Human knowledge is captured on the Web in various digital forms: web pages, news articles, blog posts, digitized books, scanned paintings, videos, podcasts, lyrics, speech transcripts, and so on. Over the years, services have emerged to aggregate, index, and enable rapid searching of this digital data. However, the full meaning of that data is only interpretable by humans. Machines are typically incapable of understanding or reasoning about this vast source of information.
The Semantic Web promises to enable machines to meaningfully process, combine, and infer information from the world’s data. With the W3C’s support, a community was formed to deliver a set of technologies, such as RDF(S) and OWL.
Machines become capable of analyzing all the data on the Web—the content, links, and transactions between people and computers. A “Semantic Web,” which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy, and our daily lives will be handled by machines talking to machines, leaving humans to provide the inspiration and intuition. The intelligent “agents” people have touted for ages will finally materialize. This machine-understandable Web will come about through the implementation of a series of technical advancements and social agreements that are now beginning.
Semantic Web technologies attempt to standardize the mechanics of information sharing so that it can be more easily supported in software. It should ...