One of the most important questions I ask myself when analyzing data is how to present this data to the audience. Data visualization means using bar graphs, dot plots, and line charts. This process will allow researchers to understand their data better and represent it. In this essay, I am discussing different techniques that could be used to present data.
Data visualization means mixing between colored, scaled, and Visual cues. For example, using dark and light colors shows the difference between the represented data. Visualization comprises different components, such as visual cues, coordinate systems, scale, and context. There are various visualization methods, making the choice of the color, shape, and size that can be used to represent the data, like mapping, color, geometry, and color. Visualization mainly depends on the data’s size, as little data means little substance visualization. While data with a high number of dimensions, high substance visualization, and more visualization choices, many of those options will be poor ones. To filter out the bad and find the worthwhile options—to get to visualization that means something—you must know your data to present it better.
Today, computers can easily enable researchers to present their data, but sometimes, it is crucial to think more about how you need to give your data to the public. As a public historian, I share my results with the public, which is more complicated than representing data to scholars. It took me longer to figure out the best way to visualize data. For example, public historians prefer to use maps to tell the story of historical size. Using a color that helps the audience understand the map is essential. However, some research requires the use of graphs and points. In this case, I believe using color and shape would engage the public and bring their attention to the study. However, it depends on the data you are presenting. For example, I have used graphs and pie to present my analysis to the public to show them how public outreach projects enhance the understanding of history; of course, I have spent some time thinking about the color that allows audiences to understand my analysis clearly. `
This week’s reading was essential because I learned the best way to represent my data. The reader also helped me to understand how to present the data according to its size. In addition, I learned how to present a map, which is frequently used in my research.
I appreciate your insightful comment on how one must know their data well in order to pick the best tools for visualization. It is interesting to think about these decisions for how to visualize and represent data in an age where many of these decisions can be made by the computer. I was very interested to hear your perspective from your public history background. It does seem very important to consider the best ways to share data with the public despite technological tools that help us make these decisions. I agree that representing data to the public can be much more complicated than presenting it to other scholars. I would love to hear more about common practices for visualizing data within the public history field. It sounds like you are very thoughtful with how you choose wether to create a map or graph (etc.) and which colors you choose.