in Figure 2, above). The aircraft flown for this flight is N713TW, a Boeing model 757-2Q8, one of the B757-200 family of aircraft. The aircraft family is represented as a model class and the the specific model is represented as an instance of that class. The FAA also designates an aircraft type, which may cover models in multiple aircraft families. The aircraft type for model 757-2Q8 is B752. Associated with type B752 aircraft are a set of instances that describe the engine type, wake turbulence category, and weight class of all B752 type aircraft.

Flight trajectory

Figure 4: Structure of an Actual Flight Route (Flight Trajectory)

This figure illustrates how the actual and planned flight routes for American Airlines Flight #AAL335 are connected to the flight instance (atm:AAL335-201407150017), which is depicted at the root of the tree structure shown. The actual flight route is represented as a sequence of track points (atm:AircraftTrackPoint). Each track point represents a specific reporting time when the aircraft’s fix and speed is captured and relayed to ground systems. The track points are each linked to an instance of atm:LatLonFix, which stores the latitude, longitude, and altitude. The planned flight root is detailed in Figure 5 below.

Flight plan

Figure 5: Structure of a Planned Flight Route (Flight Plan)

This figure elaborates on the representation for the flight plan (atm:PlannedRouteAAL335-201407150017) shown at the root of this tree and also in Figure 4. The flight plan includes a flight route string ‘KLGA./.CFB..RAAKK.Q436.EMMMA.WYNDE5.KORD’, which is a representation of the path to be flown through the airspace. The flight route string is initially filed by the pilot prior to takeoff and modified as needed en route. The root node in the graph contains this route string as a property, but the string is also converted into an explicit sequence of ‘container’ nodes that include (via the property atm:hasNavElement) the major navigational components through which the flight is planned to progress: the originating airport (KLGA); a VOR fix (CFB); a portion of a high-altitude flight route (Q436); a traverse through a standard terminal arrival route (STAR WYNDE5); and the destination airport (KORD).

  6. References back to ToC

7. Acknowledgements back to ToC

This work was funded by the National Aeronautics and Space Administration under the Aviation Operations and Safety Program.

The NASA Air Traffic Management Ontology incorporates data from the following providers, and NASA gratefully acknowledges their contribution:

My sincere thanks to Mei Wei and Shubha Ranjan, who contributed long hours to software development for the ATM Ontology, and to Michelle Eshow, who led the Sherlock Aviation Data Warehouse team and generously supported, encouraged, and contributed effort toward this ontology development activity from its inception.
   - Rich Keller