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<br />" <br /> <br />e <br /> <br />e <br /> <br />e <br /> <br />003053 <br /> <br />Recently. Geographical Information Systems (GIS) technology has given rise <br />to DSS applications developed entirely "on top of' a commercial GIS. <br />Although there could be some doubts as to whether or not these systems can be <br />considered true DSS. they do offer cenain advantages in that they make use of <br />sophisticated software for the management and evaluation of spatial data, A <br />distinct problem, however, is that the required integration of GIS and <br />simulation modeling has not yet been worked oul. The same applies to the <br />integration of multi-criteria evaluation models, although GIS applications do <br />allow for some simple evaluation techniques based on the analysis of several <br />map oyerlays. For these reasons GIS based systems perform "(very) poor" on <br />model extensibiiity -and'''moderate''.on data extensibility, Development in GIS " <br />systems is relatively cost-effective because of the commercial availability of <br />these systems. Extensions, however, can become very expensive, if possible at <br />alL <br /> <br />Data centered systems center on the data and information available on Ihe <br />specific application domain, Typically this is achieved through the <br />development of a rich geo-relational database containing all relevant <br />information on the environmental system under analysis. The model side of the <br />system is addressed through separation of the state information from the <br />process (behavior) and control information (policy) of that system, The <br />architecture allows addition and extension of both the application domain and <br />the modeling in the system. As such, data centered architectures score "good" <br />on extensibility criteria, Like in case of the purely generic systems, however, <br />extensibility is somewhat traded against performance, Data centered, generic <br />systems are expensive to develop. However. they offer high extensibility and <br />modular development, thus allowing various functions to become available <br />during the course of development for low costs. <br /> <br />From Table 4 it can be seen that Case Specific Systems, Generic/Model <br />Centered Systems, and GIS Based Systems do not perform sufficiently well on <br />both the extensibility and modularity criteria. Poor performance on modularity <br />implies that very little or no products become available during the <br />development process. Only at the end of the development process, when all the <br />coding is done and all data is assembled, do the full functionality become <br />available. Poor extensibility implies that the system cannot evolve easily from <br />both a data and process point of view, This is reflected in the extensibility cost. <br />Moreover. for the GIS based architecture we feel that current GIS technology <br />alone is simply insufficient for representing the large spread of data. models <br />and analysis tools mentioned in the Needs Analysis, <br /> <br />Both the Dedicated DSS and Data Centered Systems. however. although <br />expensive in initial development, offer sufficient opponunities for future <br />extensions. Moreover. they seem to be the only architectures which allow full <br />integration of all needs as elicited from the needs analysis. <br /> <br />GIS Based Systems: <br />EI'aluanon <br /> <br />Data Centered <br />Systems: Evaluation <br /> <br />Recommended <br />Candidate <br />Architectures <br /> <br />DAMES& MOORE/CADSWES-33 <br />