The World Wide Web enters into its next phase called Semantic Web bringing in a new paradigm called Web 3.0. The term Semantic Web was coined by Tim Berners-Lee, the man who invented the (first) World Wide Web. In a Semantic Web, machines can read and interpret web pages just like humans. Today, we can link a Web page to another but we can't link their data together. As a result, we browse through the links and then look for the right data within those links. Even when you use a search engine, you enter key words and get a set of links to websites where related information is available. They don't give you the answer to your specific query, i.e. they don't throw up the data, just the links. Social Networking sites these days are trying to improve upon this with the system of tagging. The Semantic web goes beyond the keywords and into natural language processing. So instead of typing in keywords, you can type in your complete question, and the Symantec web will try to find the answer.
So, Semantic Web refers to the technology of precise vocabularies. Though such kind of natural language processing has been in progress for years, it's only recently that it's started to take off. Some start-ups like powerset, textdigger and hakia are working on semantic search engines. A Semantic Web agent does not necessarily include artificial intelligence. Instead it relies on structured sets of information and inference rules that allow it to understand the relationship between data sources. A computer may not understand information the way humans can, but it has enough information to create logical connections and take decisions accordingly. The data itself becomes a part of the Web in case of Semantic Web -unlike the World Wide Web, which has endless information in the form of documents - and is processed irrespective of platform, application or domain. We can search for documents on the World Wide Web, but their interpretation is left for the humans to do. On the other hand, Semantic Web is all about data as well as documents on the Web so that machines can process and even act on the data in practical ways. So while in the Non-semantic Web (Web 1.0 and Web 2.0), we'll term the word 'snake' as snake. However, in the Semantic web (part of Web 3.0), it would be treated as
Let's take another example. A Semantic Search Engine can answer questions like 'Which Indian author won Booker prize in the year 1997?' It will apply the reasoning based on the fact that that the Web knows the difference between the names of Indian Booker winners, respective years and even the names of books.
|If we search for the keywords “Semantic Web” in Google, it shows all sites containing information about it. However, in a Semantic Web search such as the one provided by Powerset, you get the definition of 'Semantic Web' along with relevant links|
So the emphasis in Semantic Web goes to the back end. A Semantic Web therefore is a Web of relations between resources signifying real world objects such as, people, places and events. It is an extension of the current Web. There is a rich set of links from the Semantic Web to HTML documents. These relations characteristically unite a concept in the Semantic Web with the pages that are most relevant.
Another significant aspect of the Semantic Web is that multiple sites may contribute data about a particular resource. Without requiring any permission from any authority, all relevant data from various sites can extend the cumulative knowledge on the Semantic Web. This distributed extensibility is one of the most important aspects of the Semantic Web.