MY DATA VISUALIZATION
Research Question: How does the ranking of the top 10 male and female baby names in the US change from 2001-2010?
My data visualization process
For my visualization, I chose to put each name in its own chart. Initially, I tried to put all of the names on one graph, but I found it to be busy and challenging to parse trends. I used the “Grid of charts” option to separate each name. This allows the reader to better see how the ranking of a specific name in the data set changes between 2001 and 2010. Additionally, the visualization was split by gender through an interactive drop-down menu in the top left-hand corner. Doing this made it possible to address my research question while reducing the number of charts the reader was presented with.
To improve the clarity of the visualization, I changed the direction of the y-axis. Initially, the y-axis was ascending from 1-10. While this is a reasonable default setting, given that we are interested in rankings where 1 signifies the highest value and 10 represents the lowest, switching the direction of the y-axis (ascending from 10-1) allowed me to properly visualize how the popularity of a name declines or rises over time. Additionally, I worked with the font structure/size to create a visual hierarchy where the name associated with each graph is the largest component, followed by the axis labels, and then the tick marks. This allows each chart to appear as its cohesive unit. Finally, I used a black background and teal lines to create visual contrast.
Connections to Class Lecture, Readings, and Digital Humanities
Throughout this project, I saw clear connections to the work that we do across the field of Digital Humanities. A central component is making data that would otherwise be messy and uninterpretable easy to access and metabolize. As I was working on my project, I was reflecting on our two readings (What Gets Counted Counts & Introduction: A History of Visualization and Power) and my decision to split the visualization by gender. While gender is not central to understanding these trends, the split helped clean the visualization. However, dividing by gender enforces the idea of a binary and the understanding that certain names are meant for men or women. Thus, we can see how simple choices in design have larger ramifications for the ways that we understand a topic.