Visualizing the COVID-19 Pandemic: The Importance of Data Visualization in Communicating the Impact of a Global Crisis

 A REVIEW OF PAUL KAHN’S “COVIC: COLLECTING VISUALIZATIONS OF COVID-19 TO OUTLINE A SPACE OF POSIBILITIES.”

 

GUZMAN, JAZMIN I.

BS ARCHITECTURE  AR135 ESSAYS AND REVIEWS

 

(SUMMARY)

 

The COVID-19 pandemic began in China in January 2020 and spread rapidly throughout the world. As a result, there was a sudden increase in data visualizations in print and online to communicate the new phenomenon. The global impact of COVID-19 caught everyone by surprise and motivated the collection of visualizations. The ease of access to data visualization software, the rising popularity of data journalism, and the ability to share images on social media all contributed to this collecting activity. The question is raised as to why collect these visualizations at all as they become historical artifacts and may not hold value for certain groups of people such as data journalists, design students, or virologists.

The COVID-19 pandemic caused a disruption in daily life and a sense of uncertainty about the future, which led to two communication needs. The first need was to qualitatively communicate scientific understanding of the disease, its spread and appropriate public health response through visualizations. The second was to collect, quantify and publish data related to the spread and effect of the disease in a visual format. This data was used by epidemiologists, political leaders, economists, parents, and journalists to make decisions and tell a story. The need for consistent and understandable data drove the use of different types of charts such as histograms, bar charts and choropleth maps, as well as inventive combinations to communicate the information.

The pandemic led to the creation of thousands of visualizations to communicate information about the disease and its impact. The authors of the article are collecting these visualizations to study the problem space of the pandemic. They are collecting visualizations based on two criteria: the presence of visualizations related to the pandemic and the belief that the source of the visualization is the article. The collection has been assembled opportunistically and is limited to visualizations found through daily practices such as reading, browsing, and searching, and the bulk of the collection was recorded in the United States and France. The cultural bias and affordances of the author, an English-speaking white American male, have shaped the content and quantity of Anglo-American examples in the collection.

The COVID-19 Visualizations Collection (COVIC) is a problem space consisting of visual representations and not the articles themselves. The collection captures interaction technique, visual technique, and visualization types at the figure level and assigns subject, publisher, and publication date to the article. The collection is intended to be a resource for ongoing research in various disciplines such as graphic and information design, journalism, public health, epidemiology, economics, cognitive psychology, and computer science. COVIC is a boundary object by nature of the events that generated it and can be used to support research into a diverse range of questions. The concept of a problem space is not widely developed in design practice and this kind of timely, opportunistic, digital collection exemplifies a new approach- collecting and preserving enough design samples during an event to describe a space. COVIC can be important for discussing and evaluating design solutions and also serves as an example of a new approach to knowledge building and design research.

COVIC is a collection of visualizations related to the COVID-19 pandemic that was created by assembling visualizations from various sources and organizing them into a problem space. The authors used an iterative method to collect visualizations and created metadata for examples. They stored the collection in a spreadsheet-database hybrid platform and created a viewer that allows users to search, sort, filter, and examine sets of images and their associated metadata. COVIC is different from other disaster archives because it is being created during the pandemic event, allows them to respond to the ephemeral nature of online materials, and focuses entirely on visualizations rather than representing the entire complex global event. They also acknowledged the Collection of COVID-19 Visualization Worldwide, hosted at Peking University Visualization Lab, which reinforced their vision.

The goal of the collection is to create a "problem space" of visual representations that can be used by researchers across various disciplines to understand the pandemic and its impact. The collection was created using an iterative method, where visualizations were collected and classified using an ad-hoc classification scheme. The collection also compares COVIC to other disaster archives and highlights the differences, such as being created during the pandemic and focusing on visualizations rather than other types of information. The article concludes by stating that the collection will be a useful resource for ongoing research and critique of visualizations during times of global crisis.

(ANALYSIS – Argumentative claims and its supporting ideas)

 

1. The COVID-19 pandemic led to a sudden increase in data visualizations in print and online.

 

Supporting idea: The ease of access to data visualization software, the rising popularity of data journalism, and the ability to share images on social media all contributed to this collecting activity.

