Measuring Information Continuity in Evolving Decision Support Systems
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Public works agencies worldwide develop and refine quantitative databases and analysis models for predicting civil infrastructure system performance and estimating investment needs. Databases and models are refined for a variety of reasons including improved technologies for data collection, storage, management and analysis, and changes in the behavior and expectations of infrastructure users. Both implicitly and explicitly, the objective of these refinements is to improve the quality of information for decisionmakers. While each refinement, considered separately, may improve selected attributes of information quality, it may not be clear what is the collective impact of all refinements to a decision support system, between separate instances of information development. This paper addresses the issue of information quality in the context of the evolving infrastructure decision support systems. Specifically, the paper investigates information continuity in the context of evolving analysis models and data. This discussion is potentially useful for public works agencies with an interest monitoring and managing the overall impact of periodic decision support system refinements on the continuity of the resultant information.
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