Writing

Call for Papers: Visualizing the Past

James Torget, by way of my inbox:

I wanted to touch base to let you know about a workshop that we’re putting together out here at the University of Richmond. Basically, UR (with James Madison University) will be hosting a workshop this spring focused on how scholars can create visualizations of historical data and how we can better share our data across the Internet. To that end, we are looking for people working on these questions who would be interested in participating in an NEH-sponsored workshop.

We are seeking proposals for presentations at the workshop, and participants for our in-depth discussions. The workshop is scheduled for February 20-21, 2009 at the University of Richmond. We are asking that people submit their proposals by December 15, and we will extend invitations for participation by December 31, 2008. Detailed information can be found at: http://dsl.richmond.edu/workshop/

Thursday, November 27, 2008 | inbox, opportunities  
Book

Visualizing Data Book CoverVisualizing Data is my 2007 book about computational information design. It covers the path from raw data to how we understand it, detailing how to begin with a set of numbers and produce images or software that lets you view and interact with information. When first published, it was the only book(s) for people who wanted to learn how to actually build a data visualization in code.

The text was published by O’Reilly in December 2007 and can be found at Amazon and elsewhere. Amazon also has an edition for the Kindle, for people who aren’t into the dead tree thing. (Proceeds from Amazon links found on this page are used to pay my web hosting bill.)

Examples for the book can be found here.

The book covers ideas found in my Ph.D. dissertation, which is the basis for Chapter 1. The next chapter is an extremely brief introduction to Processing, which is used for the examples. Next is (chapter 3) is a simple mapping project to place data points on a map of the United States. Of course, the idea is not that lots of people want to visualize data for each of 50 states. Instead, it’s a jumping off point for learning how to lay out data spatially.

The chapters that follow cover six more projects, such as salary vs. performance (Chapter 5), zipdecode (Chapter 6), followed by more advanced topics dealing with trees, treemaps, hierarchies, and recursion (Chapter 7), plus graphs and networks (Chapter 8).

This site is used for follow-up code and writing about related topics.