The two datasets I will be using for this project are rosters from the National Basketball Association and Major League Baseball five years after integration. The datasets primarily come from information from websites associated with sports reference. I was able to create datasets using this information to include information like the name of the player, age of the player, where they are from, what team they played on, and most importantly for this project their race. This includes data for each team from each league. As this dataset was made by me, I’m still considering adding more data if I find something else I want to explore with this project.
Arc network diagrams are an interesting way of displaying information for a reader. With arc network diagrams, nodes are placed on a single line x axis along with arc that connects the nodes to establish a relationship. The main draw of arc network diagrams is it typically uses thickness as a way to represent the relationship between nodes on the axis. The thicker the arc, the higher the frequency. Where this type of chart can be useful is displaying information that you want the reader to understand connections between various aspects of something. In looking at examples for this type of graph, words and people were frequently displayed in this chart. This included looking at correspondences between politicians and how frequently they showed up in each other’s archives and the frequency of related words that popped up in journal articles. Showing relationships in linguistics and individuals seems to be the best usage for this type of graph.
Owen McCarty & Sarah Scott
The data set we chose was the United States Census for the city of Albany between 1850 and 1940. The federal census is taken once every ten years, so this data set accounts for 10 censuses from the city. Because Albany is a larger city and the censuses span 90 years, the amount of data given is incredible. The Excel spreadsheet has 708,786 cells, each representing a person. Out of curiosity, I tried scrolling to the bottom manually and it took well over five minutes.
The US census began in 1790 and numbers were taken by US Marshals until the Census Bureau was formed. Because there was not overarching federal entity, much of census taking was done on the state and local level. Enumerators would go house to house and get as much information as they could. The 1850 census was the first to feature all members of the household, not just the heads of home. Given the time period, there was also a lack of technology that could be used to expedite the census taking process/counting.
Layers of London. https://www.layersoflondon.org/. Funded by the Heritage Lottery Fund and developed by the University of London’s Institute of Historical Research. Reviewed February 4, 2019.
Developed by the University of London’s Institute of Historical Research, Layers of London is an interactive webpage that with collaboration from institutions across London and Britain, allows a user to interact with a map of the city. The map includes all sorts of pictures of various locations around the city including homes, churches, schools, and other landmarks. The interactive map is easy to use and the search function included in the map allows for the user to easily find what they are looking for.
The University at Albany Campus Buildings Historic Tour is a site that allows for the user to learn about the history of the campuses. This includes former campuses, downtown campus, Alumni Quadrangle, Uptown campus, and East campus.
The way the site operates the information is devoting a section to each area of UAlbany with various amounts of posts in each section. Each post for a building includes a picture, along with a short write up to describe the history of the building. The write ups are definitely the strongest aspect of this site. Each blurb is very informative, but also succinct which allows for the user to not get bogged down on any one page. Navigation on the site is simple as the interface allows the user to easily click on the section they want to learn about.