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Matching Ontologies for Air Traffic Management: A Comparison and Reference Alignment of the AIRM and NASA ATM Ontologies

Authors: A. Vennesland, R. Keller, C. Schütz, E. Gringinger, B. Neumayr
Paper: Schu19b (2019)
Citation: Proceedings of the 14th International Workshop on Ontology Matching (OM 2019), Auckland, October 26th, 2019 collocated with the 18th International Semantic Web Conference (ISWC 2019), Owen G. Glenn Building, The University of Auckland, Auckland, New Zealand, 2019.
Resources: Copy  (In order to obtain the copy please send an email with subject  Schu19b  to dke.win@jku.at)


Abstract (English):

Air traffic management (ATM) relies on the timely exchange of information between stakeholders to ensure safety and efficiency of air traffic operations. In an effort to achieve semantic interoperability within ATM, the Single European Sky ATM Research (SESAR9 program has developed the ATM Information Reference model (AIRM), which individual information exchange models should comply with. An OWL representation of the AIRM – the AIRM Ontology (AIRM-O) – facilitates applications. Independently from the European efforts, the NASA Air Traffic Management Ontology (ATMONTO) has been developed as an RDF/OWL ontology representing ATM concepts to facilitate data integration and analysis in support of NASA aeronautics research. Conceptualization mismatches between the AIRM-O and ATMONTO ontologies – mostly due to different design decisions, but also as a consequence of the different regulatory systems and philosophies underlying ATM in Europe and the United States – pose a challenge to automatic ontology matching algorithms. In this paper, we describe mismatches between AIRM-O and ATMONTO, evaluate performance of automatic matching systems over these ontologies, and provide a manual reference alignment.