Working with three different digital tools highlighted the ways digital tools can help understand data as well as develop new lines of research.  Using the same set of data, the WPA Slave Narratives Project, connections were explored using Voyant 2.0, kelper.gl, and Palladio. Each of the tools offered a way of understanding the information and had value as a stand alone analysis, however they also complement each other.

The tools revealed different aspects of the narratives. After working with Palladio and seeing the connections between topics and demographics, I think taking the topics that appeared most often (or least) in the Alabama example would be interesting to run the data again in Voyant 2.0 and see what the context was. I was surprised at the religion-Sunday-church-wedding -baptism connections, and think bringing Voyant’s analysis in for similar trends in other states may offer insight. This struck me as baptism was the item mentioned least, and may be worth exploring, as both religion and church were fairly strong topics, why was baptism less so given it is a tenet for belonging to many churches. It may also suggest church as a safe space or as a monitored space, threads worth pulling using text analysis combined with network analysis. 

After listening to a graduate student presenting her research on African Americans and migration in South Carolina this afternoon, I think I would like to test use of the three tools in conjunction with each other on a related question. Specifically, I would like to use them to develop visualizations of the movement of the formerly enslaved, whether they traveled a few minutes from the place of enslavement or chose to build a life in another location completely. The Alabama sample, for example, shows limited movement, until you take into consideration that the interviews took place over a short period, in Alabama. Kepler.gl and Palladio can show where those that remained in Alabama did not tend to travel far, but the entire data set would help expand the geospatial view. Voyant would be a useful tool to add the context to the data, and potentially add some information on those who left as part of the Great Migration.

Palladio is open source software that allows users to visualize data through mapping, graphs, and tables. Data can be represented as points on a map, connected by arcs and scalable, in a list or table form and in a gallery grip layout for organization. There are also timeline and timespan filters that it did not explore.

One of the interesting features in graphs is the dynamic interface, allowing manipulation of the network graph to isolate or drill down on nodes and connections. For example, in the graph below, the topics and work performed data sets were compared highlighting some of the differences in experience and points of view (Figure 1)

Figure 2 shows the relationship between where the person was interviewed compared to where they were enslaved. The grouping suggests limited movement between the two locations, and highlights an area to compare the WPA interview data to census data to understand the paths of movement and whether the Alabama data set is representative of all the movement post-liberation. Comparing this to census data from 1860/1880 and 1930 might be an interesting follow up to this visualization.

Palladio was fairly straightforward to use, with an excellent tutorial page to help with adding data, data structure and the different functions of the software.