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The many advantages of Distributed Database (DDB) systems can only be achieved through proper DDB designs. Since designing a DDB is very difficult and expert designers are relatively few in number, "good" DDB design methodologies and associated computer-aided design tools are needed to help designers cope with design complexity and improve their productivity. Unfortunately, previous DDB design research focused on solving subproblems of data distribution design in isolation. As a result, past research on a general DDB design methodology offered only methodological frameworks that, at best, aggregate a set of non-integrated design techniques. The conventional separation of logical design from fragmentation design is problematic, but has not been fully analyzed. This dissertation presents the SEER-DTS methodology developed for the purposes of overcoming the methodological inadequacies of conventional design methodologies, resolving the DDB design problem in an integrated manner and facilitating design automation. It is based on a static semantic data model, SEER (Synthesized Extended Entity-Relationship Model) and a dynamic data model, DTS (Distributed Transaction Scheme), which together provide complete and consistent modeling mechanisms for acquiring/representing DDB design inputs and facilitating DDB schema design. In this methodology, requirement/distribution analysis and conceptual design are integrated and logical and fragmentation designs are combined. "Semantics-based" design techniques have been developed to allow for end-user design specifications and seamless design schema transformations, thereby simplifying design tasks. Towards our ultimate goal of design automation, an architectural framework for a computer-aided DDB design system, Auto-DDB, was formulated and the system was prototyped. As part of the developmental effort, a real-world DDB design case study was conducted to verify the applicability of the SEER-DTS methodology in a manual design mode. The results of a laboratory experiment showed that the SEER-DTS methodology produced better design outcomes (in terms of design effectiveness and efficiency) than a Conventional Best methodology performed by non-expert designers in an automated design mode. However, no statistically significant difference was found in user-perceived ease of use.

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