| Summary: | Approved for public release; distribution is unlimited === This thesis describes a component-based methodology for developing a new class of systems called spatial decision support systems (SDSS). The methodology is presented within the context of the development of the ARIES (army Reserve Installation Evaluation System) software application, an SDSS designed to evaluate and compare site desirability for Army Reserve unit locations. The ARIES SDSS consists of a flexible component-based architecture that seamlessly integrates a user interface, GIS, multi-criteria decision model with associated DSS, and data warehouse. To build the SDSS, the ARIES developers introduced a new architectural paradigm, undertaking a collaborative approach with U.S. Army Reserve Command (USARC) decision-makers to rapidly prototype ARIES using component-based technologies. The developers implemented several domain specific architectures using a formalized proof of concept heuristic, Concept to Code (C2C), which conceptualizes user requirements in architectural terms, and migrating legacy data sources into a spatial data warehouse. C2C allowed the resultant ARIES application to be conceptualized initially in general terms, and then specialized architecturally around existing off the shelf components, as design requirements were collaboratively prototyped and implemented within the existing USARC information system infrastructure. C2C facilitated the complete development of a complex, map-based system and accompanying data warehouse in the span of a few months with a technical team of three analysts and programmers. Significant system performance gains resulted from instituting a Migration Architecture System (MARS) engine to extract and spatially enable relevant data sources for geographic querying. Additional performance enhancements were also obtained through the use of rapid, componentgt\h(0h9,g(, i-$i-wh*a*BC?G8*
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