Working with digital mapping, this module truly showed me how much can be done with even a small amount of data. When viewing projects such as Photogrammer, the National Mall, and Mapping the Gay Guides, I was a bit overwhelmed by the vast extent of each project. An immense amount of time and effort seemed to go into these projects, not to mention the sheer amount of data. While this is not a bad thing, it just seemed to be a significant undertaking before I explicitly began working with Kepler. gl. It was not until I started working and using the Works Progress Administration’s Slave Narrative project that I better understood and was able to map out the locations of the various formerly enslaved individuals interviewed in Alabama. Before working specifically with Kepler.gl, I was familiar with digital mapping platforms such as Datawrapper, but I had never specifically worked with any software. Therefore, when I started working with Kepler.gl, I was pleasantly surprised when I found the software to be highly user-friendly and knowledgeable. After simply uploading data, the user can use various tools, such as different layers, to demonstrate and evaluate their data. One layer is merely pointed on the map to locate your input data. This can help you understand the overall coverage of your data.   Specifically for the slave narratives, it shows the vast space in which those were located. The graph below illustrates that.

You can also change the color of your points and the theme of the map that it is located on to assist with viewability. Another interesting layer that can be applied is a cluster layer that creates larger bubbles based on the proximity of the point’s location. Those that are large bubbles help illustrate the areas where the most people were interviewed and also show the relative location of the larger areas of enslavement. The heat map layer also shows the proximity but does so based on the color gradient of numbers. The graph below illustrates that.

Another factor that can be examined with the tools in Kepler.gl is charting the various types of slaves that those who were interviewed were. The graph below shows the varying nature of enslaved people in the house, field, or both.

Working with Kepler. gl is a valuable tool that not only can map out the locations of various data points, show the frequency for which they appear, and show varying specific information, but it can also show a timeline of when the data occurred. Data mapping not only creates another dimension to digital humanities data, but it is able to answer the questions of: where are the highest frequencies located? What changes occurred over time? Was one location’s conditions unique to that area? What are the patterns throughout the areas mapped? Digital mapping allows endless possibilities for data and for the scholar working with it, and I very much enjoyed working with Kepler.gl.