One of the earliest applications of semantic technology has been to help business users more easily find and access the information they need, no matter where the data is located and no matter who owns it.
Michael Lang, CEO of Revelytix, a maker of ontology-management tools in Sparks, Maryland, is betting that semantic platforms will supplant traditional business intelligence systems. The main reason he's expecting this to happen, he says, is because semantic technology eliminates the need to extract, transform and load all relevant data from disparate information silos into data warehouses and marts that need to be constantly updated.
With semantic technology, all of that happens on the fly and in the background.
According to Lynda Moulton, an analyst at Gilbane Group, a Cambridge, Mass.-based research arm of Outsell Inc., semantic technology can provide significant benefits for enterprises that are confronted with data that has some combination of the following characteristics:
• It's voluminous, with millions of unstructured documents.
• It's complex in scope and depth.
• It's valuable to end users, but in small, disparate pieces.
• It's needed by highly paid and highly skilled professionals for use in their areas of expertise.
• It's undifferentiated for e-discovery and research purposes. That means, for example, that the information lacks metadata and is not available in a structured format that supports intelligent searches.
• It's likely to have an impact on the bottom line, indirectly or directly, when discovered.
Semantic technology can process such information so that it can be "aggregated, federated, pinpointed or analyzed to reveal concepts or meanings" that are logistically impossible for human beings to obtain manually, Moulton says. Early adopters of semantic technology included companies in the publishing and life sciences industries; they're now being followed by enterprises "whose content has grown to proportions unmanageable by humans," says Moulton.
Competing for clicks
Semantic technologies can "make search engines better or more precise in finding relevant content," says Moulton. So if your company operated a retail Web site, that would mean that semantically-enabled searches would do a better job of leading shoppers to your site and then helping them find products they want to buy.
BestBuy.com, for example, realized "high ROI in terms of increased store and product visibility on the Web," Myers says. While adding semantic metadata to product pages on some 1,100 store blogs was no small task, Myers' team saved a great deal of technical grunt work by using GoodRelations, an ontology that German university professor Martin Hepp developed specifically for e-commerce.
GoodRelations provides a standardized vocabulary -- the semantic Web term for ontology -- for product, price and company data. This information can be embedded into existing Web pages, then processed by other computers, applications and search engines that support W3C protocols. As mentioned above, this makes richer product information available to search engines that support W3C standards. It also provides the potential for cross-domain semantic querying across e-commerce sites -- as long as other e-commerce companies incorporate the vocabulary into their data, too. So far, only a handful of retailers have done so, including BestBuy.com and, more recently, Overstock.com.
While Myers could give no hard numbers on time savings, he said that, in contrast with most deployments of new methodologies and technologies, "we spent very little overhead time implementing GoodRelations in our markup." After an "initial introduction," developers typically found working with GoodRelations as easy as coding standard HTML, Myers says.
BestBuy.com is exploiting the power and precision of semantic search not only to help shoppers find what they want but also to bring their attention to specific types of products, such as "long-tail" items that don't generate huge sales, Myers explains. And early last year, his team developed a program, based on semantic Web standards, that makes it easy for store managers to publish information about "open box" or returned products on the store's WordPress blog. Because these products are slightly cheaper, they are much in demand among customers with budget restrictions, Myers points out.
Semantic Web platforms from vendors such as Expert System, Cambridge Semantics, Sinequa and Lexalytics allow users to query both internal enterprise data, and Web sources, including blogs, social networks like Facebook, and other Web 2.0 media.