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COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data
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, demogr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7432400/ https://www.ncbi.nlm.nih.gov/pubmed/32756428 http://dx.doi.org/10.3390/ijerph17155596 |
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author | Agapito, Giuseppe Zucco, Chiara Cannataro, Mario |
author_facet | Agapito, Giuseppe Zucco, Chiara Cannataro, Mario |
author_sort | Agapito, Giuseppe |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7432400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74324002020-08-24 COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data Agapito, Giuseppe Zucco, Chiara Cannataro, Mario Int J Environ Res Public Health Article 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. MDPI 2020-08-03 2020-08 /pmc/articles/PMC7432400/ /pubmed/32756428 http://dx.doi.org/10.3390/ijerph17155596 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Agapito, Giuseppe Zucco, Chiara Cannataro, Mario COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data |
title | COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data |
title_full | COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data |
title_fullStr | COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data |
title_full_unstemmed | COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data |
title_short | COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data |
title_sort | covid-warehouse: a data warehouse of italian covid-19, pollution, and climate data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7432400/ https://www.ncbi.nlm.nih.gov/pubmed/32756428 http://dx.doi.org/10.3390/ijerph17155596 |
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