Visualization plays an important role in epidemic time series analysis and forecasting. Viewing time series data plotted on a graph can help researchers identify anomalies and unexpected trends that could be overlooked if the data were reviewed in tabular form. However,there are challenges in reviewing data sets from multiple data sources (data can be aggregated in different ways and measure different criteria which can make a direct comparison between time series difficult. In the face of an emerging epidemic, the ability to visualize time series from various sources and organizations and to reconcile these datasets based on different criteria could be key in developing accurate forecasts and identifying effective interventions. Many tools have been developed for visualizing temporal data; however, none yet supports all the functionality needed for easy collaborative visualization and analysis of epidemic data. In this thesis, we develop EpiViewer, a time series exploration dashboard where users can upload epidemiological time series data from a variety of sources and compare, organize, and track how data evolves as an epidemic progresses. EpiViewer provides an easy-to-use web interface for visualizing temporal datasets either as line charts or bar charts. The application provides enhanced features for visual analysis, such as hierarchical categorization, zooming, and filtering, to enable detailed inspection and comparison of multiple time series on a single canvas. Finally, EpiViewer provides a built-in statistical Epi-features module to help users interpret the epidemiological curves. / Master of Science / We present EpiViewer, a time series exploration dashboard where users can upload epidemiological time series data from a variety of sources and compare, organize, and track how data evolves as an epidemic progresses. EpiViewer is a single page web application that provides a framework for exploring, comparing, and organizing temporal datasets. It offers a variety of features for convenient filtering and analysis of epicurves based on meta-attribute tagging. EpiViewer also provides a platform for sharing data between groups for better comparison and analysis.

如同硬體元件的模組化，軟體元件的模組化在應用系統開發領域也取得的普遍的認知。以Web為基礎的應用系統在分散式運算環境中日趨重要。美國昇陽公司開發Servlet & JSP技術來作為網際網路應用系統開發的工具。在本研究中採用 Model-View-Controller架構，就網際網路應用系統開發中的模組化趨勢透過使用 Servlet & JSP技術來加以檢驗。為了實作的需要，採用了農民曆法轉換程式來作為處理Model部份之運算邏輯。最後並自然導引出從系統開發過成中合理有效之人力資源配置原則。 / Just like the modularization of hardware component, the trend of modularization of software component has gained also general recognition in the field of application system development. Recently, web-based application has become more and more important in the distributed computing environment. The Sun Inc. has been developing the servlet & JSP technology to be used for developing interactive web application. In this research, a software component study following the model-view-Controller architecture is inspected to verify the software modularization trend in the web application development using servlet & JSP technology. For implementation purpose, a business logic dealing with Chinese Calendar Transformation is selected as the model part. The implication of human resource allocation from point of view the application system development is also outlined as a deductive conclusion.