In this post, I will be discussing digital mapping as a whole through kepler.gl, a free online mapping tool that serves a lot of different analytical functions! Based on my experiences with this program, I could analyze data through coordinates, trends relating to proximity, clusters of mapping data, timelines, heat maps, color coding based on one of the provided parameters in the uploaded file(s) (in this case a .csv file through Microsoft Excel), and more! It is a tool with a lot of versatility and features to visualize data through its different filters, mapping options, and its ability to show connections within the data that the user can then interpret through other means!

At the bottom of this post is an example of a map that was created through data surrounding interviews with formerly-enslaved people in the state of Alabama in the 1930s. It specifically plots their name, age, their sex, where they were interviewed, and their place of birth. Additionally, there is more metadata that could be enabled through the source material it is visualizing, meaning that there is a lot of different information that can be provided through the metadata. Visualizations that utilize this type of source material can be useful for analyzing the interviewer and interviewee alike. It can visualize demographic data in the case of the interviewee; encouraging questions surrounding the formerly-enslaved population of Alabama at the time, their age and life-expectancy, where they came from and who ended up there at the time of the interviews (and perhaps “why” in some cases). On the side of the interviewer, it can document where these interviews took place, who interviewed them if that was inserted into the map, and the timeline in which these interviews were conducted. Through timelines–another feature that was previously mentioned–one can track the time, day, month, and year in which interviews took place, while isolating different points if one has that data entered into the files that they submitted.

I first utilized kepler.gl during my undergraduate education, so I had some prior experience before revisiting this tool (admittedly, it has been a while since I last utilized tools of this nature in any capacity). Upon doing this, I remembered the potential of not only the tool, but the practice itself. It is a multi-step process which necessitates thorough data that covers multiple aspects of what it is one is researching and eventually plotting on a map. I was vaguely aware of this process, but seeing it unfold again and being able to edit the information yourself is a valuable experience. If nothing else, it makes me appreciate this process that the public can take for granted when utilizing these types of services, even in everyday life. Geospatial research is a crucial tool in the digital humanities, and one of my favorite methods of visualizing data!