Not every young technologist contemplating his or her career options wants to enter the commercial field, but no worries on that front. Academia holds plenty of opportunities for those who’d like to build a teaching career centered around their interest in semantic web technologies.
That’s the route chosen by Jennifer Golbeck, who is in her first year as a faculty member in the College of Information Studies at the University of Maryland. Cited in 2006 by IEEE Intelligent Systems as one of the 10 top young scientists in AI, the 31-year old Golbeck is one of the all-too-few women taking recent semantic web leadership roles, Hendler says. Her thesis was the start of her work on social networks and the semantic web, revolving around the concept of how you apply trust in social networks -- a critical factor in determining the validity of sources in the web of data. She built a movie recommendation system that used predictive recommendations about which movie you might like based on averaging how much the movie was liked by other people you trusted within the social network she created. And it worked.
In the three years since she finished that work, part of her time has been figuring out how to extend the model for computing trust beyond her purpose-built social network that let users specify how much they trusted one another Golbeck says she felt the call to academia long before she realized that computer science -- and ultimately the semantic web in relation to social networks -- provided her the route to operationalizing her interests in analyzing complex systems. (Golbeck was on her way to an undergraduate degree in political science when, in her fourth year, she changed her major to computer science.)
“I’m drawn to the pure pursuit of knowledge vs. the development of things as a product,” she says. “I wanted the freedom to look at whatever kinds of problems I thought were interesting, and pursue them just for the knowledge part, vs. taking what I think of as the tedious extra steps to get something robust that would work in the marketplace.”
But, even as the emergence of the semantic web and its intersection with social networks is opening up exciting new frontiers for young technologists to explore, Golbeck is concerned that not enough women will hop on the wagon train. Last term she taught a class for master of library science students with two men and 28 women -- the first time she had been in the presence of that many women in a classroom setting in years. In computer science, “women are a tiny fraction, not even ten percent,” she says, often a result of the fact that boys are encouraged early on to play around with computers, video games, and so on. So, by the time they get to undergrad programs, they already have some experience in lightweight programming that a lot of girls don’t have.
“So you get into classes where they are supposed to introduce the material, but most of the guys have some experience and so they skip over some of the stuff. That’s really discouraging,” she says. “And, if you get discouraged, you might be more apt to find a major that’s more comfortable for you.”
She’s working to change that, with plans to introduce dedicated semantic web classes not from the computer science perspective but from the distributed information management perspective that fits into the model of the information studies school, where majors include masters of library science and information management. “For those kind of people the semantic web is just a perfect idea,” she says. “The most exciting part is taking all this distributed information that’s all over the web in a form that people can’t handle, and being able to do really exciting things with it. These are the people who would be most interested in this and receptive to solving this part of the problem.”
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