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10.3390/ijerph17155596 http://scihub22266oqcxt.onion/10.3390/ijerph17155596 32756428!7432400!32756428     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Environ+Res+Public+Health 2020 ; 17 (15): ä Nephropedia Template TP {{tp|p=32756428|t=2020. COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data |pdf=|usr=}}{{32756428}} gab.com Text COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data JO: Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32756428 #FOAvip 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. Twit Text FOAVip COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data ????Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32756428 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32756428 #FOAvip English Wikipedia <ref>{{Cite pmid|32756428}}</ref> COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data #MMPMID32756428 Agapito G; Zucco C; Cannataro M Int J Environ Res Public Health 2020[Aug]; 17 (15): ä PMID32756428show ga 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. |*Climate[MESH] |*Data Warehousing[MESH] |*Pandemics[MESH] |Betacoronavirus/*isolation & purification[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology/virology[MESH] |Environmental Pollution[MESH] |Humans[MESH] |Italy[MESH] |Pneumonia, Viral/*epidemiology/virology[MESH] |Public Health[MESH] |SARS-CoV-2[MESH]COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and (epmc).pdf DeepDyve Pubget Overpricing