 2. The pandemic caused a disruption in daily life and a sense of uncertainty about the future, which led to two communication needs: the need to qualitatively communicate scientific understanding of the disease, and the need to collect, quantify and publish data related to the spread and effect of the disease in a visual format.

 

Supporting idea: This data was used by epidemiologists, political leaders, economists, parents, and journalists to make decisions and tell a story.

 

 3.The COVID-19 Visualizations Collection (COVIC) captures interaction technique, visual technique,d visualization types at the figure level and assigns subject, publisher, and publication date to the article.

 

Supporting idea: COVIC is intended to be a resource for ongoing research in various disciplines such as graphic and information design, journalism, public health, epidemiology, economics, cognitive psychology, and computer science.

 

4.  COVIC is different from other disaster archives because it is being created during the pandemic event, allows them to respond to the ephemeral and rapidly evolving nature of the pandemic.

 

Supporting idea: COVIC can be important for discussing and evaluating design solutions and also serves as an example of a new approach to knowledge building and design research.

 

5. The collection of visualizations related to COVID-19 is important for ongoing research in various disciplines.

 

Supporting idea: The collection captures interaction technique, visual technique, and visualization types at the figure level and assigns subject, publisher, and publication date to the article, making it a valuable resource for research in fields such as graphic and information design, journalism, public health, epidemiology, economics, cognitive psychology, and computer science.

 

(ARGUMENTS – Opinions)

 

    1. The COVID-19 pandemic led to a sudden increase in data visualizations in print and online. (Affirmative argument)

 

The COVID-19 pandemic has resulted in a significant uptick in the use of data visualizations in print and online media, which is largely due to the widespread availability of data visualization tools, the growing trend of data-driven journalism, and the ease of sharing images on social media platforms.

 

Firstly, the accessibility of data visualization software has made it possible for people and organizations to create visual representations of data easily, regardless of their technical expertise. This has led to a rise in the number of data visualizations being created and shared.

 

Secondly, the growing popularity of data journalism has played a major role in the increase of data visualizations, as the pandemic has put a spotlight on data-driven reporting, and journalists and news organizations are increasingly turning to data visualizations to help explain complex data sets and trends.

 

Lastly, the ability to share images on social media platforms has made it easy for people and organizations to disseminate data visualizations to a wide audience, further popularizing their use and aiding in the communication of information about the pandemic.

 

In conclusion, the COVID-19 pandemic has led to a significant increase in the use of data visualizations in print and online media, which is largely due to the ease of access to data visualization tools, the growing trend of data-driven journalism, and the ability to share images on social media. These factors have made it possible for people and organizations to create and share data visualizations on a large scale, providing valuable insights into the pandemic and helping to inform the public.

 

 

2 . The pandemic caused a disruption in daily life and a sense of uncertainty about the future, which led to two communication needs: the need to qualitatively communicate scientific understanding of the disease, and the need to collect, quantify and publish data related to the spread and effect of the disease in a visual format. (non-affirmative argument)

 

While it could be argued that the COVID-19 pandemic led to a sudden increase in data visualizations in print and online, it is not necessarily the case that this was due to a direct correlation between the pandemic and the communication needs for scientific understanding and data collection. There are other potential factors that could have contributed to the increase in data visualizations.

 

One possibility is that the pandemic simply highlighted pre-existing trends towards greater data visualization and data journalism. Prior to the pandemic, data visualization and data journalism were already growing in popularity, and it is possible that these trends would have continued regardless of the pandemic.

 

Another possibility is that the pandemic created an environment in which data visualizations were viewed as a useful tool for understanding and communicating about the disease, but it is not necessarily the case that this was the sole or main driver for the increase in data visualizations.

 

Additionally, the sense of uncertainty and disruption of daily life caused by the pandemic may have led to an increased demand for information, but this does not necessarily mean that data visualizations were the only or most effective way to meet this demand.

