Abstract from Nova Spivack
How will it evolve from web 2.0 to web 3.0?

We need to do a social organization of our information.
Web 2.0 has been user-generated content, and in particular the practice of “tagging” content with subject tags. Tagging has in turn led to the concept of “folksonomies” in which taxonomies that organize data are evolved in a bottom-up fashion by a decentralized community of users.

The current state of the Web does not provide anything close to the search capabilities or precision of a database today. But that is about to change.

The Semantic Web provides a way to enrich both unstructured and structured data so that it can be queried with the precision of a database. Essentially, it provides a way to tag any information with metadata that explains what it means—and this metadata can be understood by software applications, such as search engines or knowledge management applications. It’s important to note that The Semantic Web is not a new Web, it’s just a new layer of the Web we already have.

The knowledge of the Semantic Web is encoded using special new markup languages such as RDF and OWL.

So when any application, such as a next-generation search engine, sees a Web page or data record that contains RDF or OWL metadata, it can then use that metadata to understand what that page or data record means, is about, what it is related to, and how to interpret it.

In other words, it provides a way to start making the Web “smarter.”

Knowledge Evolution
The Internet and Web 2.0 transformed the process of distributing knowledge even further—enabling a global knowledge commons to emerge. The Internet and Web enable anyone and everyone to become providers of knowledge, not just consumers—a fundamental shift in the way that knowledge transmission and media function. They are not just about the mass-distribution and mass-consumption of knowledge; they enable the mass-creation of knowledge. In some respects these technologies are analogues of the printing press in that they have democratized the process of creating, sharing and accessing knowledge by fundamentally changing the economics of the entire process—making it affordable and accessible to all.

Liberating Knowledge and Intelligence from Human Brains
The Semantic Web virtualizes human knowledge and expertise outside of human brains, and even outside of any particular software application—knowledge becomes essentially just more data on the Web. When we speak of knowledge here we don’t just mean information—the first-order raw data that is currently on the Web—we mean the actual meaning and interpretation of the information that is not on the Web but rather exists only in human brains.
The Semantic Web provides a way to make the meaning and interpretation of information explicit in a form that is unambiguous and publishable, and shareable, on the Web. This will make all this knowledge understandable by software. It’s almost like the invention of a new language—a sort of meta-language for formally expressing what exactly you mean when you say something. The impact of this could be enormous. For the first time in human history, we won’t have to rely only on humans to create, understand and consume knowledge—our machines will be able to help us do this. They will help us work, collaborate, create, explore, monitor, discover, search, innovate, connect, and synthesize. This will open the door to an almost unimaginable amplification of the human mind, and human collective intelligence on this planet.


Amplifying Human Collective Intelligence
The Semantic Web does not replace humans or take them out of the equation. It simply reduces the load on humans, freeing them from some of the pain of information overload, and providing a new path for software to begin to augment and even amplify human collective intelligence.
Today there are several barriers to human collective intelligence that arise from basic limitations of the human brain. Human individuals, and groups of humans, simply cannot process or share knowledge effectively beyond a certain level of information or relationship complexity and change. For this reason, collaboration and collective intelligence are often easier to achieve and yield better results in small groups than large groups.
As group size increases, productive collective intelligence becomes dramatically harder to achieve. Thus, ironically even though larger groups offer the potential for exponential increases in collective intelligence, in practice the opposite is usually the result: the larger teams get, the dumber they get. An entire industry of management consultants and facilitators exists because of these inefficiencies.
The Semantic Web may be able to help with this age-old problem. By enabling software to understand information and relationships, we may be able to begin to automatically and intelligently facilitate interpersonal and group collaboration and knowledge management, and this may finally enable larger groups to become exponentially smarter instead of dumber.

Check out this small tutorial