Complex engineered systems evolve, with a tendency toward self-organization, which can, paradoxically, frustrate the aims of those seeking to develop them. The systems engineer, seeking to promote the development in the context of changing and uncertain requirements, is challenged by conceptual gaps that emerge within engineering projects, particularly as they scale up, that inhibit communication among the various stakeholders. Overall optimization, involving multiple criterion, is often expressed in the language of the individual parties, increasing the complexity of the overall situation, subsuming the participants within the evolution of the complex engineered system, containing the objective and subjective in counterproductive or inefficient ways that can arrest healthy development. The conventional pragmatic systems engineering approach to the resolution of such situations is to introduce architectural discipline by way of separation of concerns. In complex engineered systems projects, the crucial interface, at any level of abstraction, is between the technical domain experts and higher level decision makers. Bridging the ensuing conceptual gap requires models and methods that provide communication tools promoting a convergence of the conversation between these parties on a common "common sense" of the underlying reality of the evolving engineered system. In the interest of conceptual clarity, we confine our investigation to a restricted, but important general class of evolving engineered system, information gathering and utilizing systems. Such systems naturally resolve the underlying domain specific measures by reduction into common plausible information measures aimed at an overall sense of informativeness. For concreteness, we further restrict the investigation and the demonstration to a species that is well documented in the open literature: weather radar networks, and in particular to the case of the currently emerging system referred to as CASA. The multiobjective problem of objectively exploring the high dimensionality of the decision space is done using multiobjective genetic algorithms (MOGA), specifically the John Eddy genetic algorithms (JEGA), resulting in well-formed Pareto fronts and sets containing Pareto optimal points within 20% of the ideal point. A visualization technique ensures a clear separation of the subjective criterion provided by the decision makers by superficially adding preferences to the objective optimal solutions. To identify the integrative objective functions and test patterns utilized in the MOGA analysis, explorations of networked weather radar technologies and configuration are completed. The explorations identify trends within and between network topologies, and captures both the robustness and fragility of network based measurements. The information oriented measures of fusion accuracy and precision are used to evaluate pairs of networked weather radars against a standardized low order vortex test pattern, resulting in a metrics for characterizing the performance of dual-Doppler weather radar pairs. To define integrative measures, information oriented measures abstracting over sensor estimators and parameters used to estimate the radial velocity and returned signal from distributed targets, specifically precipitation, are shown to capture the single radar predicted performance against standardized test patterns. The methodology bridges the conceptual gap, based on plausible information oriented measures, standardized with test patterns, and objectively applied to a concrete case with high dimensionality, allowed the conversation to converge between the systems engineer, decision makers, and domain experts. The method is an informative objective process that can be generalized to enable expansion within the technology and to other information gathering and utilizing systems and sensor technologies.

(<特集>情報化時代における教育学の課題) (<Special Issue>Educational Research in the Age of Information Society: Themes and Concerns)

高階主管在面臨日益艱難的經濟情勢與經營環境〈主要是來自消費者(Customers)、競爭(Competition)及變動(Change)等3C的壓力）時，依賴傳統組織架構及報告系統來獲取決策資訊的作法，其有效性正受到強烈的質疑。高階主管資訊系統(Executive　Information Systems,EIS)可說是九○年代電腦資訊系統應用的新領域，它以易學易用的圖形使用者介面、多維分析及往下展開的特性，使高階主管能迅速存取各種攸關其企業成敗的關鍵性資訊。由於其親切易用，近年來EIS的應用更沿組織階層向下發展，成為Everyone Information Systems。在企業發展EIS日趨普遍的情況下，一套系統化的分析設計方法更形重要。 　　然而，在相關的文獻中對EIS的發展方法並沒有提出具體的執行步驟，只有概念性的描述，不易引導開發人員及高階主管將其策略理念轉換為資訊需求，而許多發展EIS失敗的例子，正是由於系統資訊需求不正確、時間與成本超出預算、操之過急及政治因素等所造成。因此實務界人士據其顧問經驗提出一個EIS快速發展方法，強調雛型系統的快速建立以爭取高階主管的持續支持及系統的後續發展。但因仍缺乏系統化的需求分析方法，系統發展者往往需經多次歷練才能領悟其中訣竅，也不易將個人經驗傳授於他人。因此雖然企業組織眾人已感受到EIS的重要性，相關的軟硬體工具也可親易用，而EIS的成功推展卻仍受到相當限制。 　　有鑑於此，本論文以符合文獻中對EIS發展方法之概念性描述的「資訊導向」觀念為基礎，並參考快速雛型系統發展方式，運用「中間擴散」(Middle-Out)方向，整合策略分析及資訊系統規劃的具體作法，發展一套結構化的EIS發展方法，稱為EISAD，含目標分析、關鍵成功要素分析、主要績效指標分析、資料分析、資料庫設計、輸出設計、轉換設計、程序及控制設計等步驟。並以金融業為例：說明此方法論的實際運用過程。以期在理論上對EIS發展方法論，及實務上對金融資訊系統應用層次之提昇有所貢獻。 / Due to the rapid changes of business environment and the increasing customer demands and competition pressure, it is getting important to have Executive Information Systems(EIS) to help executives access to high-level strategic information. Recently, EIS has even evolved down the organization hierarchy to become "Everyone Information Systems". The increasing EIS demand endues the needs for EIS development methodology. However, the literature contains only a few academic studies of EIS development methods which are broad and vague. The EIS development has not been researched in a rigorous and systematic manner. Many practitioners adopt a rapid prototyping approach to attract the executives for further support. Due to the lack of a systematic approach to help extracting the user requirements, it is usually up to the developer's experience to informally address the executives' information needs and this experience is hard to be transferred to others. In this thesis, we propose an EIS development methodology, called EISAD, based on the information-oriented concepts and middle-out system development direction. EISAD integrates related tools in strategic analysis and information systems planning as a structurized EIS development methodology. The step by step explanation of the EISAD is illustrated using a banking example.