Before taking Digital history I had very little experience with visualizing data. My experience was mostly through the use excel to visualize the data or through a YouTube video that made creative visualizations from data. This made me have a narrow view on the visualizing data, and after taking this class I learned we can a lot more with it.
I learned new ways to analyze historical data, and how to effectively display it. I discovered the difficulties in displaying time and space in data. When we looked at how an subject traveled such as the fur trade or enslaved people. Here we lacked knowing the how much distance and time it took to go from each location.
Furthermore, the way I’ve analyze data has changed. I’ve begun to look more into the data I use. I research the person who made the data, and the evidence they use. Additionally I look for the motives of sponsors and sponsors of the data. I try to discover if the argument is strongly supported by evidence or if the evidence comes from a single source. I look to see if the data comes from the primary sources or secondary sources.
Lastly, there are a few major ways I can see visualizations lying with data. First as I mentioned before, the idea of time and spaced is skewed. For example the politician’s path visualization lacks the amount of time it took them to become one which can skew the idea of becoming one. Second, after viewing the visualized data of the career of basketball players we see how some data can be displayed can possibly show bias. Here, basketball players can marked as average or superstar but the data used to mark them as such isn’t there. Lastly, visualizing data can lead researching to say correlation equals causation. Just because data has lined up with each other doesn’t mean they are the results of one another. We have to be careful with data visualizations that are showing causation and we should research other possible causation that could led to the results in the data.