HELLO, BLACK WORLD:

Du Bois, Data, and a Visual Reflection of the Black Past and Present

HELLO,
BLACK
WORLD

Du Bois, Data, and
a Visual Reflection
of the Black Past
and Present

Amy Yeboah Quarkume, Arjun Phull, Anuj Gupta, Duo Bao, Jade Flint, Amelia Matheson, Bryan Carter

INTRODUCTION

The 1900 Paris Exposition hosted countries from around the world to reflect on their individual achievements and ambitions for the new century. These primarily Western nations created elaborate displays to showcase their past and present technological and cultural prowess in contrast with exhibits of literal human zoos of "primitive people" from different regions of Africa and Latin America. This colonialist agenda led Thomas Junius Calloway to successfully appeal to the U.S. government to allow Black Americans to create their own counteractive exhibit that would be viewed by millions at the upcoming World's Fair. With such a monumentally important task, Calloway, a Black lawyer and educator, enlisted the help of his former Fisk University classmate, W.E.B. Du Bois. The desires of Calloway and Du Bois perfectly meshed in the Du Bois-led Atlanta University team's creation of various charts and diagrams that were equally informationally rich as they were visually arresting. The Exposition des Negres d'Amérique astounded viewers of all races and went on to receive much critical acclaim. Their success proved without a shadow of a doubt that Black progress was a product of our own self-determination in spite of the constant onslaught of systemic racism.

Today, we stand 125 years from this triumphant display, 25 years from the start of a new millennium, and five years from the start of the COVID-19 pandemic and the police executions of George Floyd and Breonna Taylor. At this important juncture, "Hello, Black World: Du Bois, Data, and the Black Experience" walks in Du Bois's footsteps to methodically consider how we have waxed and waned in our progression. Du Bois clearly understood that simply collecting the data was not enough; rather, it needed to be presented in a way that was accessible and engaging for the everyday person. Hello, Black World pushes Du Bois's model further by incorporating 3D visuals, augmented reality (AR), and virtual reality (VR). The collaborative project was spearheaded by Dr. Amy Yeboah Quarkume of Howard University and Dr. Bryan Carter of the University of Arizona and developed by Arjun Phull, Anuj Gupta, and Duo Bao of the University of Arizona. Hello, Black World utilizes technology to harness the power of our ever-present smartphones and enhance the physical surroundings with layered virtual visuals. With visual effects, VR, and AR, this new exhibit allows viewers to easily compare the statistical 2D graphs of Du Bois's time with present information in 3D.

Apart from Du Bois's path-breaking work, there are several other sources from contemporary scholarship in digital rhetoric, technical communication, and Africana studies that have inspired our work. First, following Aaron Beveridge's (2017) recommendation for teachers to make data-driven arguments more accessible and meaningful to their students through data visualizations, the data visualizations in our initial exhibition—and now in this webtext—seek to encourage students and teachers to explore the world around them using the power of data-driven storytelling. Additionally, our work responds to Lisa Melonçon's and Emily Warner's (2017) advice for future technical and professional communication scholars to pay attention to the affordances provided by innovative, interactive visualizations as they can enhance the work of science communication. Through the Hello, Black World exhibition, we've tried to make a kind of science—data science—more accessible to the public at Howard University by communicating its impact and purpose in an engaging and accessible way using interactive data visualizations. Finally, one of our major sources of inspiration is Gloria Washington, Marlon Mejias, Saurav Aryal, Todd Shurn, and Legand Burge III's (2021) advocacy in favor of integrating the rich legacy of HBCU culture into computing education, specifically teaching elementary data structures. By incorporating unique cultural perspectives, such as historical context and experiences, they argued that educators can enhance student engagement and understanding of fundamental data structures in the computing field. A similar approach was forged with the Hello, Black World exhibit, bridging cultural relevance with technical education, providing a novel approach to enriching the learning experience for potential data science students.

VIRTUAL EXHIBIT

A 360-degree tour of the Hello, Black World exhibit at Howard University. Click and drag to move around!

VISUALIZATIONS

The Hello, Black World exhibit adopted a multimodal approach in scientific communication. Recognizing the historical underrepresentation of people of African descent in the field of data science, despite the pioneering efforts of researchers like Du Bois, the aim was to create an exhibit that demonstrated the power of data science as accessible and inclusive. By incorporating a diverse array of modalities in data visualizations—such as textual, visual, spatial, gestural, and immersive elements—the exhibit pulled in viewers of all ages into the field of data. Utilizing 3D visuals, AR, VR, video, and audio, seven exhibitions were created, each linked to a historical Du Bois diagram exploring diverse facets of Black life, such as income, education, criminal justice, housing, health, and environmental justice, alongside corresponding contemporary data. The exhibit exposed visitors to Du Bois's diverse work and empowered them to gain an interdisciplinary understanding of the power of data.

Our webtext broadens the project's scope beyond Howard University's walls. We begin by offering a 360-degree tour of the exhibit space. Corresponding pages then present each individual visualization along with an audiovisual depiction of a historical Du Bois visualization, commentary connecting contemporary data, and insights from the creators of the visualizations.

