CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics: A Case Study of COVID-19

Su Yeon Han; Joon Seok Kim; Yuqin Jiang; Jeon Young Kang; Jinwoo Park; Chaeyeon Han; Alexander Michels; Shaowen Wang

doi:10.1145/3681777.3698474

CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics: A Case Study of COVID-19

Su Yeon Han, Joon Seok Kim, Yuqin Jiang, Jeon Young Kang, Jinwoo Park, Chaeyeon Han, Alexander Michels, Shaowen Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The COVID-19 pandemic underscored the critical need for effective disease mapping tools, essential for tracking infectious diseases. Following the WHO's pandemic declaration in March 2020, numerous technological solutions emerged to map cases, assess risk factors, and monitor mobility. However, there remains a shortage of reusable, open-source geovisual analytics tool for rapid response to future pandemics. To address this gap, we developed an innovative open-source JavaScript-based geovisual analytics tool as part of the CyberGIS-Vis project. This paper introduces two visualization modules of CyberGIS-Vis, showcasing their use in visualizing spatiotemporal COVID-19 data by integrating advanced cyberGIS and online visualization with robust analytics for geospatial knowledge discovery.

Original language	English
Title of host publication	SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology
Editors	Joon-Seok Kim, Taylor Anderson, Max Lau, Amira Roess, Andreas Zufle
Publisher	Association for Computing Machinery, Inc
Pages	19-22
Number of pages	4
ISBN (Electronic)	9798400711534
DOIs	https://doi.org/10.1145/3681777.3698474
Publication status	Published - 25 Oct 2024
Event	5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology, SPATIALEPI 2024 - Atlanta, United States Duration: 29 Oct 2024 → …

Publication series

Name	SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology

Conference

Conference	5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology, SPATIALEPI 2024
Country/Territory	United States
City	Atlanta
Period	29/10/24 → …

Bibliographical note

Publisher Copyright:
© 2024 Copyright held by the owner/author(s).

Keywords

COVID-19
CyberGIS
geovisual analytics
visualization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3681777.3698474

Cite this

Han, S. Y., Kim, J. S., Jiang, Y., Kang, J. Y., Park, J., Han, C., Michels, A., & Wang, S. (2024). CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics: A Case Study of COVID-19. In J.-S. Kim, T. Anderson, M. Lau, A. Roess, & A. Zufle (Eds.), SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology (pp. 19-22). (SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology). Association for Computing Machinery, Inc. https://doi.org/10.1145/3681777.3698474

Han, Su Yeon ; Kim, Joon Seok ; Jiang, Yuqin et al. / CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics : A Case Study of COVID-19. SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology. editor / Joon-Seok Kim ; Taylor Anderson ; Max Lau ; Amira Roess ; Andreas Zufle. Association for Computing Machinery, Inc, 2024. pp. 19-22 (SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology).

@inproceedings{f6f343c1182c4c83b1fc088f078c6e6e,

title = "CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics: A Case Study of COVID-19",

abstract = "The COVID-19 pandemic underscored the critical need for effective disease mapping tools, essential for tracking infectious diseases. Following the WHO's pandemic declaration in March 2020, numerous technological solutions emerged to map cases, assess risk factors, and monitor mobility. However, there remains a shortage of reusable, open-source geovisual analytics tool for rapid response to future pandemics. To address this gap, we developed an innovative open-source JavaScript-based geovisual analytics tool as part of the CyberGIS-Vis project. This paper introduces two visualization modules of CyberGIS-Vis, showcasing their use in visualizing spatiotemporal COVID-19 data by integrating advanced cyberGIS and online visualization with robust analytics for geospatial knowledge discovery.",

keywords = "COVID-19, CyberGIS, geovisual analytics, visualization",

author = "Han, {Su Yeon} and Kim, {Joon Seok} and Yuqin Jiang and Kang, {Jeon Young} and Jinwoo Park and Chaeyeon Han and Alexander Michels and Shaowen Wang",

note = "Publisher Copyright: {\textcopyright} 2024 Copyright held by the owner/author(s).; 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology, SPATIALEPI 2024 ; Conference date: 29-10-2024",

