The Construction of an Ontology-Based Knowledge Management Model for Departure Procedures

Abstract

With increased global economic development, the air traffic volume (including passengers and parcels) increases every year. Thus, the business-related load on air traffic controllers becomes heavier, which influences their need for frequent learning and training opportunities. Therefore, the only solution is to enhance the performance of the training for the air traffic controllers (ATCs) and to build uniform training procedures and standardized training content, which constitute a shared framework with ontology knowledge. Taking departure operation control processes as an example, the research analyzes an aviation organization framework, with information communication procedures and relevant knowledge assets from the viewpoint of departure processes, to explore a knowledge management model of aviation control. This research studies how explicit knowledge is transformed by CommonKADS methodology using the CommonKADS sheet, and the Unified Modeling Language (UML) graph presentation and ontology model are discussed in this research. This analysis procedure can be applied to the systematic analysis and establishment of similar business-based information systems, allowing this research result to be further shared in different industries.

Research on the Impact of the Knowledge Graph on Public Service Quality

“…The source of these entities relies on structured data in highquality databases. The bottom-up construction method requires us to extract entities from public external data (Su et al, 2016). The ontology model can be constructed after selecting the part with higher credibility and adding the database.…”

“…We need to determine what type of knowledge graph is constructed, including the definition of class relations, class domains, and class attributes (Su et al, 2016). Class relation contains the active and passive relationship between two entities.…”

“…First of all, we can obtain data from the records of previous government services and crawl data through existing databases. These two methods are the embodiment of the reusing and transformation of existing ontology (Su et al, 2016). Another broader and commonly used way is to crawl semi-structured data or unstructured data on society and the Internet.…”

Development methodologies for ontology‐based knowledge management systems: A review

“…In other OKMS developed in the agriculture management domain (Zheng et al, 2012), the following ICT were used: intelligent sourcing of concepts using ML mechanisms (decision trees, and KNN [k‐nearest neighbour]), ontology web language (OWL) ontology representation, rule‐based KBS using semantic web rule language (SWRL), Jess rule‐based inference engine, and a web‐based GUI. In contrast, in an OKMS developed in the aviation operations domain (Su et al, 2016), a single tool Protégé OWL provided the OWL ontology representation, and OWL visualization and consulting tools. In a final example of an OKMS implemented in the domain of civil engineering (Xu et al, 2019), the ICT used were OWL ontology and resource description framework scheme (RDFS) representation, rule‐based KBS using SWRL, JESS rule‐based inference engine, and SPARQL protocol and RDF query language (SPARQL) as the query language.…”

“…Satisfactory OKMS real‐world cases have been reported in diverse knowledge‐intensive tasks domains such as chemical process design (Brandt et al, 2008), agriculture management (Zheng et al, 2012), financial analysis (Hu et al, 2014), software development (Misra & Misra, 2014), industrial design (Yan et al, 2015), aviation operations (Su et al, 2016), medical therapy (Asprino et al, 2019), and civil engineering (Xu et al, 2019), among other relevant domains. Overall, OKMSs have provided to organizational knowledge workers functional capabilities such as: (1) provision of computer‐based accessible repositories of taxonomies; (2) support for semantic content in databases; (3) re‐utilization, adaptation, and/or extension of knowledge bases; (4) visualization of complex knowledge structures with ontology navigation and visualization tools; (5) white‐box models in both human and machine reading format of the knowledge used in the system; and (6) distribution and access through web platforms.…”