I hope to blog more extensively on semantic web technologies, but decided to start with a simple overview of the subject for those just getting started. The following was actually something I decided to write earlier this week after a conversation a colleague and I had with a client. (I work for an online marketing company and the client was interested in how search engines are starting to use structured data when providing search results, i.e. "That's cool! I want that for my site."). I think I cleared things up for him somewhat, so I hope to step back a little further and do the same here. (Note: I may update/add to this post in the future.)
The term “Semantic Web” was created by a computer scientist named Tim Berners-Lee. The name might sound familiar because, back in the very early 90s he invented the World Wide Web (pretty impressive, eh?). At any rate, Berners-Lee also founded (and currently heads) the World Wide Web Consortium (W3C), which works on developing technical standards for the Web.
The technology aims to link up information, on a worldwide scale, in a way that is easily understood by machines. In essence, the Semantic Web will allow computers to process syntax closer to the way humans do by describing things in ways that computers can understand.
For example, consider the following statements:
- The Rolling Stones are a rock band.
- Keith Richards plays guitar in the Rolling Stones.
- "Brown Sugar" was recorded by the Rolling Stones.
Those sentences, and their mutual relationship, are easily comprehended by most people. To be understood by computers, however, they would need the ability to process syntax semantically.
This process is likened to the use of hyperlinks, which connect a current web page to another one, thus defining a relationship between the two pages. However, on the Semantic Web, an important difference is that such relationships could be recognized between any two or more resources, if the information is properly structured.
To do this, the Semantic Web uses special languages for detailing web-based resources and information, such as RDF (Resource Description Framework). Information put into RDF files allows computers to find, extract, store, analyze, and process web-based information, which the Semantic Web can then describe. (For more information, check out the RDF primer and Semantic Web Wiki over at the W3C website.)
Machines can currently use algorithms to infer relationships between different things online, and not without some success (modern search engines, for example). At the same time, with semantic web technologies, relationships between data can now be better understood by machines because of how the data is structured. This adds a greater level of precision than when relying on inferences based solely on hyperlinks, metadata tags, etc.
Simply put: In our era of ever-increasing data on the Web, the upshot of semantic content is that we will be able to use more of it, more often, and for more things.