Moose And Wolves Map – Midterm Assignment

Jane Parson – DGAH 2023

For my project, I chose to use the moose/wolfdata set, and implement it in an interactive map using ArcGIS. Using the tool below, you can scroll across north America, and view individual moose and wolf sightings, along with photos, background information, and the dates they were viewed.

As mentioned previously, I chose the moose/wolf dataset, because I thought out of all the sets we were given, it would benefit the most from a more intuitive visualization – location in raw coordinates isn’t really possible to sift through by raw text, and this sort of compilation lets you see where specific species clump up.

To process the data, I went through and cut out as much of the excess information as possible. For example, the “best guess” entry for species was split between the common and scientific names, even though both of those existed as separate columns. Additionally, the “location concealed” and “geoprivacy” columns had identical data, and so one could be removed.

When it came to visualizing, there were a few priorities I had. Moose and Wolves had many different subspecies, but I wanted to make clear at a glance which each data entry was. Because of this, I split all of the wolves into different shades of red, and the moose into different shades of blue, making the map easy to read at a glance. I also wanted to put the images submitted at the forefront of each data point- rather than needing to click a link, each is clearly visible on the datapoint, letting the user see both the environment at that point on the map, and the animal/signs of an animal in question.

This kind of visualization is important in digital humanities because it gives access to the bigger picture. Having a clear image of your data lets you understand patterns in a way that would be otherwise near impossible – to find that only wolves exist on Vancouver island, you’d need to go through the hundreds of thousands of lines of information and sort out every point by location, something that would take months, if not years. By automatically placing each data point out this way, you have instant access to that larger picture.