Event Details
Identified as Coronavirus (2019-nCov), this new virus has recently spread from Wuhan to other regions of China as well as about 24 countries. The virus presented unprecedented challenges, but also provided a rare opportunity for studying it that, if seized, will help us understand future risks. Researchers from the Center for Geographical Analysis at Harvard University, the Geo-computation Center for Social Sciences at Wuhan University, RMDS Lab, and the Chinese Data Institute are working together to build a web-based platform for sharing research data on 2019-nCoV. This talk will introduce the available resources for 2019-nCoV studies, which include the daily statistics on the virus cases, inter-region migration data, local health facilities, social media data as well as demographic and business data from the population and economic censuses integrated with the administrative maps. It will discuss how to get access to these data using web technology and GIS tools. It will also introduce the on-going initiative of China Data Lab, a cloud based platform that offers an integrated environment for data and tools for workflow-based virus data analysis. A questions and answers session will follow the online
- Thursday — February 20, 2020
5:00PM - 6:00PM
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The Organizer
Research Methods and Data Science Meetup
This Research Methods and Data Science (RMDS) meetup group is devoted to make big data & AI useful, and to promote big data technologies. It is a meet-up group bringing together people from research methodology, data science, data professional services, AI and computing in the greater Los Angeles area.
The focus of the group is about utilizing big data & AI technologies to improve data analytics & research for social good, and to promote research methods and data science innovation. On a regular base, we run workshops on big data analytics that can be applied to model and visualize open data and other complicated big data sets. Also, we will organize special meetings to discuss special data science projects, as well as data science automation and augmentation.