DATA VISUALIZATION Process Book Oct 15 – Nov 7, 2018 Lily Greenwald
“Hi Giorgia! Still getting used to drawing again, hope I get better!” -Stephanie Posavec
The research for this process was all the collecting without much of the searching. It began by collecting data over the course of fall break. I chose the conversation prompt because when I heard it as an option I had a lightbulb click. I collected conversations that made me laugh, specifically over text. If I didn’t narrow it down to just over text, I would have had too much data to fit on the page; besides that, conversations would become boring because I would be recording everything that was said so I didn’t miss when I laughed, and then, I probably wouldn’t have laughed. Moving on, when we returned from break we had a workshop where we looked at data visualization examples from a wonderful book, Dear Data. After analyzing those postcards, we created very abstract representations of data using prompts like scale, shape and color. It was a fun and freeform exercise that was supposed to help when we began configuring our own data in a visual way.
“For a card about laughter, I am sad about how this card turned out.� -Stephanie Posavec
Discovery was a MAJOR part of this project. In fact, it was almost the entire project. It began by trying out 5 different ways to visualize the data we collected. Immediately when I began drawing smiley faces as a way to distinguish between smart and silly jokes, I felt as though I hit jackpot. What could represent laughter better than smiley faces? I thought adding text bubbles would just further the connection from data to visualization. I realized slowly, I was trapping myself. I wanted so badly to not have an x-y axis and make if fun and colorful that I made everything too representional. After plotting the smiley faces on a graph, it made more sense, but the faces got mixed up and confused in the process. I professed for my love for smiley faces, but in this project I hated them. Every time I tried something with them I thought it looked so childish and boring. So, I had to simplify it more.
“This was a last minute spontaneous decision.” -Stephanie Posavec
What’s the opposite of smiley faces? Squares. I moved away from faces and had to think off a way to represent multiple variables in one mark on a page. I realzied that the only clear way to represent my data was actually in a grided space, no matter how badly I wanted to avoid it. I had some issues now that there was no face to express exactly what I wanted. Instead, I used a combination of circles and squares with different colors to mean different things. It created an interesting pattern, which made me realize that a scatter plot may not be so boring after all. However, I was still unhappy. There was little contrast and the colors kind of just meshed when reading that data. For every plot point I feel like the viewer had to double check they were reading everything correctly. I had to find a way to fix that.
“I threw down my 4 pens when I finished.� -Stephane Posavec
Critique is the reason for the decision that I made at the end of this project. (That is the same line I used for this part of the process book for the last project.) I removed circles completely. When recieving critique, I was asked to look back at what I was playing with in the past: text bubbles. On the iPhone, the text bubbles are more rounded squares as texts get longer. So, I chose that as my icon and instead of layering another icon or a face on top of that, I used one square to mean a whole conversation. Then, inside of the that square would be multiple dimensions. I formed a small distinction between my data and that of partner because it was clear by the quantity of conversations that it was two different people. I guess I laugh a lot more than the average person. When I was finished, I felt as though I struggled enough with this project to be complete, but everything still felt incomplete. If I could go back in time maybe everything would be different.