Portfolio: Loughran Portfolios Project Proposal

6: Final Project Proposal

I will use three datasets that Prof. Kane assembled for the Module 2: Data Critique assignment. These are the two Jelles Fonda datasets and the Dutch Account books from the Indigenous Economic Data category. I explored the Unidentified Dutch Account book, but I want to look at Fonda’s account books as well and see if I could combine the data entries from all three datasets into one sheet. I think this is possible for the two Fonda accounts that Thomas and Meghan critiqued, especially given that the categorical columns are characterized by similar field names and the information overlaps in a lot of ways. The Dutch Account Book and the smaller Fonda one only have about 400 records combined, but with the larger Fonda account I will have over 1,000 records to analyze.

I was drawn to these datasets because I study material culture. As a historical archaeologist who focuses on the Northeastern US, I’m interested in colonial encounters characterized by the exchange of shared material culture between different groups during the colonial period. The fur trade existed during a time of cultural hybridity, and this had a lot to do with the trade partnerships and relations that transcended cultural boundaries and transformed group identities. None of these datasets have any external abouts, but I would like to compare recorded trade items by year to see how patterns changed from the seventeenth to the eighteenth centuries. To put it in the context of the fur trade, I’d particularly be looking at the frequency of beaver in these exchanges. My secondary research will involve looking into Wendell’s To Do Justice to Him and Myself to better contextualize my data. I’m interested in Wendell’s dataset as well, but for now I’m going to see what I can do with the three that I’ve chosen so I don’t get too in over my head.

There are a few questions I think my datasets can answer: How did payment received for beaver furs change over time, and what does this tell us about the evolution of the indigenous-European trade relationship? Were there differences in the number of exchanges that took place at certain times of the year, based on the available monthly data, and if so, which times were busiest for the fur trade and what were the attributing factors? When did female indigenous traders start to participate in the fur trade, and how did their transactions differ from their male counterparts?

I’ll be highlighting differences between all three datasets by showing how interactions between European and indigenous traders differed from the early to the late eighteenth century in what is now New York State. I’m not only interested in learning about what trade items appeared more frequently over time, but also what became rarer later on. I’d like to see what kind of argument I can propose on the fluctuating states of supply and demand for beaver furs or other commodities. I’m no economist, but I’d like to visualize the rise of prices for certain goods due to inflation or other historical events that significantly impacted regional trade, such as the Seven Years’ War or the American Revolution.

I would like to visualize my data using an ArcGIS StoryMap, so I’m hoping to combine images of fur trade artifacts, Tableau charts, and historical or current maps to frame a clear, identifiable story arc. I’ll also be adapting the Opening-Challenge-Action-Resolution format discussed in this week’s reading so I can present my findings in an organized manner.

2 replies on “6: Final Project Proposal”

Those are all good questions and should be doable, but I strongly suggest using the Wendell data from the start since it’s by far the largest of the datasets. You’ll have a hard time pulling out a lot of those questions using only the other three just because they’re more limited.

For the seasonal question, you’ll want to decide if you’re tracking number of unique visits, or number of purchases made by date. Right now the data for all of those are structured with one purchase per row, and that could skew things to make it look like there are many more individual visits than there actually are. If you just want to track unique visits, you’ll want to give each visit a unique ID number or something and blank down in OpenRefine to make yourself a new, separate spreadsheet to use for that question. Let me know if you want to chat about restructuring your data for your questions at all.

Thanks, I just looked at the Wendell data now and you’re right. It has so much more information than the other three. I’ll start on that unique ID number. I’ll also see if I can still incorporate the other datasets without it being overkill.

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