So, not only is Drucker’s article about the different important aspects of digital visualizations and such, but the author seems to like to use big words to make it seem more difficult than it probably is. Either way, this article was very difficult to grasp, so, as a tip, don’t read it when you’re already tired.
After reading through all of Drucker’s pretentious vocabulary, I tried to get to the core of this whole data vs. capta thing. Drucker seems to say that it is important for data to be reconfigured into capta so that it can by expressed in a graphic display. Now, what is the difference between the two you ask? Drucker says that capta is “taken actively,” whereas data is assumed to be known and so can be observed and recorded. Essentially, data is a given, and to reconfigure it into capta, it has to be reproduced using a humanities-driven thought process , thus making it “taken and constructed”.
Drucker not only makes a point about reconstructing data into capta, but she also emphasizes that the representation of knowledge must be acknowledged. Drucker declares that the history of knowledge itself is basically the constantly changing forms of knowledge that we, as humans, have had throughout time. Knowledge has only ever been changed or transformed in the different cultures and times, and so has not been explicitly new, making the representation of knowledge important to what it actually means.
Knowledge representation is key to visualization, mainly because it enables one to see the relationships and patterns between different pieces of information. Knowledge, Drucker says, must be carefully scrutinized and contain theoretical insight in order for it to be used in a graphic display.
Following Drucker’s obscure reasoning and incorporating what Yau said in the chapter of his book, charts and other graphic displays are both knowledge and the representation of knowledge. A graphic display uses set information to exhibit knowledge, but it also shows the relationships and patterns that may emerge upon comparing them. Thus, visualizations of data can reveal new information through the knowledge it already possesses and presents, and also allows for new interpretation to be gleaned from what it is showing.