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The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic

Distributed spatial infrastructures leveraging cloud computing technologies can tackle issues of disparate data sources and address the need for data‐driven knowledge discovery and more sophisticated spatial analysis central to the COVID‐19 pandemic. We implement a new, open source spatial middlewar...

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Autores principales: Kolak, Marynia, Li, Xun, Lin, Qinyun, Wang, Ryan, Menghaney, Moksha, Yang, Stephanie, Anguiano, Vidal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8420397/
https://www.ncbi.nlm.nih.gov/pubmed/34512108
http://dx.doi.org/10.1111/tgis.12786
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author Kolak, Marynia
Li, Xun
Lin, Qinyun
Wang, Ryan
Menghaney, Moksha
Yang, Stephanie
Anguiano, Vidal
author_facet Kolak, Marynia
Li, Xun
Lin, Qinyun
Wang, Ryan
Menghaney, Moksha
Yang, Stephanie
Anguiano, Vidal
author_sort Kolak, Marynia
collection PubMed
description Distributed spatial infrastructures leveraging cloud computing technologies can tackle issues of disparate data sources and address the need for data‐driven knowledge discovery and more sophisticated spatial analysis central to the COVID‐19 pandemic. We implement a new, open source spatial middleware component (libgeoda) and system design to scale development quickly to effectively meet the need for surveilling county‐level metrics in a rapidly changing pandemic landscape. We incorporate, wrangle, and analyze multiple data streams from volunteered and crowdsourced environments to leverage multiple data perspectives. We integrate explorative spatial data analysis (ESDA) and statistical hotspot standards to detect infectious disease clusters in real time, building on decades of research in GIScience and spatial statistics. We scale the computational infrastructure to provide equitable access to data and insights across the entire USA, demanding a basic but high‐quality standard of ESDA techniques. Finally, we engage a research coalition and incorporate principles of user‐centered design to ground the direction and design of Atlas application development.
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spelling pubmed-84203972021-09-07 The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic Kolak, Marynia Li, Xun Lin, Qinyun Wang, Ryan Menghaney, Moksha Yang, Stephanie Anguiano, Vidal Trans GIS Special Section: Cyberinfrastructure and Intelligent Spatial Decision Support Systems Distributed spatial infrastructures leveraging cloud computing technologies can tackle issues of disparate data sources and address the need for data‐driven knowledge discovery and more sophisticated spatial analysis central to the COVID‐19 pandemic. We implement a new, open source spatial middleware component (libgeoda) and system design to scale development quickly to effectively meet the need for surveilling county‐level metrics in a rapidly changing pandemic landscape. We incorporate, wrangle, and analyze multiple data streams from volunteered and crowdsourced environments to leverage multiple data perspectives. We integrate explorative spatial data analysis (ESDA) and statistical hotspot standards to detect infectious disease clusters in real time, building on decades of research in GIScience and spatial statistics. We scale the computational infrastructure to provide equitable access to data and insights across the entire USA, demanding a basic but high‐quality standard of ESDA techniques. Finally, we engage a research coalition and incorporate principles of user‐centered design to ground the direction and design of Atlas application development. John Wiley and Sons Inc. 2021-06-30 2021-08 /pmc/articles/PMC8420397/ /pubmed/34512108 http://dx.doi.org/10.1111/tgis.12786 Text en © 2021 The Authors. Transactions in GIS published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Special Section: Cyberinfrastructure and Intelligent Spatial Decision Support Systems
Kolak, Marynia
Li, Xun
Lin, Qinyun
Wang, Ryan
Menghaney, Moksha
Yang, Stephanie
Anguiano, Vidal
The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic
title The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic
title_full The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic
title_fullStr The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic
title_full_unstemmed The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic
title_short The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic
title_sort us covid atlas: a dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic
topic Special Section: Cyberinfrastructure and Intelligent Spatial Decision Support Systems
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8420397/
https://www.ncbi.nlm.nih.gov/pubmed/34512108
http://dx.doi.org/10.1111/tgis.12786
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