Web 3.0
The term Web 3.0, also often referred to as the Semantic Web, is used to denote the third phase in the evolution of the Internet, i.e. an era characterised by a strong interconnection of data and an increased awareness of the user’s use of information. As we are currently in the Web 2.0 era, this is the next revolution that the Internet will observe.
This definition was first provided by Tim Berners-Lee in 2006, a computer scientist who can be described as the father of the World Wide Web.
According to Berners-Lee, in Web 3.0, shared content (such as files, HTML code, videos or mp3s) will be associated with metadata specifying their semantic context and facilitating data interconnection.
With this information, search engines (e.g. Google or Bing) and algorithms will be able to process user requests more efficiently and faster.
Every piece of data associated with a piece of content on the Internet will be stored within a series of decentralised databases (among which we can find Solid, the first Web 3.0 archive ever realised and created by Berners-Lee himself).
Within these registers, a large amount of data and information can be stored and extracted.
The efficiency of Web 3.0 will be ensured by the use of artificial intelligence, such as Chat GPT3, and machine learning, i.e. the ability of computers to create data-driven systems capable of predicting future user interactions. These innovations will facilitate the use of search engines by humans, making the Internet an interactive and interconnected place.
Although they are often regarded as synonymous, a distinction must be made between Web 3.0 and Web3.
The Web3, a term coined by Gavin Wood in 2014, is in fact associated with the use of blockchain to promote digital identity and full user control over the content they publish online.
Although several solutions exist to foster interoperability, blockchain technology generally makes it difficult to exchange information between one platform and another.
Web 3.0 innovations, on the contrary, aim at facilitating data sharing and data mining.
