Data Visualization & Mining

 In reading chapters 6 & 7 of The Digital Humanities Coursebook, I was able to extract new information to further expand my knowledge (thus simultaneously losing myself further in the abyss of all digital humanities can be), particularly concerning the topics of data visualization and mining.

In terms of data visualization, I found the name itself to be fairly self-explanatory, however the details in its construction and representation provided a lot of information I didn't know. For example, I learned that there are two components to visualization: metrics and graphics. Through these components, information and data can be represented in numerous ways, and a choice between which visual representation to use can be made to best aid readability and consumption of the data. It is also noted in the text that one of the best ways to decide what kind of visual to use is to decipher whether the data is discrete or continuous. Before reading chapter 6, I had a rough idea of the benefits/reasons to use one kind of graphic over another, but I had no idea that data was classified as discrete and continuous, each being better suited for particular visuals than the other.

In terms of data mining, I wasn't so sure what it was, aside from being fairly certain it involved extracting data in some way. From chapter 7 of the book I learned that it involves finding patterns and taking information from digital files. Also, I learned that though it's useful for extracting information from a large pool of data, it is not used for this exclusively. It's also important to note that data mining always processes digital files, so there is room for error. This would happen in a case where a photo of a sculpture is assessed and extracted from as opposed to the sculpture itself. This being said, data mining is not limited to text, but can be represented in other formats as well, such as photos. There are also many analysis and computation tools used to "mine" data.

Comments

  1. Dr. MSeptember 26, 2022 at 10:38 AM

    Oh boy, it's at abyss level now! We've already seen some great examples of mining and visualization!

    ReplyDelete
  2. NataliaSeptember 26, 2022 at 5:31 PM

    Hello, I liked the point you made about how data and information can be represented through numerous ways. I liked that you included how data can either be discrete or continuous as well. In chapter seven I learned a lot about the errors that could go wrong with data mining as well.

    ReplyDelete

Post a Comment

Popular posts from this blog

Maps & Virtual Spaces

  I thought it was interesting to learn about the range of complexity that is mapping and GIS, just like digital humanities. It seems that the more qualities of the digital humanities that we learn, the more it helps to break down what the digital humanities are. That being said it is odd that adding complex features of the subject would make it easier to understand. For mapping, it seems to be complex in the way that there are so many ways to layer the information that is to be given. I like that the chapter on the subject in our textbook broke down the different purposes of using maps to relay information.  The text also discusses a virtual exhibit created to recreate Pompeii. This reminded me of when I visited Pompeii, I got to see some of the 3D models that were created to represent its appearance, and I even remember there being a virtual exhibit that broke down the volcano erupting and the pattern (most likely based on evidence gathered) in which it buried the city.  On the googl
Read more

What is digital humanities?

  Kaitlin Carroll     When I think of the d igital humanities the first thing that pops into my head is a computer. Whether thats accurate or not it's what pops into my brain. Digital obviously makes me think about electronics, and then following it with humanities make me think of how people interact/express themselves within those electronics. After playing around with the blog and reading some of the Digital Humanities course book, the definition of digital humanities can be interpreted to be combining humanities properties with computational methods. (Drucker, pg 1). The components that Johnna Drucker discussed in her book of digital humanities were most helpful at breaking that subject down for me. In the manifesto, it is explained that it is hard to limit what can be classified as digital humanities because the subject is wide with various allowances of what counts as the category. I like this because then digital humanities is a perfect way to be expressive in a persons own
Read more

Data and Visualization and Mining

Chapters 6 and 7 taught me a lot of new things in terms of data mining and visualization. To begin, data visualization is putting a given set of data into a graph. They help to see patterns that are happening through different types of graphs such as; bar, line, bubble, and pie charts. The important part about data visualization is how you choose to express it, as said in the text "The challenge is to understand how the information visualization creates an argument and then make use of the graphical format whose features serve your purpose" (90). The key thing to note when it comes to rhetorical graphs is questioning the creator of the content as sometimes it can be deceptive. I also learned about networks and the complexion and how it "is that the development of the system cannot be predicted-- because the processes are nonlinear and/or non-deterministic from a statistical standpoint.  Data Mining as defined in the book "is an automated analysis that looks for patt
Read more