Members of the Group: Blossom Booth, Quan Tran, Selam Nicola, Genesis Rojas
Methology
Our data will be obtained through Carleton’s digital archives of the Zoobook. The Zoobook’s are in PDF files, so transcribing the data of students hometowns from them would be easier. We will develop a code to pull data from the Zoobook to organize and categorize the data. The analysis that we will conduct from this data is what the students hometowns have been over the period of 1955-2015. The results will be presented on an interactive map which will be done with the usage of ArcGIS.
Proposed Timeline
5th-7th week we will be working with the data through transcribing.
7th-8th week we will be figuring out the delivery of our presentation.
8th-10th week we will be finalizing our map.
Project Topic & Objectives
Where do Carls come from? Our project will cover the states and countries that students are from during the period of 1955-2015.
DH Project Model: This is a good visual example on how we want to display our data.
This sounds like an interesting project! I’m curious to see the overall trends in where students come from and see if there are any particular aspects about their hometown that may show they are more likely to choose Carleton. Your post was informative, and gave readers a general overlook for the project in mind, but I think we could benefit from any more specific details you may have at the moment. If not, it looks like it’s off to a great start!
Yeah, like Tonya, I’d really like to see if there are any trends concerning the location of Carleton students’ hometowns. It’d be cool to see just how the demographic makeup of these students changed in the past 60 years, too. I also think a few more specifics could come in handy, but it seems like a solid idea right now. Also, I’m digging the title.
I agree with the other two commenters, it will be really cool to see if there are any trends from where students come from. I think that the DH project you want to model it after in order to display your data is a really good idea.
Hi Stalker Team (not sure about that title…),
I really like the concept of your project, and the Zoobooks are a great source for this.
As I mentioned in class you’ll need to make sure you anonymize your data, since you’re dealing with fairly recent graduates. You’ll also need to consider if you can find comparable data from the Algol yearbooks or other sources for pre-1955 classes, since ideally this project should cover the years from 1916 forward.
You also may want to have a look at some other possible tools for this project. ArcGIS might work, but CartoDB could provide some interesting visualization options through its torque map features. And you might also explore Palladio. It is what the Republic of Letters project you link to was built in, and might allow a nice combination of map, timeline and network analysis if you find members from similar schools over your data set. Here’s a nice overview video tutorial and a step by step lesson courtesy of the Programming Historian.
I can’t wait to see what you all produce!
Team Stalker Map,
I really do think Palladio would be great for this project and this tutorial video shows an example that you could really imitate quite easily with your data.
You already have the world cities list that Quang found to extend your data with places, and if you added a column for destination and filled it with Northfield, MN for everyone, you could produce a map much like his for Monaco. And you should definitely add a class year column with dates.
We don’t want to expose the names, but it would also be great if you could predict the genders and do some analysis based on that data. You can download historical name/gender data from the Social Security Administration that includes 1916-2014, and Quang’s python script could easily be edited to add gender to your data matching against these.
Finally, if anyone knows, or wants to learn, R, there is also a good tutorial for using these data with the R gender package.