Tim Berners-Lee was in the Economist the other week (subscription is required for the article):
Analogies between the web and the brain have long played a profound role in Sir Tim’s thinking. He is the son of two mathematicians who worked on the team that developed the world’s first commercial, stored-program computer, the Manchester University Mark 1, which was commercialised by Ferranti, a British company, in the 1950s. He remembers his father reading books on the brain, looking for ways to make computers able to identify connections between things, as the brain does.
This line of thought has stuck with Sir Tim and is at the core of one of his most enduring passions, the semantic web. Whereas the web today provides links between documents which humans read and extract meaning from, the semantic web aims to provide computers with the means to extract useful information from data accessible on the internet, be it on web pages, in calendars or inside spreadsheets. Such data—much of it stored in databases that can be queried by humans via the web—is part of what is referred to as the “deep web”, and cannot be accessed by the web-crawler programs used by most search engines.
No one knows exactly how much information is in the deep web, but estimates range from hundreds to thousands of times more than in the “surface web” that search engines currently index, which is thought to contain over 10 billion pages. If semantic-web technology can help computers access even a fraction of this hidden data, and make sense of it, it could make possible new forms of searching and would even allow software to retrieve information and make deductions from it.
This is the clearest explanation of “semantic web” I’ve read.
We think of the internet as there to serve us, but it only works as well as it does because someone thought of a way to order information in a way that a machine can understand. In this view, improving machine comprehension is still the way forward, rather than a solved problem.
