Efficient Integration of Complex Information Systems in the ATM Domain with Explicit Expert Knowledge Models

Abstract

The capability to provide a platform for flexible business services in the Air Traffic Management (ATM) domain is both a major success factor for the ATM industry and a challenge to integrate a large number of complex and hetero-geneous information systems. Most of the system knowledge needed for integra-tion is not available explicitly in machine-understandable form, resulting in time-consuming and error-prone human integration tasks. In this chapter we introduce and evaluate a knowledge-based approach, "Semantically-Enabled Externalization of Knowledge" for the ATM domain (SEEK-ATM), which explicitly models a) expert knowledge on specific heterogeneous systems and integration require-ments; and b) allows mapping of the specific knowledge to the general ATM problem domain knowledge for semantic integration. The domain-specific model-ing enables a) to verify the integration knowledge base as requirements specifica-tion for later design of technical systems integration and b) to provide an applica-tion program interface (API) to the problem space knowledge to facilitate tool support for efficient and effective systems integration. Based on an industry case study, we evaluate effects of the proposed SEEK-ATM approach in comparison to traditional system integration approaches in the ATM domain. Major advantages of the novel approach are the efficient derivation of technical configurations and automated quality assurance of the expert knowledge models.