 

In conclusion, while it is true that the COVID-19 pandemic led to a sudden increase in data visualizations in print and online, it is not clear that this was solely due to the pandemic creating a need for data visualization to communicate scientific understanding and data collection. There may be other factors at play and it is not clear that data visualization is the only or most effective way to meet communication needs.

  

3.  The COVID-19 Visualizations Collection (COVIC) captures interaction technique, visual technique, and visualization types at the figure level and assigns subject, publisher, and publication date to the article. (Affirmative argument)

 

 

The COVID-19 Visualizations Collection (COVIC) is a powerful resource for organizing and accessing data visualizations related to the COVID-19 pandemic.

 

First, COVIC meticulously records the technical aspects of the visualizations, such as the interaction and visual techniques used, as well as the type of visualization, allowing users to quickly and easily find visualizations that utilize specific techniques or types.

 

Secondly, COVIC provides crucial context for the visualizations by assigning subject, publisher, and publication date to the article. This information allows users to understand the specific topic or area that a visualization is focused on, as well as the source and date of the visualization.

 

Lastly, by providing a comprehensive collection of data visualizations related to the COVID-19 pandemic, COVIC helps to improve understanding of the disease and its impact by making the data easily understandable for a wide range of audiences.

 

In conclusion, the COVID-19 Visualizations Collection (COVIC) is an effective tool for capturing and organizing information about data visualizations related to the COVID-19 pandemic. It efficiently records technical details of the visualizations, provides valuable context, and offers a comprehensive collection of visualizations that facilitates understanding of the pandemic.

4.   COVIC is different from other disaster archives because it is being created during the pandemic event, allows them to respond to the ephemeral and rapidly evolving nature of the pandemic. (Affirmative argument)

 

The COVID-19 Visualizations Collection (COVIC) is a unique and valuable resource for understanding and responding to the COVID-19 pandemic.

 

Firstly, COVIC is different from other disaster archives because it is being created during the pandemic event. This allows COVIC to respond to the ephemeral and rapidly evolving nature of the pandemic by capturing and preserving data visualizations in real-time, rather than after the event has passed.

 

Secondly, COVIC allows for a quick response to the constantly changing information about the pandemic, this is because the collection is being updated during the pandemic event, it captures current and up-to-date data visualizations, which can be used by researchers, journalists, and policymakers to make informed decisions.

 

Additionally, COVIC allows for a better understanding of the pandemic in real-time, this is because the collection captures data visualizations from different sources and perspectives, which provides a more comprehensive and nuanced understanding of the pandemic and its impact.

 

In conclusion, COVID-19 Visualizations Collection (COVIC) is an exceptional and valuable resource for understanding and responding to the COVID-19 pandemic, because it is being created during the pandemic event, it allows for a quick response to the constantly changing information about the pandemic, which allows researchers, journalists, and policymakers to make informed decisions and have a better understanding of the pandemic in real-time.

5.    The collection of visualizations related to COVID-19 is important for ongoing research in various disciplines. (Affirmative argument)

 

The compilation of visual representations of COVID-19 data is crucial for ongoing research across different fields. These visualizations make it simpler to interpret complex information and aid researchers from various disciplines in understanding and analyzing data related to the pandemic.

 

For example, by visualizing the spread of the virus over time and in different locations, researchers can gain insight into how the virus spreads and its effects on different populations. Additionally, visualizations can be utilized to monitor the pandemic's impact on various aspects of society such as healthcare, economy, and education, allowing researchers to identify the factors that contribute to the pandemic and its effects, and to devise strategies to mitigate these impacts. Furthermore, visualizations can be used to evaluate the effectiveness of different policies and interventions, such as testing and vaccination rates, which can assist researchers and policymakers in making data-driven decisions on how to respond to the pandemic. Lastly, visualizations can aid in creating a more comprehensive understanding of the pandemic by combining data from multiple sources and disciplines, leading to new insights and knowledge.

 

In conclusion, the collection of visualizations related to COVID-19 is a vital resource for ongoing research in various disciplines, as it enables the communication of complex data in an easily understandable format, allows for the tracking of the pandemic's impact on different aspects of society, enables the evaluation of policies and interventions and leads to new insights and knowledge about the pandemic.