The recognition of spatial and temporal patterns in the distribution of a pandemic plays a pivotal role in guiding policy approaches to its management, containment and elimination. For this purpose, a database has been built for the COVID-19 pandemic in the Trentino Province, in the eastern Italian alps, near the border between Italy and Austria. The database management system and the WebGIS mapping these data is based on Free and Open Source Software. The Data Base Management System (DBMS) runs on MySQL, available under the GNU General Public License, storing and processing geographic data. A custom procedure has been created to update the dataset, with the capability to import data from suitably formatted spreadsheets by an authenticated administrator. To ensure flexibility and responsiveness on desktop and mobile devices, the WebGIS has been created with a client-side approach, using the Leaflet and Bootstrap JavaScript language libraries, available with Open Source Licenses. These libraries, with additional custom scripts, create the user interface and render geographic data into maps. The exchange of data between the DBMS server and the client is performed using geojson tables. To protect the privacy of the patients, WebGIS users cannot access the source data even though maps and graphs can be downloaded as pictures. Geo-statistical analysis aimed at the detection of spatial and temporal patters is underway

MAPPING COVID-19 EPIDEMIC DATA USING FOSS / Zatelli, P.; Ciolli, M.; Besana, A.; Gabellieri, N.. - In: INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES. - ISSN 2194-9034. - ELETTRONICO. - XLVIII-4/W7-2023:(2023), pp. 261-267. (Intervento presentato al convegno FOSS4G2023 Free and Open Source Software for Geospatial, FOSS4G 2023 tenutosi a Prizren, Kosovo nel 26 June - 2 July 2023) [10.5194/isprs-archives-XLVIII-4-W7-2023-261-2023].

MAPPING COVID-19 EPIDEMIC DATA USING FOSS

Zatelli, P.
;
Ciolli, M.;Besana, A.;Gabellieri, N.
2023-01-01

Abstract

The recognition of spatial and temporal patterns in the distribution of a pandemic plays a pivotal role in guiding policy approaches to its management, containment and elimination. For this purpose, a database has been built for the COVID-19 pandemic in the Trentino Province, in the eastern Italian alps, near the border between Italy and Austria. The database management system and the WebGIS mapping these data is based on Free and Open Source Software. The Data Base Management System (DBMS) runs on MySQL, available under the GNU General Public License, storing and processing geographic data. A custom procedure has been created to update the dataset, with the capability to import data from suitably formatted spreadsheets by an authenticated administrator. To ensure flexibility and responsiveness on desktop and mobile devices, the WebGIS has been created with a client-side approach, using the Leaflet and Bootstrap JavaScript language libraries, available with Open Source Licenses. These libraries, with additional custom scripts, create the user interface and render geographic data into maps. The exchange of data between the DBMS server and the client is performed using geojson tables. To protect the privacy of the patients, WebGIS users cannot access the source data even though maps and graphs can be downloaded as pictures. Geo-statistical analysis aimed at the detection of spatial and temporal patters is underway
2023
Free and Open Source Software for Geospatial (FOSS4G) 2023 – Academic Track
Hannover
Copernicus GmbH
Zatelli, P.; Ciolli, M.; Besana, A.; Gabellieri, N.
MAPPING COVID-19 EPIDEMIC DATA USING FOSS / Zatelli, P.; Ciolli, M.; Besana, A.; Gabellieri, N.. - In: INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES. - ISSN 2194-9034. - ELETTRONICO. - XLVIII-4/W7-2023:(2023), pp. 261-267. (Intervento presentato al convegno FOSS4G2023 Free and Open Source Software for Geospatial, FOSS4G 2023 tenutosi a Prizren, Kosovo nel 26 June - 2 July 2023) [10.5194/isprs-archives-XLVIII-4-W7-2023-261-2023].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/382209
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