ProTips: Visualizations

Aside from the history and explanation of various data visualization types (data maps, time series, narrative graphics, etc.) I found that there were 5 major recurring themes in Chapter 1 of The Visual Display of Quantitative Information. Intuitiveness, effectiveness, efficiency, multivariation, and integrity. I more-or-less agreed with most of Tufte's recommendations, although there are a few personal revisions I'd like to make.

Intuitiveness
Tufte hit the nail on the head with this one. It's important to use common sense and adhere to the basic principles of whatever medium is being dealt with for that portion of the visualization. Example: if you're drawing a bar graph by hand, please use a ruler.

Effectiveness
Getting the message across. If the data or correlation is overly complicated, there's no real reason you shouldn't simplify it to increase receptiveness.

Efficiency
I felt that Tufte placed too much value on space and over-stressed minimizing the use of ink. Yes, it's important to try and reduce the amount of time it takes to communicate an idea, but there are times when ideas shouldn't be broken down any further. If the visualization is electronic, consider having optional, expandable areas of the visualization where viewers may have access to more information should they wish to pursue it.

Multivariation
I disagreed with Tufte on this one. "Graphical excellence", as he calls it, is not nearly always multivariate. True, there are times when more data is desirable, for comparisons or whatever other purpose you can imagine. However, there are also times when it's ideal to have as little variables as possible. The less variables involved, the simpler the data, the more straightforward the visualization, the easier the communication.

Integrity
A no-brainer, really. Unless it's the purpose of the visualization, it's unprofessional to fabricate data or skew graphical representations to help make a point. (Ever noticed how America appears huge on some maps and much smaller in others?)

Processing: Mapping Exercise

Just finished working away at the example in Chapter 3 of Ben Fry's Visualizing Data. Ended up with a nice, bouncy, interactive map visualization, and an understanding of:

• How to map data
• How to provide extra mouse interactivity
• How to smoothen shape growth in Processing. 

 I can't be the only one who held space at this point...

BitTorrent Visualization

Seen this a while ago but only recently noticed it was actually coded using Processing!

It's an interactive visualization demonstrating the roles of peers and seeders in a swarm!

Linky

BitTorrent is cool.

Assignment #1 DataSet

The dataset I have chosen for Assignment #1 is an up-to-date list of roller coaster record-holders. This includes a list of the 10 fastest roller coasters in the world, their top speed, theme park and country of residence, and opening date.

Roller coasters are awesome.

Source:

“Record Holders,” Roller Coaster DataBase, accessed January 21, 2013, http://rcdb.com/rhr.htm.

Well hello there

Hi!

My name is Alexander Ornat – I’m a third year Digital Media major at YorkU. I dig media stuff like design, video games, and photography, so it's no surprise I am currently taking a course which focuses on data visualization and data art. You appear to have stumbled upon the blog which follows my progress through this course. 

Data art and visualizations are what happens when you combine any form of sensible data (whether it be qualitative or purely quantitative information) with some form of visual expression (most often using digital tools). The result may be used to clearly communicate a pattern present in a data set, or it may cryptically work to inspire a viewer into deeper contemplation concerning an issue. Either way, data visualization appears to be an effective communication tool suitable for executing a wide variety of tasks.

I hope to learn more about the process behind creating data art and visualizations, and about the authors behind popular works. I’m also excited about finding new ways to use Processing, and can't wait to begin creating data visualizations of my own.