Data Visualization and Mining

 


I love the idea of being able to interpret data easier by visualizations. As we all have learned so far data is an endless wonder of information and that can get confusing. Chapter six discussed different forms of visualisation data like graphs, charts and diagrams. It also discusses the different important variables that graphics need to be interpreted correctly/easier like ize generally indicates quantity, but can signal importance, particularly with typography. Color, like shape, is very legible and makes distinctions highly visible, as does texture"(Drucker 98).  Speaking of interpreting data more easily, another thing aI learned about was data mining. In chapter seven, it talks about how data mining can be helpful when recognising large amount of data. It did however specify that "Data mining only takes place on the information literally in the file, so clarification about the process is essential" (Drucker 110) which makes sense with how big and complex we know the digital humanities to be. 

After learning this new information I looked at the Six Degrees of Francis Bacon. This one was interested because although I found it highly intimidating to look through because of its busy looking appearance, I do agree the data being displayed in charts made it easier to understand. This project relies basically only on the graphics which is why I think it worked for it. On the other project Yesterday, Today, and Tomorrow, data mining was a main factor is this site because it allows you to narrow in on the large amount of tweets that they gathered sorted into different months. 

Comments

  1. CamSeptember 26, 2022 at 7:07 PM

    Hey Kait! I thoroughly enjoyed the quote you used for data visualizations; having color and an eye-catching visual makes data consumption significantly more enjoyable for a general audience. I liked that you chose to talk about Yesterday, Today, and Tomorrow as an example of data mining, because I actually chose Six Degrees as my data mining example. Your reasoning makes so much sense! Both projects offer so much from both a mining and a visual perspective!

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  2. Jordan RobichaudSeptember 27, 2022 at 2:03 PM

    Hi Kait, I really like your approach here in your response. I can tell that you enjoy learning more about more design-specific data visualization, which is cool to think about. Where I focused more on the types of data visualization available, you made me think about the importance of color and texture. I also like the comparison to data as "an endless wonder of information."

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