Lab 9 – Graphing Data

For Lab 9 of my Digital Humanities course, I evaluated the various ways to organize and then visualize data. These graphics were done using Tableau Prep and Tableau Desktop and are far from comprehensive. The dataset manipulated for these graphics came from a group called Gallup in 2019 and is titled the Self-described religious identification of Americans. This dataset is similar to the Longitudinal Religious Congregations and Membership File discussed in previous posts as it also looks at self-identified religious groups over time. Although both evaluate similar categories, they each draw the categorical lines differently, and beyond that, count category members differently (but this is an idea that I’ll explore later).

For now, it is important to understand the process of visualizing data. Once you’re the one in charge, the choices of inclusion and exclusion become quite obvious. Consider my first attempt at cleaning and visualizing the Gallup data:

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DH Lab 7 – Creating Data

As I have repeated many times to my classmates in Digital Humanities: the data doesn’t speak for itself. Part of understanding that comes from an insight provided by the Philosopher Karl Popper, who reminded a group of physics students that the first step in observation is choosing what to observe in the first place.

This is exactly what we were asked to do for our lab this week – choose what to observe and thus, create data. Every student evaluated the same data source, The Seventh Day Adventist Yearbook, but we each chose different information to make into our own datasets.

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