COVID-19 data visualization public welfare activity
Open accessAbstract
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.
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Alibaba has integrated AI with cloud computing for supporting coronavirus data analytics.
“For instance, Alibaba has integrated AI with cloud computing for supporting coronavirus data analytics [172].”
From Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey (2021) · cites this paper as [172]
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Cited by 11
- Authors
- Wang, Y., Wang, T., Cui, Y., Mei, H., Wen, X., Lu, J., & Chen, W.
- Affiliations
- Zhejiang University (CN)
- Corresponding author
- Chen, Wei
- Venue
- Visual Informatics
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 4
- Issue
- 3
- Pages
- 51-54
- ISSN
- 2468-502X (ISSN-L)
- PMC
- PMC7486205
- OpenAlex
- W3085893429
- Cited by
- 11
- References
- 0
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2022: 5 · 2021: 2
- FWCI
- 0.87
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Visual Informatics (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Alibaba–Zhejiang University Joint Institute of Frontier Technologies
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
- Social Sciences › Communication › Communication and COVID-19 Impact
- Keywords
- COVID-19 pandemic, public welfare activities, epidemic forecasting, multi-source heterogeneous data, epidemic prevention and control, public information dissemination
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