A Comparative Study of Two Complex Ontologies in Air Traffic Management

Abstract

Over the past 25 years, multiple different data models have been introduced to standardize information management and facilitate data exchange and integration in the aviation domain. As a next step in the evolution of aviation data management, ontologies capturing the semantics (concepts, properties, and relationships) have been produced based on those models. In this paper, we describe a study comparing two recently released and independently-developed complex ontologies focused on Air Traffic Management (ATM) - the NASA ATM Ontology and an ontology derived from the ATM Information Reference Model. We develop a methodology for manually comparing two ontologies and identifying what we describe as exact, light, and mismatches between concepts in the two ontologies. We also describe a classification scheme that characterizes mismatches in terms of the general reason for the mismatch. This approach can be applied to improve existing ATM ontologies and foster interoperability, which will benefit aviation stakeholders.