Mapping/ Kepler.gl

Mapping software is another popular tool used in the digital humanities to translate text files into historical, memory, cultural, community, and many other types of maps. Maps allow users to analyze information by visualizing the data, which may detect trends or patterns that are not that evident through different tools. There are many open-source tools available to the public that you can use to generate maps using your text files as long as they provide latitude and longitude, fundamental fields to build your map.  The mapping tool I will explore today is Kepler.gl, a digital tool created by Uber that helps users visualize and analyze geospatial data.

The data that I will be using here comes from the WPA Slave Narratives, a collection of more than two thousand interviews with former slaves from the seventeenth states collected in 1936-1938 by writers for the Project of the Works Progress Administration. Those interviews are now available to the public in the Library of Congress, and their transcriptions are part of Project Gutenberg in the form of text files. They obtained the latitude/longitude information for the locations by entering them in a free georeferencing site in Google Maps.  

We use the online demo version that runs in the browser and does not store data in this activity. When you go to the website, you hit Get Started, which takes you to a screen to upload your text files. Then, choose the Alabama Interviews files. After uploaded, the tool will translate the data provided by the Excel file into a map indicating the location of the interviews with dots.

Fig. 1 Alabama Interviews
Fig, 2 Point Map

This type of map is a Point map. Here you can adjust the colors and the sizes of the points by clicking on the first icon under kepler.gl and going to Layer Settings. You can also change the information that appears in pop-ups when you roll the mouse over the points by clicking on Interactions, the third icon under kepler.gl. These pop-ups contain the information that appears in the columns of the spreadsheet you just uploaded.

Fig. 3 Point Map Showing Interviews Pop-Up Window

In addition, you can click on Base Map, the fourth icon under kepler.gl to go to Map Style, where you can see the map options, two degrees of dark and two of light. I stayed with the dark option. You can also control which elements appear on the map by clicking the eye icons in Map Layers by turning them on and off.  

Then, you can make a Cluster map which replaces points on the map with circles representing geographical points close to each other to indicate density. To create a cluster map, you go to the Layers Menu, click on the Interviews Data, and then on the Layer Type box, showing Point, to open the options. Here you click on Cluster. You can then adjust the size of the circles representing each cluster using the Cluster Size slider (under Radius).

Fig. 4 Cluster Map

Kepler.gl provides a helpful feature, the Dual View, that presents users the opportunity to compare two layers of the map simultaneously. To use this feature, add a layer to create a Heat Map, a map that replaces points on the map with areas in a spectrum of colors to represent groups of points located close to each other. After selecting the Heat Map on the Layer Type box, click on the Lat box and select Latitude and then Longitude from the pull-down menu. Now the Cluster and the Heatmaps are on the same map. To compare them, use the dual map view, the top button on the right top of the window, splitting the screen into two maps. The Layer Panel under the dual view allows you to select which layers display in each map. On the left map, click on the Interviews switch to turn off the Cluster layer, and on the right map, click on the switch next to the new layer to turn off the Heat Map layer.  

Fig. 5 Dual View

You can add filters to control what data you want to show by clicking on Filter, the second icon under kepler.gl on the top left. When you select Add Filter, you have to indicate which column of data to filter. In the case of the Slaves Narratives activity, we used this feature to show yet another option provided by Kepler.gl to visualize time intervals. Then, select “time when interview,” and a timeline will appear at the bottom of the map. When you press the play bottom, the line moves across the timeline, showing what occurs within it and hiding what is outside.

Fig. 6 When Interviewd Timeline

Kepler.gl allows related points on a map to be linked by arcs or lines. Thus, you need two different geographical sets of coordinates to make that connection. For the Slaves Narratives activity, delete the previous datasets and upload the second text file, the Alabama Combined dataset, which includes data on the location where an interview took place and the location where the interview subject was enslaved. Next, open the Layer Settings and change Layer Type to Arc and here you have to define the latitude and longitude for the Source (where interviewed) and the Target (Where Enslaved). You can also adjust the colors to show where slaves were interviewed and enslaved in different colors.

These network connections shown with arcs can be displayed using lines instead. The map that appears at the beginning of this post displays this network connection.

As you can see, Kepler.gl is an excellent open-source mapping tool that allows users to present data visually, which in many cases happens to be more approachable and explicative that the documents by themselves.

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