year = "2024",

month = oct,

day = "25",

doi = "10.1145/3681777.3698474",

language = "English",

series = "SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology",

publisher = "Association for Computing Machinery, Inc",

pages = "19--22",

editor = "Joon-Seok Kim and Taylor Anderson and Max Lau and Amira Roess and Andreas Zufle",

booktitle = "SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology",

}

Han, SY, Kim, JS, Jiang, Y, Kang, JY , Park, J, Han, C, Michels, A & Wang, S 2024, CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics: A Case Study of COVID-19. in J-S Kim, T Anderson, M Lau, A Roess & A Zufle (eds), SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology. SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology, Association for Computing Machinery, Inc, pp. 19-22, 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology, SPATIALEPI 2024, Atlanta, United States, 29/10/24. https://doi.org/10.1145/3681777.3698474

CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics: A Case Study of COVID-19. / Han, Su Yeon; Kim, Joon Seok; Jiang, Yuqin et al.
SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology. ed. / Joon-Seok Kim; Taylor Anderson; Max Lau; Amira Roess; Andreas Zufle. Association for Computing Machinery, Inc, 2024. p. 19-22 (SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics

T2 - 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology, SPATIALEPI 2024

AU - Han, Su Yeon

AU - Kim, Joon Seok

AU - Jiang, Yuqin

AU - Kang, Jeon Young

AU - Park, Jinwoo

AU - Han, Chaeyeon

AU - Michels, Alexander

AU - Wang, Shaowen

PY - 2024/10/25

Y1 - 2024/10/25

N2 - The COVID-19 pandemic underscored the critical need for effective disease mapping tools, essential for tracking infectious diseases. Following the WHO's pandemic declaration in March 2020, numerous technological solutions emerged to map cases, assess risk factors, and monitor mobility. However, there remains a shortage of reusable, open-source geovisual analytics tool for rapid response to future pandemics. To address this gap, we developed an innovative open-source JavaScript-based geovisual analytics tool as part of the CyberGIS-Vis project. This paper introduces two visualization modules of CyberGIS-Vis, showcasing their use in visualizing spatiotemporal COVID-19 data by integrating advanced cyberGIS and online visualization with robust analytics for geospatial knowledge discovery.

AB - The COVID-19 pandemic underscored the critical need for effective disease mapping tools, essential for tracking infectious diseases. Following the WHO's pandemic declaration in March 2020, numerous technological solutions emerged to map cases, assess risk factors, and monitor mobility. However, there remains a shortage of reusable, open-source geovisual analytics tool for rapid response to future pandemics. To address this gap, we developed an innovative open-source JavaScript-based geovisual analytics tool as part of the CyberGIS-Vis project. This paper introduces two visualization modules of CyberGIS-Vis, showcasing their use in visualizing spatiotemporal COVID-19 data by integrating advanced cyberGIS and online visualization with robust analytics for geospatial knowledge discovery.

KW - COVID-19

KW - CyberGIS

KW - geovisual analytics

KW - visualization

UR - http://www.scopus.com/inward/record.url?scp=85211599720&partnerID=8YFLogxK

U2 - 10.1145/3681777.3698474

DO - 10.1145/3681777.3698474

M3 - Conference contribution

AN - SCOPUS:85211599720

T3 - SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology

SP - 19

EP - 22

BT - SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology

A2 - Kim, Joon-Seok

A2 - Anderson, Taylor

A2 - Lau, Max

A2 - Roess, Amira

A2 - Zufle, Andreas

PB - Association for Computing Machinery, Inc

Y2 - 29 October 2024

ER -

Han SY, Kim JS, Jiang Y, Kang JY , Park J, Han C et al. CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics: A Case Study of COVID-19. In Kim JS, Anderson T, Lau M, Roess A, Zufle A, editors, SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology. Association for Computing Machinery, Inc. 2024. p. 19-22. (SPATIALEPI 2024 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology). doi: 10.1145/3681777.3698474

CyberGIS-Vis for Democratizing Access to Scalable Spatiotemporal Geovisual Analytics: A Case Study of COVID-19

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this