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A data visualization interactive exploration of human mobility data during the COVID-19 outbreak: a case study

机译:在COVID-19爆发期间的数据可视化交互式探索人类流动性数据:一个案例研究

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In this paper, we present a real-world study where a community-based tracking infrastructure has been put to good use for understanding human mobility during the COVID-19 outbreak, in order to contrast its diffusion. In particular, the infrastructure, deployed in 81 points of interests (POIs) across the Madeira Islands (Portugal), can collect a massive amount of spatio-temporal data, that can be enriched with potentially independent data sources of additional values (such as the official number of people affected by the coronavirus disease), and crowdsourced data collected by citizens. These enriched hyper-local data can be manipulated to provide i) stakeholders with a visual tool to contrast COVID-19 diffusion through human mobility monitoring, and ii) citizens with an interactive tool to visualize, in real-time, how crowded is a POI and plan their daily activities, and contribute to the data acquisition. Here we present the deployed community-based infrastructure and the data visualization interactive web application, designed to extract meaningful information from human mobility data during the COVID-19 outbreak.
机译:在本文中,我们进行了一项现实世界的研究,其中充分利用了基于社区的跟踪基础结构来了解COVID-19爆发期间的人员流动性,以对比其传播。特别是,在马德拉群岛(葡萄牙)的81个兴趣点(POI)中部署的基础架构可以收集大量的时空数据,这些数据可以通过可能具有附加价值的潜在独立数据源进行充实(例如受冠状病毒病感染的官方人数)以及市民收集的众包数据。可以操纵这些丰富的超本地数据,以为i)利益相关者提供一种可视化工具,以通过人类移动性监测来对比COVID-19的扩散,以及ii)市民提供一种交互式工具,以实时可视化POI的拥挤程度并计划他们的日常活动,并为数据采集做出贡献。在这里,我们展示了已部署的基于社区的基础架构和数据可视化交互式Web应用程序,旨在从COVID-19爆发期间的人员流动数据中提取有意义的信息。

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