ABSTRACT: The proposed Next Generation Air Transportation System (NextGen) will dramatically improve our nation’s ability to respond to change, reduce costs and accelerate the development and delivery of network-centric Air Traffic Management (ATM) capabilities for the National Airspace System (NAS). This paper presents an overall methodology for the efficient, effective and repeatable application of Semantic Data Services (SDS) to address the fundamental data problems exposed by Service Oriented Architecture (SOA) implementations. The SDS framework presented in this paper takes advantage of new/emerging semantic technologies and standards for data enrichment, mediation, representation, fusion, access, visualization and security. The primary differentiators are the methods and processes used to extend the traditional SOA data layer through the pragmatic application of semantic technology. The SDS framework and supporting methodology presented herein addresses the inherent challenges of the “data problem”, setting the stage for “realistic” SOA manifestations of the Department of Defense’s (DoD’s) Net-Centric Data Strategy that maximizes the decoupling of mission-critical data from the user interfaces and software applications, and operationalizes the data in terms of a shared, interoperable vocabulary across ATM Communities of Interest (COI).

The SDS framework leverages ontologies to serve as the basis for model-driven data integration, enrichment and fusion, adding cohesion and value to the fundamental enterprise information fabric. For example, semantic representations of data models such as the National Information Exchange Model (NIEM), Maritime Information Exchange Model (MIEM), the Universal Core and the Joint Consultation Command and Control Information Exchange Data Model (JC3IEDM) serve as pluggable data fusion ontologies. Each deployed instance of SDS can serve as reusable infrastructure for a variety of services and applications that are beneficial to a COI and the broader NextGen SOA ecosystem. The abstraction provided by SDS adds substantial power for reasoning and correlating information in an automated fashion.

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