AN ONTOLOGY TO SUPPORT BRAZILIAN TRAFFIC FLOW MANAGEMENT BASED ON NASAs ATM REFERENCE MODEL¶
Abstract¶
Time over the past two decades has shown different data models being introduced to try to standardize information for interoperability in the aviation domain. World’s aviation organizations are rushing to maximize the efficiency of data exchange and actual initiatives like SWIM recommend the use of semantic knowledge descriptions to support air-traffic management information systems. The use of ontologies is increasing as a next step in aviation’s data structures evolution, describing semantics (concepts, properties and relationships) and being conceived in machine-readable language, able to be accessed via programming languages. This paper presents an OWL-DL Ontology to support Air Traffic Flow Management based on NASA’s ATM (Air Traffic Management) reference model. The original RDF files from NASA’s release are the core of the implemented ontology, which was built to adapt NASA’s taxonomy to Brazilian aeronautical laws and rules. Furthermore, the paper presents a set of experimental results which were carried out to manipulate the Brazilian customized ontology by using Python language and making CRUD (Create, Read, Update, and Delete) operations. In addition, the experiments show how to fill out and persist a flight plan form to simulate a pilot and an aeronautical information system interacting for a flight authorization.
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Citing¶
@inproceedings{SIT178,
author = {LUÍS ANTONIO DE ALMEIDA RODRIGUEZ; JOSÉ MARIA PARENTE DE OLIVEIRA},
title = {AN ONTOLOGY TO SUPPORT BRAZILIAN TRAFFIC FLOW MANAGEMENT BASED ON NASAs ATM REFERENCE MODEL},
booktitle = {Proceedings of the 2022 Air Transportation Symposium},
series = {SITRAER 2022},
year = {2022},
pages = {43-53},
publisher = {SBTA - Brazilian Air Transportation Research Society},
address = {São José dos Campos, Brazil,}
}
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