A metadata architecture for mediated integration of product usage data [diagnostic maturation analysis]

The goal of the diagnostic maturation process is to minimize system life cycle cost; once a diagnostic design has been deployed and begun operation it must be monitored for correctness and effectiveness within the context of its operational environment. The product data that is typically required for maturation analysis is generally stored in disparate heterogeneous data systems - this makes access, retrieval, and integration of the requisite information a costly and often incomplete process. A key issue when accessing heterogeneous information sources is how to bridge the differences in conceptual vocabulary that exist. This suggests a degree of semantic integration is required that allows the extraction and combination of information provided by the data sources. The approach should also provide a means to support the fusion of the information obtained from those sources with the knowledge of the system design and diagnostic engineers. This paper describes a metadata architecture that (1) supports mediated semantic integration of heterogeneous product data systems and (2) enables development of knowledge representations to support development of analytical maturation applications. The resulting synthesis of logical and ontological principles provides a strong basis for effective computational support for maturation application development.