Barbara Liskov wins Turing Award

What a brilliant woman:

Liskov, the first U.S. woman to earn a PhD in computer science, was recognized for helping make software more reliable, consistent and resistant to errors and hacking. She is only the second woman to receive the honor, which carries a $250,000 purse and is often described as the “Nobel Prize in computing.”

I’m embarrassed to admit that I wasn’t more familiar with her work prior to reading about it in Tuesday’s Globe, but wow:

The latter day Ada herselfLiskov’s early innovations in software design have been the basis of every important programming language since 1975, including Ada, C++, Java and C#.

Liskov’s most significant impact stems from her influential contributions to the use of data abstraction, a valuable method for organizing complex programs. She was a leader in demonstrating how data abstraction could be used to make software easier to construct, modify and maintain…

In another contribution, Liskov designed CLU, an object-oriented programming language incorporating clusters to provide coherent, systematic handling of abstract data types. She and her colleagues at MIT subsequently developed efficient CLU compiler implementations on several different machines, an important step in demonstrating the practicality of her ideas. Data abstraction is now a generally accepted fundamental method of software engineering that focuses on data rather than processes.

This has nothing to do with gender, of course, but I find it exciting apropos of this earlier post regarding women in computer science.

Thursday, March 12, 2009 | cs, gender  

What has driven women out of Computer Science?

1116-sbn-webdigi-crop.gifCasey yesterday noted this article from the New York Times on the declining number of women who are pursuing computer science degrees. Declining as in “wow, weren’t the numbers too low already?” From the article’s introduction:

ELLEN SPERTUS, a graduate student at M.I.T., wondered why the computer camp she had attended as a girl had a boy-girl ratio of six to one. And why were only 20 percent of computer science undergraduates at M.I.T. female? She published a 124-page paper, “Why Are There So Few Female Computer Scientists?”, that catalogued different cultural biases that discouraged girls and women from pursuing a career in the field. The year was 1991.

Computer science has changed considerably since then. Now, there are even fewer women entering the field. Why this is so remains a matter of dispute.

The article goes on to explain that even though there is far better gender parity (since 1991) when looking at roles in technical fields, computer science still stands alone in moving backwards.

The text also covers some of the “do it with gaming!” nonsense. As someone who became interested in programming because I didn’t like games, I’ve never understood why gaming was pushed as a cure-all for disinterest in programming:

Such students who choose not to pursue their interest may have been introduced to computer science too late. The younger, the better, Ms. Margolis says. Games would offer considerable promise, except that they have been tried and have failed to have an effect on steeply declining female enrollment.

But I couldn’t agree more with the sentiment with regard to age. I know of two all-girls schools (Miss Porter’s in Connecticut and Nightingale-Bamford in New York) who have used Processing in courses with high school and middle school students, and I couldn’t be more excited about it. Let’s hope there are more.

Tuesday, November 18, 2008 | cs, gender, reading  

Gender and Information Graphics

Just received this in a message from a journalism grad student studying information graphics:

I have looked at 2 years worth of Glamour (and Harper’s Bazaar too) magazines for my project and it shows that Glamour and other women’s magazines have less amount of information graphics in the magazines compared to men’s magazines, such as GQ and Esquire. Why do you think that is? Do you think that is gender-related at all?

I hadn’t really thought about it much. For the record, my reply:

My fiancée (who knows a lot more about being female than I do) pointed out that such magazines have much less practical content in general, so it may have more to do with that than a specific gender thing. Though she also pointed out that, for instance, in today’s news about the earthquake in China, she felt that women might be more inclined to read a story with the faces of those affected than one with information graphics tallying or describing the same.

I think you’d need to find something closer to a male equivalent of Glamour so that you can cover your question and remove the significant bias you’re getting for the content. Though, uh, a male equivalent of Glamour may not really exist… But perhaps there are better options.

And as I was writing this, she responded:

Finding a male equivalent of Glamour is hard but they actually do have some hard-hitting stories near the back in every issue that sometimes might be overshadowed by all the fashion and beauty stuff. Actually, finding a female equivalent of GQ or Esquire is also hard because they sort of have a niche of their own too. I have to agree with your fiancée too, because, I studied Oprah’s magazines a little in my previous study and sometimes it is really about what appeals to their audience.

Well, my study does not imply causality and it sometimes might be hard to differentiate if the result was due to gender differences or content. So, it’s interesting to find all these out, and actually men’s magazines have about 5 times more information graphics than women’s magazines which is amazing.

Wow—five times more. (At least amongst the magazines that she mentioned.)

My hope in posting this (rather than just sharing the contents of my inbox…can you tell that I’m answering mail today?) is that someone else out there knows more about the subject. Please drop me a line if you do; I’d like to know more and to post a follow-up.

Monday, May 12, 2008 | gender, inbox, infographics  

Visualizing Data Book CoverVisualizing Data is my 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. Unlike nearly all books in this field, it is a hands-on guide intended for people who want to learn how to actually build a data visualization.

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 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.