Activity 14: Constructing Data Visualizations

https://public.flourish.studio/visualisation/323702/

https://public.flourish.studio/visualisation/323498/

Partially born out of a frustrated effort to work through the technical issues that can arise from working with a new form of data representation, I produced the above two chord diagrams for this week’s exercise in data visualization. Both diagrams were made using data acquired from the Trans-Atlantic Slave Trade Database (the download page is available here).

After discovering Flourish offered a chord diagram feature–a type of visualization I had not heard of before–I realized this might have a lot of potential for representing slave trade networks, and I wanted to see if I could make that happen given the readily available access to data on the Trans Atlantic Slave Trade via the Slave Voyages website. The TAST Database is very thorough, consisting of data derived from the records of tens-of-thousands of individual enslaving voyages, encoding available details for each ship such as the number of people it carried as cargo or where it traveled to and from. That said, both of the above visualizations are constructed with three variables: the region in Africa that is “the imputed principal place of slave purchase”, the broad region in the world that is considered “the imputed principal place of slave disembarkation”, and the “total slaves on board at departure from last slaving port” (while this does not give an accurate representation of those who survived the journey across the ocean, I ultimately judged that it was better in such limited visualizations like these to skew towards the scale of people taken from Africa in the cargo holds of ships, rather than risk erasing them by using only the numbers of those who made it to their destination). The differences between the two visualizations is a matter of what voyages I drew from. My “Slave Trade from Different Regions of Africa” diagram is intended to highlight the diversity of areas people were taken from in the slave trade, and was made using the first 1500 voyages listed in the TAST Database (albeit, the “randomness” of this data sample has a high risk of being skewed by whether or not the voyages in the database were added in a relatively random order). Out of fascination for a region that is not often discussed in the history of the slave trade, my visualization of “Slave Voyages from Southeast Africa” consists strictly of the over 900 voyages that the database lists “Southeast Africa and the Indian Ocean Islands” as the principle source of human cargo. If nothing else, this draws attention to the range of places around the Atlantic these peoples from the Indian Ocean were brought to as strangers in chains in strange lands.

Admittedly, neither of these visualizations are ideal; my intent was to create a non-directional chord diagram in which both ends of a “chord” have the same thickness. In visualizing the slave trade and African diaspora, this makes sense for emphasizing the equal importance of peoples’ former homes and the lands they were brought to in bondage. Otherwise, we risk reducing the diversity of enslaved experiences to an amorphous destination of “America” or, even more often, recreating one of slavery’s inherent injustices of reducing peoples of wide ranging origins to an amorphous mass of “Africans.” Nonetheless, my visualizations do not achieve this. After failing to make the “non-directional” flow feature work with two different visualizations, what I am left with is one visualization depicting people funneled out of Southeast Africa into diverse destinations, and another depicting people from across the African continent funneling into a deceivingly singular “American” endpoint. While it can be informative and interesting to contemplate the relative scales of where people came from and ended up over the course of the slave trade (and even suggest that visually that the Southeast African slave trade might have covered a wider proportion of the TAST come the 19th century), the one directional nature of these visualizations makes these seem not enough like chord diagrams and too much like pie charts. More work and technical know-how is needed to make these achieve their potential.

 

Leave a Reply

Your email address will not be published. Required fields are marked *