Select each tab below to explore the corresponding visualization.

Black Space and the Environment
The Blossoming of Black Literature
Health and Income Across Race
Homeownership Across Race
Black Family Dynamics
Illiteracy Across Race
Incarceration Across Race

Created by Arjun Phull

Open this visualization in a new tab

INSPIRATION AND CONTEXT

Du Bois visualized demographics among Black Philadelphians in engaging and intuitive ways.

This visualization was inspired by Du Bois’s exploration of differential health data among Black and white Pennsylvanians, which you can see in the video in this section (Du Bois, 1899/2007, p. 156). Du Bois’s original data visualization explored how death rates differed between Black and white Americans across all age groups, using a color-coded bar chart to illustrate the stark difference. Du Bois also famously mapped Philadelphia’s Seventh Ward, creating a visualization in which he encapsulated spatial, socioeconomic, and demographic data. In his charts, Du Bois thought outside the box, using creative spacing and color coding to redefine the purpose of a bar graph and area chart. His creative thinking inspired me to envision my own data visualization, one that leveraged the breadth of geospatial data with the visual familiarity of a bar graph. What you see in front of you is a 3D map of the state of Pennsylvania, reimagined as a bar graph. Each county is colored on a color scale pulled directly from Du Bois’s visualizations, representing the proportion of Black and African American populations in each county. The heights of each county correspond to normalized rates of environmentally influenced conditions, including asthma, COPD, and lung cancer. The melding of maps and bar graphs into one cohesive visualization pays homage to Du Bois’s eclectic approach to data visualization.

PURPOSE

This visualization is designed to tie together the differential rates of disease across Pennsylvania and the differential proportions of the Black population in each county. As you explore this interactive data visualization, consider the story that the data is telling. You can move the map around to view it from different angles and examine the correlation between health condition incidence and the Black population within each county. This may help you answer questions such as "Are Black people disproportionately affected by these environmentally-driven conditions?" and "What institutional factors might be driving that correlation?"

INSTRUCTIONS

This visualization is optimized for a desktop or laptop computer and does not currently work on mobile devices. You can select a condition to explore across counties from the menu below the map. Then, you can hover over each county to view the relative incidence rate of the selected condition. You can click and drag to move, zoom, and rotate the map.

METHODOLOGY

To build this visualization, I imported 3D models of each county in Pennsylvania in .gltf format using a JavaScript library called Three.js. There are 67 counties within Pennsylvania, so this made for a lot of lines of code. Thankfully, I was able to use Python to create a code template that would load each model, and so I used Python to automate the loading of each model. The data regarding the Black populations of each county came from the U.S. Census Bureau (2020). County-level data for population and age-adjusted prevalence of asthma, COPD, cancer, and coronary heart disease came from the CDC’s “PLACES: Local Data for Better Health, County Data 2024 release” dataset (2024). Poverty data comes from the U.S. Census Bureau Table S1701 (2022). The Black population data was already in percentage form, so I used Python to create a dictionary that mapped each county to its Black population percentage. For the CDC PLACES data, I used a Python library called Pandas to transform the tabular condition incidence data into relevant percentages. I then normalized the data on a scale from one to 10, which allowed me to highlight the relative spread of disease incidence. Once my data was transformed, I used Three.js and another JavaScript library called GSAP to animate the heights of each county according to the data regarding the condition selected. To build the color scale across all the counties, I created a JavaScript function that takes a county’s percentage of Black population and returns RGB values that correspond to a color between off-white and brown. I then used Three.js to set the color of each county to the color returned by the function. Lastly, I used HTML and CSS to wrap my data visualization within a web app.

CONTRIBUTORS

"Hello, Black World: Du Bois, Data, and a Visual Reflection of the Black Past and Present" was envisioned by Dr. Amy Yeboah Quarkume, associate professor of Africana studies at Howard University. The project was developed at the University of Arizona's Center for Digital Humanities, directed by associate professor of Africana studies Dr. Bryan Carter.

The visualizations Black Space and the Environment, The Blossoming of Black Literature, and Homeownership Across Race were developed by Arjun Phull, a student developer at the Center for Digital Humanities and undergraduate student at the University of Arizona. Arjun conceptualized and developed the design language behind each visualization and the webtext, paying homage to Du Bois's signature aesthetic. He also developed the HTML, CSS, and Javascript behind this webtext.

The visualizations Health and Income Across Race, Illiteracy Across Race, and Incarceration Across Race were developed by Anuj Gupta, a research assistant at the Center for Digital Humanities and PhD candidate at the University of Arizona.

The visualization Black Family Dynamics was developed by Duo Bao, a student developer at the Center for Digital Humanities and graduate student at the University of Arizona.

The virtual exhibit was developed by Amelia Matheson, a student developer at the Center for Digital Humanities and undergraduate student at the University of Arizona.

The webtext's content and visualizations' data were compiled by Jade Flint of Howard University.

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