Preprint Brief Report Version 1 Preserved in Portico This version is not peer-reviewed

COVID 19 Data Visualization through Automatic Phase Detection

Pradipta Biswas
* ORCID logo ,
Kamalpreet Singh Saluja
,
Somnath Arjun
,
LRD Murthy
,
Gowdham Prabhakar
,
Vinay Krishna Sharma
,
Jeevitha Shree DV
Version 1 : Received: 23 May 2020 / Approved: 24 May 2020 / Online: 24 May 2020 (20:23:04 CEST)

A peer-reviewed article of this Preprint also exists.

Biswas, P.; Saluja, K.S.; Arjun, S.; Murthy, L.; Prabhakar, G.; Sharma, V.K.; Dv, J.S. COVID-19 Data Visualization through Automatic Phase Detection. Digital Government: Research and Practice 2020, 1, 1–8, doi:10.1145/3411756. Biswas, P.; Saluja, K.S.; Arjun, S.; Murthy, L.; Prabhakar, G.; Sharma, V.K.; Dv, J.S. COVID-19 Data Visualization through Automatic Phase Detection. Digital Government: Research and Practice 2020, 1, 1–8, doi:10.1145/3411756.

Abstract

This paper 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.

Supplementary and Associated Material

http://cambum.net/Covid19/index.html: COVID 19 Data Analytics Tool

Keywords

Data Visualization; Information Visualization; COVID 19 Pandemic

Subject

Computer Science and Mathematics, Analysis

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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