COVID-19 Data Visualization through Automatic Phase Detection-Reference-Cited by-同舟云学术

COVID-19 Data Visualization through Automatic Phase Detection

Published:2020-10-31 Issue:4 Volume:1 Page:1-8
ISSN:2691-199X
Container-title:Digital Government: Research and Practice
language:en
Short-container-title:Digit. Gov.: Res. Pract.

Author:

Biswas Pradipta¹^ORCID,Saluja Kamalpreet Singh¹,Arjun Somnath¹,Murthy Lrd¹,Prabhakar Gowdham¹,Sharma Vinay Krishna¹,Dv Jeevitha Shree¹

Affiliation:

1. Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore, India

Abstract

This article presents a new interactive visualization system to represent and compare rate of spread of COVID-19 pandemic across different countries over time. We surveyed existing visualization techniques used in various websites and media outlets and introduced use of a knee detection algorithm that divides the exponential spread in multiple linear components. A set of use cases demonstrates the utility of the system in comparing the spread across different countries for both analysis and prediction.

Publisher

Association for Computing Machinery (ACM)

Subject

General Medicine

Link

https://dl.acm.org/doi/pdf/10.1145/3411756

Reference17 articles.

1. Wade Fagen-Ulmschneider. 2020. 91-DIVOC. Flip the Script on COVID-19. Retrieved from 91-divoc.com/pages/covid-visualization/. Wade Fagen-Ulmschneider. 2020. 91-DIVOC. Flip the Script on COVID-19. Retrieved from 91-divoc.com/pages/covid-visualization/.

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