Writing

You stick out like a sore thumb in the matrix

Finally got around to watching Dan Frankowski’s “You Are What You Say: Privacy Risks of Public Mentions” Google Tech Talk the other day. (I had the link set aside for two years. There’s a bit of a backlog.) In the talk, he takes an “anonymized” set of movie ratings and removes the anonymity by matching them to public mentions of movies in user profiles on the same site.

Interestingly, the ratings themselves weren’t as informative as the actual choice of movies to talk about. In the case of a site for movie buffs — ahem, film aficionados — I couldn’t help but think about participants in discussions using obscure film references as colored tail feathers as they try to out-strut one another. Of course this has significant impact on such a method, making the point that individual uniqueness is only a signature for identification: what makes you different just makes you more visible to a data mining algorithm.

The other interesting bit from the talk is about 20 minutes through, where starts to address ways to defeat such methods. There aren’t many good ideas, because of the tradeoffs involved in each, but it’s interesting to think about.

Monday, September 7, 2009 | privacy, speaky  
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.