Go to an Internet search engine and ask for a list of researchers who have received NSF grants and who work at universities in states with fewer than 1 million residents.

“It’s not that this multifaceted query cannot be answered by one of today’s search engines,” says Jeff Heflin, associate professor of computer science and engineering. “But it requires cognitive ability on the part of the Internet user, and it also requires trial and error.”

Heflin is part of an international effort to improve the “Semantic Web” by integrating ontologies. An ontology is a set of terms described specifically to provide a common vocabulary for information exchange among people in related fields.

The Semantic Web at present, says Heflin, consists of many independent ontologies, but they require mapping, or alignment.

“Without alignment, the data described in terms of one ontology will be inaccessible to users who ask questions [using the terminology] of another ontology,” he says.

Heflin and his students have developed two prototype Semantic Web domains – one for e-academia and one for e-government – by uploading to a knowledge base 1.5 million realworld Web pages in each category. The knowledge base, called Hawkeye, contains more than 166 million facts from real-world data sources.

“We can query our system and find, for example, all bills dealing with clean air that have been sponsored by Congressmen from states with a population of less than 10 million,” says Heflin.

“Our system can answer complex queries in less than a minute and simple queries in just seconds.”

Heflin was a member of the Web Ontology Working Group, which developed the Web Ontology Language.