{"id":1,"date":"2023-10-26T16:27:05","date_gmt":"2023-10-26T16:27:05","guid":{"rendered":"http:\/\/dgahfall2023midterm.lefeversb.sites.carleton.edu\/blog\/?p=1"},"modified":"2023-10-29T23:13:26","modified_gmt":"2023-10-29T23:13:26","slug":"hello-world","status":"publish","type":"post","link":"https:\/\/dgahfall2023midterm.lefeversb.sites.carleton.edu\/blog\/uncategorized\/hello-world\/","title":{"rendered":"Midterm For DGAH 110 Fall 2023"},"content":{"rendered":"\n

Introduction<\/em><\/strong><\/p>\n\n\n\n

For my midterm project, I explored the wolf and moose sightings in North America. Using this dataset, I wanted to visualize where the sightings were located in North America on a map. Thus, I decided to clean up the data using OpenRefine and a bit of hand cleaning. Then, I used ArcGIS to plot the moose and wolf sightings based on latitude and longitude. The result showed that most sightings of both animals were closer to the west and west coast and all over the north of North America.<\/p>\n\n\n\n

Source and Cleaning<\/em><\/strong><\/p>\n\n\n\n

The wolf and moose sighting data set was a large data set given to us for this exam. In this data set, there were a few problem areas that I decided to clean or exclude from my visualization of the data set, along with some that I did not. The first issue was the date of discovery did not have a consistent format. To combat that, I attempted to use OpenRefine. For some, it works; for some other significantly different formatting, I decided to exclude them from the visualization. The other was the inconsistent use of the capitalization of the words moose and wolf, along with the inconsistent classification of the scientific names of each. To fix this, I used OpenRefine and their text facet to simplify these categories. Otherwise, I was happy with the data set and decided to move forward with it to plot it on the map.<\/p>\n\n\n\n

Pr<\/em><\/strong>ocess and Presentation<\/em><\/p>\n\n\n\n

I chose to put the data I worked with on a map using ArcGIS. I did this because the data had exact longitude and latitude, which lent itself to precise placement on the map. To accomplish this, I first looked through the data to see what I wanted to use. I then cleaned the data as per the section above. Then, I got to work creating a map for my data and using a hosted layer for my data set. ArcGIS automatically placed my data using the latitude and longitude, and all I had to do was configure the pop-up and change the icons.<\/p>\n\n\n\n

To configure the pop-up, I decided to showcase the information of the date when the animal was observed, whether there was a description of the image, the guess of the species and scientific name, the coordinates, and whether or not those coordinates were obscured, and the image itself. I decided on these things to show because they gave more detail on what each symbol represents. As for the icons, I decided to go broad and chase all moose into moose from a pack already on ArcGIS and the wolves all into wolves from an image I found on Google. I decided to go broad rather than specific because while the wolf species could get specific, the moose generally did not. It also was not a piece of information I thought was justifiable as what I wanted my map to show did not need that information provided. Then I decided to publish the map as a web app just in case the embed map below did not show up, as historically, it has been a hit or miss if it did. The reason it is on a subdomain on WordPress is because it was a requirement for this project to be on a subdomain, and I thought WordPress would work best for writing up the rest of the requirements for this midterm.<\/p>\n\n\n\n

Here is the link to the web map version if the embed does not work. <\/a><\/p>\n\n\n\n