Link to map, also embedded at the bottom of the page.
Source: The source I selected was that off the Wolf and Moose sightings in North America. The data lists the date, location and species of the animal spotted. The data is from the range of 2009-2023. I found the date created section to be the most interesting in theory but also the hardest to just read from the data. In order to see if the date was of any interest I knew I would have to visualize it and then decide if it was worth pursuing.
Process: Their were quite a few steps I took the clean the data. I knew I wanted to analyze the data by time in ArcGIS but for some reason ArcGIS was having a problem viewing the date table as dates. I brought the data into excel and I realized the date was done in multiple formats in Date Observed some of which were not readable by ArcGIS so I decided had to change them all into one format. I first used the find and replace tool to delete wherever it said the day of the week. I then used the “split column” tool to move all of the times(HH:MM:SS) to another column which i then deleted. After this I used format cell to turn the all of the different date formats into the date format of MM/DD/YYYY. I then removed the portions of the data that did not contribute to the graph: the URL, Description, Place Guess, Positional Accuracy, Geoprivacy and Coordinates Obscured. I then split the data in to two separate sheets, one sheet just containing wolf sightings, the other just containing Moose Sightings.
Presentation: I decided I wanted to theme the ArcGIS visualization around nature. I took the basemap Modern Antique and edited the colors to having the landmasses be made of light and dark green and gave the water a more vibrant blue. In ArcGIS I then set the style of the Wolf layer and the Moose layer to follow the date attribute and used continuous timeline color to have a gradient of time be shown on the map. I set the gradients of the two layers to be very different gradients but still with colors that matched the theme, I settled on green to blue for moose and white to black for wolf. I then set the image URLs to appear on the pop up of each data point. Through ArcGIS I then created a basic Webmap that had a button to toggle layers which I then embedded using the code editor in WordPress. In regards to the website itself I decided to use a simple blank theme but changed the main color in the CSS editor to a dirty brown and gave all boxes a green outline.
Significance: I think this visualization of the data gives two main insights. Number one it shows places were wolves and moose have only been recently spotted there. Number two is the inverse, places where wolves and moose have not been spotted for awhile and should probably be checked again to see if their are still large amounts of those animals in that region. I believe that the largest difference in this approach between Digital humanities and Data science is the need for visualization of data, the artistic element and the lack of math involved. This aspect of the data was not really understandable through just viewing the data it had to be visualized and while Data science does involve visualization like graphs its usually not to this degree of complexity. I also believe that data science usually focuses on mathematics of stats and data which this technique contains almost none of but still manages to showcase something about the data.
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