The management of the COVID-19 pandemic presents several unprecedented challenges in different fields, from medicine to biology, from public health to social science, that may benefit from computing methods able to integrate the increasing available COVID-19 and related data (e.g., pollution, demographics, climate, etc.). With the aim to face the COVID-19 data collection, harmonization and integration problems, we present the design and development of COVID-WAREHOUSE, a data warehouse that models, integrates and stores the COVID-19 data made available daily by the Italian Protezione Civile Department and several pollution and climate data made available by the Italian Regions. After an automatic ETL (Extraction, Transformation and Loading) step, COVID-19 cases, pollution measures and climate data, are integrated and organized using the Dimensional Fact Model, using two main dimensions: time and geographical location. COVID-WAREHOUSE supports OLAP (On-Line Analytical Processing) analysis, provides a heatmap visualizer, and allows easy extraction of selected data for further analysis. The proposed tool can be used in the context of Public Health to underline how the pandemic is spreading, with respect to time and geographical location, and to correlate the pandemic to pollution and climate data in a specific region. Moreover, public decision-makers could use the tool to discover combinations of pollution and climate conditions correlated to an increase of the pandemic, and thus, they could act in a consequent manner. Case studies based on data cubes built on data from Lombardia and Puglia regions are discussed. Our preliminary findings indicate that COVID-19 pandemic is significantly spread in regions characterized by high concentration of particulate in the air and the absence of rain and wind, as even stated in other works available in literature.

中文翻译：

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COVID-WAREHOUSE：意大利 COVID-19、污染和气候数据的数据仓库。

COVID-19 大流行的管理在不同领域提出了一些前所未有的挑战，从医学到生物学，从公共卫生到社会科学，这些挑战可能受益于能够整合不断增加的可用 COVID-19 和相关数据（例如，污染）的计算方法。 、人口统计、气候等）。为了解决 COVID-19 数据收集、协调和集成问题，我们介绍了 COVID-WAREHOUSE 的设计和开发，这是一个数据仓库，可对意大利 Protezione Civile 每天提供的 COVID-19 数据进行建模、集成和存储部门以及意大利地区提供的一些污染和气候数据。经过自动 ETL（提取、转换和加载）步骤后，使用维度事实模型（时间和地理位置两个主要维度）来集成和组织 COVID-19 病例、污染措施和气候数据。COVID-WAREHOUSE 支持 OLAP（在线分析处理）分析，提供热图可视化工具，并允许轻松提取所选数据以进行进一步分析。拟议的工具可在公共卫生背景下使用，以强调大流行在时间和地理位置方面的传播方式，并将大流行与特定区域的污染和气候数据相关联。此外，公共决策者可以使用该工具来发现与大流行增加相关的污染和气候条件的组合，因此，他们可以采取相应的行动。讨论了基于伦巴第和普利亚地区数据构建的数据立方体的案例研究。我们的初步研究结果表明，COVID-19 大流行在空气中颗粒物浓度高且无雨无风的地区显着传播，甚至正如其他文献中所述。