COVID-19 Vaccination Data Visualization: Issues and Challenges
Data Visualization plays an important role for patterns and trends analysis in trillion of data rows Big Data analysis, where the data can be represented in some graphical forms. Hence, the data could be more comprehensible in its visual summary in dashboards and storyboards. This study aims to disc...
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2-s2.0-85148643791 Ismail I.S.; Hajar Aishah Samsudin S.; Sani Mohd Sofian M.A.; Jantan H. COVID-19 Vaccination Data Visualization: Issues and Challenges 2022 IVIT 2022 - Proceedings of 1st International Visualization, Informatics and Technology Conference 10.1109/IVIT55443.2022.10033417 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148643791&doi=10.1109%2fIVIT55443.2022.10033417&partnerID=40&md5=92e5641e8b76c43ad5bb3370740b1fbf Data Visualization plays an important role for patterns and trends analysis in trillion of data rows Big Data analysis, where the data can be represented in some graphical forms. Hence, the data could be more comprehensible in its visual summary in dashboards and storyboards. This study aims to discuss some issues and challenges in visualizing COVID-19 vaccination datasets. There are some possible issues in data visualization, as it is not easy and may be challenging to produce a good dashboard that are interesting and easy for viewers to understand. Therefore, this study focuses on some issues that may arise during performing a data visualization on the COVID-19 dataset. In this study, there are three dashboards have been studied, which are the COVID-19 tracker, its effectiveness, and its acceptance. The first two dataset are derived from Ministry of Health Malaysia bank data, whereas the third dataset is from a survey to support this analysis. The selected attributes are states, the number of people who have received the vaccine as adults, children, and teenagers, and the number of people who already received boosters, and reasons to not get a booster. The visualization issues found within the dashboard are mis-choice of colors, mis-choice of visual object type, lack of interactivity, and plotting too much data. As a result, this proposed alternative solutions for those issues such as color deliberately, pick a suitable visual object, create an interactive dashboard, and reduce the information overload in visualizing the data. © 2022 IEEE. Institute of Electrical and Electronics Engineers Inc. English Conference paper |
author |
Ismail I.S.; Hajar Aishah Samsudin S.; Sani Mohd Sofian M.A.; Jantan H. |
spellingShingle |
Ismail I.S.; Hajar Aishah Samsudin S.; Sani Mohd Sofian M.A.; Jantan H. COVID-19 Vaccination Data Visualization: Issues and Challenges |
author_facet |
Ismail I.S.; Hajar Aishah Samsudin S.; Sani Mohd Sofian M.A.; Jantan H. |
author_sort |
Ismail I.S.; Hajar Aishah Samsudin S.; Sani Mohd Sofian M.A.; Jantan H. |
title |
COVID-19 Vaccination Data Visualization: Issues and Challenges |
title_short |
COVID-19 Vaccination Data Visualization: Issues and Challenges |
title_full |
COVID-19 Vaccination Data Visualization: Issues and Challenges |
title_fullStr |
COVID-19 Vaccination Data Visualization: Issues and Challenges |
title_full_unstemmed |
COVID-19 Vaccination Data Visualization: Issues and Challenges |
title_sort |
COVID-19 Vaccination Data Visualization: Issues and Challenges |
publishDate |
2022 |
container_title |
IVIT 2022 - Proceedings of 1st International Visualization, Informatics and Technology Conference |
container_volume |
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container_issue |
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doi_str_mv |
10.1109/IVIT55443.2022.10033417 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148643791&doi=10.1109%2fIVIT55443.2022.10033417&partnerID=40&md5=92e5641e8b76c43ad5bb3370740b1fbf |
description |
Data Visualization plays an important role for patterns and trends analysis in trillion of data rows Big Data analysis, where the data can be represented in some graphical forms. Hence, the data could be more comprehensible in its visual summary in dashboards and storyboards. This study aims to discuss some issues and challenges in visualizing COVID-19 vaccination datasets. There are some possible issues in data visualization, as it is not easy and may be challenging to produce a good dashboard that are interesting and easy for viewers to understand. Therefore, this study focuses on some issues that may arise during performing a data visualization on the COVID-19 dataset. In this study, there are three dashboards have been studied, which are the COVID-19 tracker, its effectiveness, and its acceptance. The first two dataset are derived from Ministry of Health Malaysia bank data, whereas the third dataset is from a survey to support this analysis. The selected attributes are states, the number of people who have received the vaccine as adults, children, and teenagers, and the number of people who already received boosters, and reasons to not get a booster. The visualization issues found within the dashboard are mis-choice of colors, mis-choice of visual object type, lack of interactivity, and plotting too much data. As a result, this proposed alternative solutions for those issues such as color deliberately, pick a suitable visual object, create an interactive dashboard, and reduce the information overload in visualizing the data. © 2022 IEEE. |
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Institute of Electrical and Electronics Engineers Inc. |
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English |
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Scopus |
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1809678025397108736 |