Final Proposal: Laura, Andrea and Thai

Here is a link to the proposal: Powerpoint Proposal

Times Newswire Project

This visualization is a tag cloud of the newswire sections. The frequency of the section determines the weight in the cloud.
Parsing the sections to get the frequency was the toughest, but more rewarding part of working on this project.
I had some trouble adding urls for the tag cloud to the project, to make it more interactive. It’s something that I would want to add
in another iteration of the project.

Tag Cloud

I think of this as a widget that could be in the corner of a webpage.

Reading Response #2

Few “Communicating Numbers”

Is it wrong for me to say that this whitepaper is now going to be considered an invaluable resource? It’s a struggle with my own ego to say that I have learned more about when to construct a graph verses a table and why type of graph to use, in this article than and any other point in my seemingly endless education.
The clarity that the article is written in, as well as the principles of decluttering a graph are firmly in line with what good data visualization needs. I should go back to my

Tidwell “Showing Complex Data”

Where Communicating numbers leaves off in general graphical layout and design choices, “Showing Complex Data” drills down into the specifics of interactive data visualization. I often find myself in a quandary when I’m trying a new skill or field of inquiry: “What is that and how can I do it?” This leads to scouring of ‘cookbooks’ and overly generalized sources without something as ideal as this reading. Sometimes seeing a good example, along with the advice of when to use them, is better than a direct instruction set of how to do it.

Reading Response Assignment 1

Edward Tufte:

I found the Tufte article to be extremely useful and engaging, as a first reading for the book. His writing style seemed to meander at first, but as you continue through, you realize that what
might have seemed like unusual examples, were in fact a skillful navigation of numerous examples of data visualization pitfalls and solutions. This brief article has
changed how I approach a data visualization, tremendously. Is it clearly outlines, without superfluous information? Are there too many plot lines? Plot lines are not always your friend? Is the enough space? I would not have thought about having additional information, such as the train timetables, for the sake of readability. I now am overly concerned about data ink, for the better.

Christine Paul:

Paul’s article on database aesthetics started off strong and informational, however, I slowly became more and more dismayed as the date of this article became more and more apparent.
I wanted to read about projects that took advantage of newer technologies and changes. Although it was informational, it did pain me a bit to read about a project completed in 1997, when much of the internet was still in it’s training pants. I don’t want my opinion to be solely on the desire for new, vs. valuable, yet dated information, yet that is what stood out the most to me.

Data Viz Inspiration

Evan Roth’s Graffiti Taxomony

Evan Roth, a Parsons D & T graduate, created a data visualization project that stemmed out of his thesis research. Graffiti Taxonomy was a study of the most common letters used in graffiti and a visual representation

of the diversity of shapes that the letters took. In this representation that is at the Foundation Cartier, Evan uses graffiti that is found around Paris as his survery group. The most common letters that are used for his survey are the letters A,E,I,K,N,O,R,S,T and U. In his presentation, the use is able to scroll through each example, sorted by the common letter and we cna se the original graffiti.

The project  is being presented in the form of an innteractive website as well as a physical representation on the building of the Foundation Cartier.

Graffiti Taxonomy: Paris, 2009 from Evan Roth on Vimeo.

Additional Information on his methodolgy for