Up until this point in the semester, the George Mason interns have been working on the individual countries we had been assigned in January. I have been working on the Polish dataset, which has been really exciting for me since I have a personal and academic interest in Poland and Polish cultural heritage.
When I first received the Poland dataset, it seemed to be about eighty percent complete. However, after comparing the museums listed on the Polish dataset to the museums in the book, “1,000 Museums of Poland,” I realized that many of the museums in the book were not included in the dataset. The first edit I made of the dataset was to put the entries into alphabetical order. This made it so the museums were listed alphabetically by town name, which would allow me to discover which museums were missing from the original dataset.
Starting from the “A’s,” I began comparing the museums in the “1,000 Museums of Poland” book to the museums on the dataset. Though I haven’t kept track of how many museums I’ve added along the way, it has been a substantial amount. This process has also allowed me to find duplicates that were in the original spreadsheet. In this way, I’ve been able to streamline the dataset and make it more accurate. I am nowhere near finishing the Poland dataset. I have made it halfway through the alphabet in comparing the dataset to the museums in the book, while also completing entries that had previously been left blank.
With only one month left of this internship, the George Mason interns have been given one final assignment. A main goal of the SCRI is to find a way to share the information they’ve gathered on museums around the world. The leaders of the SCRI have imagined this as a map. Knowing that we have learned skills in the digital humanities, they have asked the George Mason interns for help in determining the best mapping program to use for this project.
As a group, we did some basic internet searches on programs that we have either used in the past, or know could potentially be used for this project. Together, we put various information on these programs into a Google Sheet so we could get an accurate image on which program would work best for us. Ultimately, the group concluded that Google Fusion Tables would be a good option, probably the best for our use.
This program is new to me. So far, I’ve tried messing with the program to see how it works before we figure out the best way to start importing data. I have a spreadsheet that I’ve used for a previous mapping project that I imported into Google Fusion Tables as a test. It worked quickly and easily. So now, the next step is to figure out the best way to go about importing the data. There are still some aspects of the program that we need to figure out. But hopefully, soon, we’ll have a map of the SCRI data.