Jennifer Zaino
SemanticWeb.com Contributor

In the last few years, computer science has lost some of its luster as a career option for the next generation. But there's reason for excitement again, as semantic web standards pave the way for new technologies, services, and business opportunities.

Just ask 27-year old Christian Halaschek-Wiener. He recently received his PhD under the direction of one of the seminal figures in the semantic web community, Dr. James A. Hendler, from the Computer Science Department of the University of Maryland. Now, Halaschek-Wiener is a chief technical officer at a startup in the San Francisco Bay Area within the financial domain.

At the University of Maryland, his dissertation work was essentially an application of some of the reasoning capabilities that languages such as OWL can provide, especially around content dissemination over the web -- in colloquial terms, news aggregation on steroids. Halascheck-Wiener says he really enjoyed the time he spent in academia, but by transitioning to the private sector he could make sure that he could continue investigating some of the more practical aspects of applying some of these technologies to real world problems.

Another reason: "Right now in the more commercial space, it's quite an active and newly emerging area, so the timing seemed quite good to move out," he says. "There's some common names that we are seeing in the media that are very vocal and active in the space, like Radar Networks and Metaweb. I think we will continue to see companies such as these coming up with new and innovative ways to apply the technology."

Having new and interesting problems to solve in a constantly evolving area is a good reason for getting up to go to work each day, he says. "That's what's unique about this field."

Another young tech, Aditya Kalyanpur, who started graduate studies at the University of Maryland in 2001, has also moved to the commercial world, working at IBM TJ Watson Research Center "on an exciting project that aims to solve one of the main barriers to the adoption of Semantic Web technologies -- scalability of ontology reasoning on the Web. When he started his graduate studies, Kalyanpur says, there was quite a bit of buzz forming around the semantic web. Hendler, his advisor, had just written about the semantic web vision with Tim Berners Lee and Ora Lasilla in the Scientific American; some early W3C standards activity was taking place around semantic web languages such as RDF and OWL; and numerous academic research projects were taking off in this area.

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One such project at the University of Maryland that caught his eye was SHOE (Simple HTML Ontology Extension) which was about adding simple tags to HTML to describe web page content better using ontological entities -- categories, relations, and rules. A relatively simple Knowledge Representation language, it demonstrated the value of adding a semantic layer over HTML to do tasks such as search better.

"The research area is clearly relevant, presenting opportunities for high-impact work given the pervasiveness and popularity of the Web, while being challenging, due to the numerous social as well technical issues that come from applying KR principles to the Web," Kalyanpur says.

He's excited by the huge potential for developing mainstream semantic web applications thanks to advances in AI algorithms and the push toward establishing a large community around shared knowledge resources. For example, the W3C-backed "Linking Open Data" project aims to consolidate the rich knowledge-bases around open, accessible and structured repositories such as DBpedia, GeoNames, MusicBrainz and their ilk into a giant "data cloud," whose datasets are all exposed in RDF and interlinked to related ones, he says.

"This is a very promising initiative, since as this community grows, we should expect to see more mainstream semantic web applications and services leveraging this wealth of structured information," he says. "Already, we have seen a few interesting prototypical applications come out of the Semantic Web Challenge that make use of third-party datasets, such as an ontology-backed multimedia search engine, and a general-purpose reviewing and rating site, Revyu, which uses RDF beneath the covers. On the horizon are applications such as PowerSet and Twine which combine NLP, machine-learning, and semantic web technologies to do smarter search and analytics."
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."