Organization's Orderly Interest Exploration: Inception, Development and Insights of AIAA's Topics Database

Marshall, Jospeh R.; Morris, A. Terry

doi:10.2514/6.2007-2936

Cited by 3 publications

(2 citation statements)

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“…-Critical ontology has been developed for the indexing and searching of meteorological documents. One of the uses of the critical ontology relates to the concepts of specific weather conditions and the relevant scenarios for air traffic alert and collision avoidance systems [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Ontology generation for flight safety messages in air traffic management

Aghdam¹,

Tabbakh²,

Chabok³

et al. 2021

J Big Data

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The analysis of various data is a challenging issue in the field of air traffic flow management (ATFM). Managing a large volume of data and their correct interpretation plays a key role in the prevention of air accidents, human errors, and flight interactions. In general, pilots and flight navigators deal with massive and variety information, including flight safety messages, meteorological messages, aviation notes for air man (NOTAMs) and etc. Therefore relationship between Heterogeneous big data is problem. Recently, the semantic web has been recognized as a novel foundation of knowledge management that relies on ontology (concept modeling language). The present study aimed to propose an efficient infrastructure for ATMs by defining the concepts, rules, and relationships between the concepts related to the scope of flight information. To this end, we designed and implemented the ontology of flight safety messages, which included an important part of flight operation information. In this research, the internet protocol suite (IPS)-based aviation networks and methontology methodology were exploited for the engineering of the ontology of flight messages. In addition, the implementation process was carried out using the Protégé software. The analysis of the system was performed using the actual data of Mashhad Airport, Iran. Finally, the implementation of the ontology of flight messages was demonstrated after a case study of several flight examples. The developed ontology could be incorporated into the foundation of an aeronautical telecommunication network (ATN) aviation network as an application.

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Section: Literature Reviewmentioning

confidence: 99%

Ontology generation for flight safety messages in air traffic management

Aghdam¹,

Tabbakh²,

Chabok³

et al. 2021

J Big Data

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“…In (Putten et al, 2008) a survey on ontologies oriented toward Traffic Flow Management (TFM) in aeronautics is presented, as they aim at providing a Collaborative and multi-agent TFM system. However, XCALIBR (Marshall and Morris, 2007) and AIAA Topic Database (Neff et al, 2007) are of interest for the aviation domain in general. Unfortunately, these knowledge sources aim at new development of component architecture and do not handle the Maintenance part of the avionics works.…”

Section: Avionics and Ontologiesmentioning

confidence: 99%

Avionics Maintenance Ontology Building for Failure Diagnosis Support

Palacios

Lortal

Laudy

et al. 2016

Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management

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In the aviation industry, the delay in maintaining or recovering aircrafts heavily impacts the profit of an airline company. Consequently the maintenance actions identification and planning of aircrafts is crucial. However, due to the complexity of the domain in terms of data sources, distributed systems and information availability, it is hard to provide automatic maintenance support. We propose to use semantic technologies to model the domain at a conceptual level through ontology, thus abstracting from the data sources and the maintenancers'uses and jobs. In this manner the information relevant for characterizing failures and maintenance events is encapsulated and provided to end users via an easier access, which otherwise would be inaccessible or would require expert analysis to obtain. Such a formal model of the domain can furthermore enable automated reasoning for maintenance discovery and failure causes detection by integrating a large amount of background contextual information scattering in different resources. In this paper we provide the rationale of the Avionics Maintenance ontology i.e. how we built it through expert knowledge and alignment of different sources and an ontology alignment evaluation tool.

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