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An Ontology is a formal explicit description of concepts in a domain of discourse. An Ontology models concepts and their relationships. They are a powerful way to organize query formulation and semantic reconciliation in large distributed information environments. They can capture both the structure and semantics of information environments, so an Ontology-based search engine can handle both simple keyword-based queries as well as complex queries on structured data. Ontology-based interoperation is especially good at dealing with inconsistent semantics. An Ontology provides a commonly agreed understanding of a domain, which is reused and shared across applications and groups.

Why use an Ontology?

• To Share common understanding of the structure of information among people or software agents
• To enable reuse of domain knowledge
• To make domain assumptions explicit
• To separate domain knowledge from the operational knowledge
• To analyze domain knowledge
• The following figure presents a high level representation of a knowledge base taxonomy for aviation. The knowledge base taxonomy is created based on the needs of the application domain; “aviation policy making and concept validation.” An application driven knowledge framework establishes the overall ontology structure and relationships in the knowledge base. The upper level of the knowledge base contains representations for supporting aviation policy, program & funding decisions.

The policy level Ontology breaks down into Institution, Safety, Security, Economic, Environmental, and Operational Ontology. Each Ontology is interdependent. The policy level Ontology relies on a more generalized domain Ontology presented at lower levels. At the second level of the knowledge base, aviation user/providers roles and NAS operations are mapped to a NAS domain related Air Traffic Services (ATS) Ontology. Each ATS Ontology mirrors corresponding NAS services. The next level in the knowledge base corresponds to domain physical components such as Airspace, Airports, Aircraft, and Controllers. Each physical component is mapped to its high-level behavior Ontology. This high level Ontology provides a level of fidelity required to meet the application need of the knowledge base. The fourth level of the knowledge base provides components for temporal and spatial representations. These components contain an Ontology to represent externally abstracted and filtered; aviation models, scenarios, and simulation-run data. The lowest level in the knowledge base represents fundamental knowledge representational components that are used throughout the knowledge base.

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