Blog Post 4: Information Visualization & Distant Reading
Is data valuable if it is nearly impossible to interpret? I would argue yes, it still holds value; however, the reach of who can understand the significance of said data is incredibly limited. In the textbook, Chapter 6 talks about visualization and how it is a tool to bridge this gap, making data digestible for more people. Turning data into a visual form, such as a graph, allows for whoever is viewing the information to understand what it means and why it is significant. If the information was displayed solely in a table, the relationships between two or more entities wouldn’t be as obvious and would cause a lot of people to miss out on a lot of information that could’ve been interpreted if it was presented in a different way. A digital humanities project that exemplifies this point is the Degrees of Francis Bacon. This digital humanities project allows for people to understand the reach Francis Bacon had as a philosopher and scientist. The website allows you to view the data as a list of names and dates which means nothing to the viewer without context. When the data is presented this way, it doesn’t really allow the viewer to understand his reach; therefore, when the data is presented in a graph that visualizes all of Bacon’s networks, and his network’s networks, etc., it emphasizes the influence that Bacon had. It is important to note that there is a responsibility ethically when providing means of distant reading through visualizations as one can skew the viewers interpretation of the data incredibly if the scale, labels, etc. aren’t properly conveyed.
Chapter 7 talks about data mining and its importance to the field of digital humanities. Data mining is the analysis of digital data through a searching for patterns that may assist in determining meaning. In digital humanities, many resources that need to be accessed may be incredibly long and confusing to look at/interpret. Through data mining, one is able to extract the information that is important for analysis. An easy example that was presented in class is a word cloud. During one of the first classes, Dr. M took all of our responses to our selfie project and put it into a word cloud that showcased the most frequently used words in our responses. This word cloud showed an overall consensus on how we felt about looking at a picture of ourselves and analyzing it. Without this digital mining tool that created the word cloud; in order to conclude what the class consensus was, it would have been necessary to read each person’s response and compare them all. This short cut allows for a faster analyzation process. The Yesterday, Today, Tomorrow project does the same thing but on a larger scale, as it maps fear, joy, sadness, and confidence in citizens throughout the COVID-19 pandemic. The data is collected by analyzing over 600,000 tweets from before, during , and after the pandemic through the use of AI as it’s means of data mining. It is evident that data mining is an incredible tool that offers much assistance to the digital humanities field as the faster information can be analyzed, the faster new discoveries and understandings can be made.
I really enjoyed your take on the reading this week! I thought you had a great explanation of how visualization can transform the way data and information is interpreted. My DH project is a memorial timeline for the 9/11 attack and visuals are a huge part of their materials and presentation. Without the visual aspect, I think the severity of the day would not have as much of an impact on the audience as it should. I also think the visuals give victims and heroes of the day the honor they deserve by showing their personal belongings and even pictures of them. It adds a humanistic aspect to a horrific event that really isn't about the wreckage itself, but the impact it felt on our nation socially and culturally.
ReplyDeleteYou also highlighted key aspects to data mining and its importance to every DH project. The 9/11 timeline did not have a lot of raw data on their website, but they did have a lot of qualitative data that needed to be collected and sorted into classifications that were easy to digest for the audience. My website “extracted” data through donations and obtaining artifacts from the government/news sources. They were able to take the raw qualitative data and mine through it to determine the important information for their timeline and construct it in a beneficial and accurate way. This was probably not done through computer analysis, but rather by hand, digging through the information they obtained and mining it themselves. I think this is a cool aspect to the website since the premise is to add humanity to the events of that day and the information was collected and shortened primarily by humans themselves.
I like how you describe how visualization and displaying data in certain ways creates the meaning and significance of the most important pieces of the data. This is the part that people need to understand and view. When it goes hand and hand with data mining, I think you've outlined two more important concepts to digital humanities when dealing with data and finishing the projects. There is always meaning in data, but we have to have systems to extract it, make it meaningful, and display it to people in concrete ways that they can visualize.
ReplyDeleteThe word cloud is a great example (though it was group analysis of a DH project :)). The Bacon site really highlights those relations through the data visualization, where researchers might make interpretations about social or professional connections that may have influenced ideas or writings, etc. This might be like our modern Linked In, except the correspondence was done through social gatherings and letters.
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