Young Guns Driving Semantic Web (Part 1)

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.”