Reflecting on the semester, I believe I have progressed significantly. I now know where to start when employing computational methods. Before, I would have been totally lost. I have also made good progress with the computational skills themselves. I feel comfortable with markdown. I feel I can use regular expressions (although with much room for improvement). I can use tableau effectively to produce visualizations, and I have a foundation in R from which I might one day advance my skills further. Finally, I have created a website I am proud of, and will use as my own personal website going forward.

Future Potential for My Project.

Envisioning how to use my data was probably the greatest struggle I had at the start of the class, and I still have not become adept at thinking about what my data can do for me. However, I have a strong sense for where I want to take this project in the immediate future. In the Journal de Médecine Militaire, there are articles about medical topography (quality of air, soil, water and general salubriousness of a given region). Similar articles exist in other journals. I would like to gather these articles into one place, clean them, tabularize them, and overlay their information on a map of France. This could produce a color gradient map of the healthiest and un-healthiest regions of the country according to contemporaries. This would be visually stunning, I just need to increase my technical skills to produce such a map. Mainly, I need to think about how to quantify the information within the articles so that they produce a color gradient.

Data Potential for Others

I think a lot could be done with the hospital statistics. If someone knowledgeable with the French army could cross reference these statistics with the situation on the ground I think the results would be interesting. I am somewhat familiar with the army, but I am medical historian and social historian of the military and thus not perfectly equipped to contextualize the numbers I have. An operational historian might do wonders with these data. For example, maybe a hospital had an unusually high mortality rate. An operational historian might be aware of convoy troubles that prevented supplies from getting to that hospital.
I think the biggest inhibitor is the depth of the hospital statistics. More information needs to be found, especially for other years in order to make the data truly useful. What I have not will demonstrate change-over-time well because only details one year of hospital operations. Unfortunately I have not yet discovered any set of tables produced like this for the period between 1630 and 1815.