One such effort is the e-commerce semantic vocabulary. As of now, only a handful of companies, including BestBuy.com and Overstock.com, have signed up for it. Google recently announced that it also supports the vocabulary, according to Hepp Research, which markets and publishes GoodRelations.

"Like telephones and the Internet... the technology becomes more valuable as more people use it," says Phil Simon, a consultant and the author of . What's still missing, for many businesses, is a clear payback that will justify the often major cost of deployment, he adds. A company that wants to make a large body of unstructured information accessible, either internally or on the Web, "can spend years and years setting up a semantic Web infrastructure ... before it sees a payoff," says Simon, noting that such efforts can involve huge investments in cleaning up and tagging of data, plus investments in new technologies.

Indeed, the semantic Web, like many other groundbreaking information technologies before it, may be stuck in a classic Catch-22: A critical mass of users is needed before the benefits kick in, but businesses, particularly e-commerce companies, won't jump in until that magic number is reached.

In his blog, , BestBuy.com's lead Web development engineer, Jay Myers, says: "Product categories can be unique to a retailer/manufacturer, and with billions of consumer products and endless numbers of product categories, universal product categorization seems to be an unreachable goal. I have seen a few attempts at mass product categorization, but I haven't seen a ton of progress (who would want to manage a massive global product taxonomy?!). Furthermore, getting consensus on category definitions seems like a futile effort that should really be avoided."

More optimistically, he goes on, "just because there aren't any universal standards out there doesn't mean we can't start giving machines a shot at some semblance of product categorization" using available W3C standards and ontologies like GoodRelations. "That's a win-win," he adds, "because the business gets satisfied customers, and the customer makes optimal buying decisions based on relevant product data."