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

TL;DR

This paper explores data exchange challenges during COVID-19 by using TEEDA to analyze data requests, missing data characteristics, and creating scenarios for unobserved event data design.

Contribution

It introduces TEEDA as a platform for externalizing data requests and analyzes missing data characteristics in the context of COVID-19.

Findings

Identification of key data request patterns during the pandemic

Analysis of missing data characteristics related to COVID-19

Development of scenarios for unobserved event data design

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.