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Jump to: Data Work, Simulations, Conceptual Graphics, Vision, Get Started

The Work

Source: 2021 United States Census Current Population Survey Annual Social and Economic Supplement. Individual income in USD. Note that all individuals identified as multiple races are put in the multi-racial category. Those in the other four race categories listed a single race on the survey.

Data Analysis & Visualization

There is a lot of insight that can be gleaned from conventional datasets by looking at the information in a slightly different way. 30+ years after Kimberlé Crenshaw's seminal talk on "Demarginalizing the Intersection of Race and Gender," intersecting systems remain in the margins and subtext of most demographic data visualizations. Here, I'm looking at a quantity that has a profound impact on every day life: income. I have crosstabulated the data based on race and gender. Unexpected insights immediately arise.

The way I have chosen to break down the data means that an important dimension is left out: ethnicity. Specifically, what the Census describes as Hispanic ethnicity is surveyed in a seperate column from race. Because there are Hispanic people of all races according to the Census, I prefer to measure Hispanic ethnicity across race, but adding this fourth dimension to a conventional bar chart would start to crowd it. For this reason, I have been creating some internal tools that allow intersectional analysis to be visualized clearly, even if many dimensions of data are involved. If you are interested in learning about these tools, contact Starling.

Starling can meet whatever particular data analysis and data visualization needs you bring to the table. Other public facing works include The 2020 State of Housing in Black America and "Come for the Science".

Simulations

The principles of design and mathematics can come together to create simulations that help us better understand social and natural phenomena, from past to present to future. Simulations can be used to visualize anything from climate change, to market dynamics, to COVID-19. A classic coding challenge is a flocking simulation, like the one all over this page. The simulation above is a study of bezier curves, which are a cricical part of typography. Click here for a simulation of the impact of housing discrimination on two imagined families.

Conceptual Visualizations

Conceptual visualizations can help illustrate complex causal systems using a variety of tactics including animation. These visualizations often use data or are based in data, but include interpretation that takes into account the larger context around the numbers.

A note from the founder

There is so much to observe in the movements of flocking birds. You can see individuals animated by their surroundings. At the same time, you can see a whole mobilized by a thousand parts. Each bird steers itself based on the few birds closest to it: each has limited perception, but the perceptions in the flock overlap, so that as a whole the murmuration will move in synch. When birds flock in large numbers, the effect feels so improbable as to mesmerize and haunt. (Starlings can flock in the tens of thousands... other birds in the millions or more.)

I came up with the slogan "information in relation" because the way we understand data is always rooted in context. In the same way that a bird can only steer based on what it can see, a person can only understand data based on the world that they know. The process of visualizing data as meaningful information should attend to that context. Excellent design makes this possible.

In the way I've simulated a flock of birds for this website, it's easy to see the individual within the whole. In the way I design, I want to remember that each data point corresponds to something vast: often a person or a household, something that breathes and changes every minute. On a practical level, this means design as a strategy to express information about individuals who don't fit easily into the traditional pools of data. Conventional data visualizations often leave some people out. Even though the term "intersectionality" has entered a popular lexicon, few data visualizations express the conditions of those who occupy intersecting identities. I am working to create data tools that accomodate these hidden nuances. The current landscape of interactivity and animation makes this work both possible and fun.

After years of freelancing primarily through word-of-mouth, I created Starling Data. Starling is a home for my work in data analysis and expression. I chose a murmuration as the anchoring image for this site for the reasons I’ve just described. But I selected the starling in particular because it is a bird from my past. Growing up in Wisconsin, I loved watching starlings bathe on days when rain had puddled. I was fascinated by the starling’s trill and the way its dark feathers shine colors when glistening in the right light. I know that starlings can interfere with agriculture, and sometimes it’s a big problem. But my personal history means I see these birds as lovely animals. Their image as I render it is personal. In the same way, data, when forged into information, becomes personal. Through design, we can embrace data as something tangled into the world of the personal, of personhood, of people.

—Morgan Green

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Copyright 2022, Morgan Green