Web 3.0 is going to be like having a personal assistant who knows practically everything about you and can access all the information on the Internet to answer any question. Many compare Web 3.0 to a giant database. While Web 2.0 uses the Internet to make connections between people, Web 3.0 will use the Internet to make connections with information. Some experts see Web 3.0 replacing the current Web while others believe it will exist as a separate network.
It's easier to get the concept with an example. Let's say that you've decided to go see a movie and grab a bite to eat afterward. You're in the mood for a comedy and some incredibly spicy Mexican food. Booting up your PC, you open a Web browser and head to Google to search for theater, movie and restaurant information. You need to know which movies are playing in the theaters near you, so you spend some time reading short descriptions of each film before making your choice. Also, you want to see which Mexican restaurants are close to each of these theaters. And, you may want to check for customer reviews for the restaurants. In total, you visit half a dozen Web sites before you're ready to head out the door.
The next generation of the Web -- Web 3.0 -- will make tasks like your search for movies and food faster and easier. Instead of multiple searches, you might type a complex sentence or two in your browser, and the Web will do the rest. In our example, you could type "I want to see a funny movie and then eat at a good Mexican restaurant. What are my options?" The Web 3.0 agent will analyze your response, search the Internet for all possible answers, and then organize the results for you. Eventually you might be able to ask your agent open questions like "where should I go for lunch?" However, before this can happen, data will have to be structured in a way that machines can understand.
On the Web, “structured” data means that digital processes can accurately analyze and present information that is procured from the real, physical world. The current standard for enabling this functionality the Resource Description Framework (RDF), an XML-based technology that works on the subject-predicate-object model, where a subject is related to an object through the predicate, and where each subject, predicate, and object are unique resources. In simple terms, RDF describes arbitrary things such as people, meetings, or airplane parts so that it can be categorized according to human perception and be "understood" by computers. The structured data enables the understanding of what a users means to say and how elements of the content relate to each other, within and between data sources. There is no doubt that the current Web is loaded with information, and perhaps even overloaded. The usefulness of this information when it is spread between millions of Web sites is questionable.
To computers, the Web is a flat boring world, devoid of meaning. HTML only describes documents and the links between them. When utilizing a Web search engine, the engine is not able to fully understand the user's search or what motivates it. The search engine simply looks for Web pages that contain the keywords. The search engine cannot determine if the Web page content is actually relevant to that particular search. Results generated by searches routinely number in the millions. Finding just the right information can be a challenge, thus, effectively limiting the value of search engine results for users.
To understand where the Web is going, we need to take a quick look at where it's been.
A little history
The first generation Web utilized a single document mindset -- allowing only limited dynamic interactions. The second generation, dubbed the "Web 2.0" by O'Reilly, has focused on moving towards social networks. It has also fostered rich online media, as well as an explosion in personal publishing. This has created an abundance of information scattered across the Web (sometimes in a haphazard manner). The idea of the Web of Data or Web 3.0 originated with the Semantic Web. People have tried to solve the problem of the inherent inability of machines to understand Web pages. Initially, the aim of the Semantic Web was to invisibly annotate Web pages with meta-attribute sets and categories, which would enable machines to interpret text and put it in an appropriate context. This approach did not succeed, because the annotation was too complicated for people who lacked technical backgrounds. Similar approaches, such as micro-formats, simplify the markup process and thus help bootstrap this particular chicken-egg problem.
These approaches have in common the effort to improve the machine-accessibility of knowledge on Web pages, which were originally designed to be consumed by humans. However, these sites contain lots of information that is irrelevant to machines and that must be filtered. What is needed is a knowledge base so that machines can look up "noiseless" information. The Web of Data concept sprang from both this limitation and the existence of countless structured data sets, which are distributed across the world and which contain all kinds of information. These data sets belong to companies looking to make them more accessible. Typically, a data set contains knowledge about a particular topics, such as books, music, encyclopedic data and companies. If these data sets were inter-connected (i.e. linked to each other like Web sites), a machine could traverse this independent Web of noiseless, structured information to gather semantic knowledge across arbitrary entities and domains. The result would be a massive, accessible knowledge base that would form the foundation for a new generation of applications and services.
Semantic Web versus Web 3.0?
What is most confusing is the difference between the Semantic Web and Web 3.0 – both are conceptual entities. However, rather than competing spaces they should be viewed as successive layers that are developing. By adding the semantic web to Web 2.0, we move conceptually closer to web 3.0. The underlying technologies of the Semantic Web, which enrich content and the intelligence of the social web, pulls in user profiles and identities, and must be combined for Web 3.0 to work.