Data Requests and Scenarios for Data Design of Unobserved Events in Corona-related Confusion Using TEEDA

September 08, 2020 Β· Declared Dead Β· πŸ› 2020 IEEE International Conference on Big Data (Big Data)

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Authors Teruaki Hayashi, Nao Uehara, Daisuke Hase, Yukio Ohsawa arXiv ID 2009.04035 Category cs.HC: Human-Computer Interaction Cross-listed cs.CY Citations 0 Venue 2020 IEEE International Conference on Big Data (Big Data) Last Checked 5 months ago
Abstract
Due to the global violence of the novel coronavirus, various industries have been affected and the breakdown between systems has been apparent. To understand and overcome the phenomenon related to this unprecedented crisis caused by the coronavirus infectious disease (COVID-19), the importance of data exchange and sharing across fields has gained social attention. In this study, we use the interactive platform called treasuring every encounter of data affairs (TEEDA) to externalize data requests from data users, which is a tool to exchange not only the information on data that can be provided but also the call for data, what data users want and for what purpose. Further, we analyze the characteristics of missing data in the corona-related confusion stemming from both the data requests and the providable data obtained in the workshop. We also create three scenarios for the data design of unobserved events focusing on variables.
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