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COVID-19 data visualization public welfare activity
The coronavirus disease 2019 (COVID-19) pandemic started in early 2020. At the beginning of February, a public welfare activity in epidemic data visualization, jointly launched by China Computer Federation (CCF) (CCF) CAD & CG Technical Committee, Alibaba Cloud Tianchi (Alibaba Cloud Tianch), Ji...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s) Published by Elsevier B.V. on behalf of Zhejiang University and Zhejiang University Press.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486205/ http://dx.doi.org/10.1016/j.visinf.2020.09.003 |
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author | Wang, Yiting Wang, Ting Cui, Ying Mei, Honghui Wen, Xiao Lu, Jinzhi Chen, Wei |
author_facet | Wang, Yiting Wang, Ting Cui, Ying Mei, Honghui Wen, Xiao Lu, Jinzhi Chen, Wei |
author_sort | Wang, Yiting |
collection | PubMed |
description | The coronavirus disease 2019 (COVID-19) pandemic started in early 2020. At the beginning of February, a public welfare activity in epidemic data visualization, jointly launched by China Computer Federation (CCF) (CCF) CAD & CG Technical Committee, Alibaba Cloud Tianchi (Alibaba Cloud Tianch), JiqiZhixin (JiqiZhixin), Alibaba Cloud DataV (Alibaba Cloud DataV), and DataWhale (DataWhale), was launched with the theme “Fighting the Epidemic with One Mind and Talents like Tianchi.” Developers in general are expected to focus on several demand scenarios, such as epidemic situation display, epidemic popular science, trend prediction, material-supply situation, and rework and return situation of employees from all sectors and areas, to discover the relationship between complex heterogeneous multi-source data, develop various upbeat works and present useful information to the public in a coherent manner. The entry works take the form of data visualization and are divided into two categories: popular science publicity and application scenarios. The popular science publicity category includes works for the public, focused on epidemic situation display, epidemic popular science publicity, epidemic prevention and control, and others. The application scenario category consists of the works of frontline officers, which can provide anti-epidemic workers with effective data tools for efficient and intuitive epidemic analysis; offer reliable, understandable, and easily transmitted information for disease prevention; and assist governments, enterprises, and institutions in the fight against COVID-19. |
format | Online Article Text |
id | pubmed-7486205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Author(s) Published by Elsevier B.V. on behalf of Zhejiang University and Zhejiang University Press. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74862052020-09-14 COVID-19 data visualization public welfare activity Wang, Yiting Wang, Ting Cui, Ying Mei, Honghui Wen, Xiao Lu, Jinzhi Chen, Wei Visual Informatics Article The coronavirus disease 2019 (COVID-19) pandemic started in early 2020. At the beginning of February, a public welfare activity in epidemic data visualization, jointly launched by China Computer Federation (CCF) (CCF) CAD & CG Technical Committee, Alibaba Cloud Tianchi (Alibaba Cloud Tianch), JiqiZhixin (JiqiZhixin), Alibaba Cloud DataV (Alibaba Cloud DataV), and DataWhale (DataWhale), was launched with the theme “Fighting the Epidemic with One Mind and Talents like Tianchi.” Developers in general are expected to focus on several demand scenarios, such as epidemic situation display, epidemic popular science, trend prediction, material-supply situation, and rework and return situation of employees from all sectors and areas, to discover the relationship between complex heterogeneous multi-source data, develop various upbeat works and present useful information to the public in a coherent manner. The entry works take the form of data visualization and are divided into two categories: popular science publicity and application scenarios. The popular science publicity category includes works for the public, focused on epidemic situation display, epidemic popular science publicity, epidemic prevention and control, and others. The application scenario category consists of the works of frontline officers, which can provide anti-epidemic workers with effective data tools for efficient and intuitive epidemic analysis; offer reliable, understandable, and easily transmitted information for disease prevention; and assist governments, enterprises, and institutions in the fight against COVID-19. The Author(s) Published by Elsevier B.V. on behalf of Zhejiang University and Zhejiang University Press. 2020-09 2020-09-12 /pmc/articles/PMC7486205/ http://dx.doi.org/10.1016/j.visinf.2020.09.003 Text en © 2020 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Wang, Yiting Wang, Ting Cui, Ying Mei, Honghui Wen, Xiao Lu, Jinzhi Chen, Wei COVID-19 data visualization public welfare activity |
title | COVID-19 data visualization public welfare activity |
title_full | COVID-19 data visualization public welfare activity |
title_fullStr | COVID-19 data visualization public welfare activity |
title_full_unstemmed | COVID-19 data visualization public welfare activity |
title_short | COVID-19 data visualization public welfare activity |
title_sort | covid-19 data visualization public welfare activity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486205/ http://dx.doi.org/10.1016/j.visinf.2020.09.003 |
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