Any data analysis, especially the data sets that may be changing often or in real-time, consists of at least three important synchronized components: i) figuring out what to infer (objectives), ii) analysis or computation of objectives, and iii) understanding of the results which may require drill-down and/or visualization. There is a lot of attention paid to the first two of the above components as part of research whereas the understanding as well as deriving actionable decisions is quite tricky. Visualization is an important step towards both understanding (even by non-experts) and inferring the actions that need to be taken. As an example, for Covid-19, knowing regions (say, at the county or state level) that have seen a spike or prone to a spike in cases in the near future may warrant additional actions with respect to gatherings, business opening hours, etc. This paper focuses on an extensible architecture for visualization of base as well as analyzed data. This paper proposes a modular architecture of a dashboard for user-interaction, visualization management, and complex analysis of base data. The contributions of this paper are: i) extensibility of the architecture providing flexibility to add additional analysis, visualizations, and user interactions without changing the workflow, ii) decoupling of the functional modules to ease and speedup development by different groups, and iii) address efficiency issues for display response time. This paper uses Multilayer Networks (or MLNs) for analysis. To showcase the above, we present the implementation of a visualization dashboard, termed CoWiz++ (for Covid Wizard), and elaborate on how web-based user interaction and display components are interfaced seamlessly with the back end modules.

中文翻译：

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用于可视化基础数据和分析数据的可扩展仪表板架构

任何数据分析，尤其是可能经常或实时变化的数据集，至少包含三个重要的同步组件：i) 弄清楚要推断什么（目标），ii) 分析或计算目标，以及 iii)了解可能需要深入分析和/或可视化的结果。作为研究的一部分，对上述组件中的前两个组件给予了很多关注，而理解和得出可操作的决策则非常棘手。可视化是理解（即使是非专家）和推断需要采取的行动的重要一步。例如，对于 Covid-19，了解在不久的将来出现病例激增或可能出现激增的地区（例如，在县或州一级）可能需要对聚会采取额外的行动，营业时间等。本文重点介绍一种可扩展的架构，用于基础数据和分析数据的可视化。本文提出了一种用于用户交互、可视化管理和基础数据复杂分析的仪表板的模块化架构。本文的贡献是：i) 架构的可扩展性提供了在不改变工作流的情况下添加额外分析、可视化和用户交互的灵活性，ii) 功能模块的解耦以简化和加速不同组的开发，以及 iii) 解决显示响应时间的效率问题。本文使用多层网络（或 MLN）进行分析。为了展示上述内容，我们展示了可视化仪表板的实现，称为 CoWiz++（用于 Covid 向导），