The COVID-19 pandemic has been regarded as the most significant global disaster since World Wars I and II. It has caused social and economic disruptions all over the world, as well as millions of deaths. Quarantines and lockdowns have been frequently occurring around the globe. Thus, the COVID-19 pandemic has brought new unknown challenges to everyone.

The global science and medical communities have advanced with timely research and analysis, contributing to our understanding and response to the virus. But much valuable information is still hidden in vast quantities of relevant data, such as statistics, text, speech, etc.

Social media outlets have become an increasingly crucial source of potentially rich information. Such data may provide useful insights regarding the public’s reactions to social dilemmas. Since COVID-19 was never seen before, massive amounts of misinformation could have been rapidly distributed.

This workshop aims to support research to observe impacts of COVID-19, to explore challenges and opportunities for improving safety and health to fight COVID-19, and to encourage collaborations between researchers in Language Processing (NLP), machine learning, deep learning, information visualization, geospatial computing, cloud computing, healthcare, and finance communities to share their recent findings in this active and late-breaking research.

Topics
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We invite submissions related to any aspect of Big Data analytics in theory, methodologies, and applications for COVID-19 topics. List of potential COVID-19 related topics includes, but are not limited to:
• COVID-19 contact tracing and hotspot detection
• COVID-19 tracking, data collection, and data management
• COVID-19 data mining, query processing, and information retrieval
• COVID-19 simulation and modeling
• COVID-19 prediction of positive cases, deaths, etc.
• COVID-19 spatial analysis, mapping, visual analytics
• COVID-19 socioeconomic impact
• COVID-19 and social media (e.g., sentiment analysis, misinformation detection, hate and toxic speech detection, etc.)
• Effects of social distance, mask wearing, or vaccines
• COVID-19 impact on education and distance learning
• COVID-19 disaster response and emergency management

Important Dates
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• First Deadline:
• Oct. 4, 2021: Submission of full papers (7-10 pages) and short papers (5-6 pages)
• Nov 1, 2021: Notification of paper acceptance
• Nov 15, 2021: Camera-ready of accepted papers
• Second Deadline (General Workshop Deadline of IEEE Big Data 2021):
• Oct. 27, 2021: Submission of full papers (7-10 pages) and short papers (5-6 pages)
• Nov 10, 2021: Notification of paper acceptance
• Nov 18, 2021: Camera-ready of accepted papers
• Dec. 15-18, 2021: IEEE Big Data Conference & Workshops (Virtually)

Submission
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Please follow the web link to submit to IEEE Big Data 2021 paper submission site.