History of Web 3.0 development

The first central idea of Web 3.0 is the semantic web. Not without the creator of the World Wide Web Tim Berners-Lee, who first described the semantic web in 1994. Later, his 2001 article in Scientific American brought the idea popularity in the Internet community, and the concepts of “Web 3.0” and “semantic web” became almost interchangeable. Now the semantic web is one of the main technologies at the heart of the new network.

In 2007, the author of the modern term Web 2.0, Tim O’Reilly, distinguished the concepts of Web 3.0 and the semantic web. O’Reilly described Web 3.0 as an interaction between the Internet and the offline world. This interaction is realized thanks to sensors and smart devices — what is now called the “Internet of things”.

Web 3.0 today

Web 3.0 is a web infrastructure consisting of several main technologies: blockchain, machine learning and AI, semantic web and Internet of Things. Each of these technologies is an integral part of the future network with its own role in the ecosystem.

Let’s start with the semantic web. The essence of this concept is to make all the information on the network readable and “understandable” for machines. To implement the semantic web of all information in the network, you need to assign metadata — information about information. Thanks to metadata, the algorithm can “understand” the context, build logical relationships between pieces of information and form associations, almost like people.

A key element in the implementation of the semantic web is a set of Resource Description Framework (RDF) specifications from the W3C. RDF is a model for describing information through special machine-understandable statements — triplets. The triplet consists of three parts: “subject”, “predicate” and “object”.

Such statements can describe anything: a person, a web application, or a piece of music.

One of the RDF implementations is the Dublin Core. This is a database of English language concepts for describing any digital or physical resource like a YouTube video or a paper book.

A popular e — book format .epub uses the Dublin Core to represent metadata in OPF files.

Machine learning is a system of methods that computer algorithms use to solve problems without direct instructions. The algorithm is trained to perform a specific task. He analyzes a set of data and independently identifies patterns in them, which he then uses in the task.

Imagine an algorithm that distinguishes cats from dogs in photos. To make it work, the programmers showed the algorithm a lot of photos of cats and said they were cats, and then showed the same number of photos of dogs and said they were dogs. The algorithm analyzed all the photos and determined which data in the photo corresponds to the “cat” tag and which to the “dog” tag. Now you don’t have to distinguish the animals in the photo yourself.

The IBM Watson system and Google Brain’s Tensorflow library are examples of popular machine learning and AI initiatives.

The concept of the Internet of Things (IoT) describes a network of many devices that are equipped with sensors and an Internet connection, interact with each other and can be controlled remotely. The Internet of Things connects the world of web applications with the world of “smart” physical objects: toasters, cars and houses.

Smart home technologies like locks and remote-controlled thermostats are an element of the Internet of Things. Such a house can automatically regulate heating and lighting, recognize the owner at the front door and notify about a pie forgotten in the oven. That’s because every switch, thermostat and kitchen appliance has sensors and controllers that exchange data and instructions over the Internet.

According to TechJury forecasts, by 2025 the number of devices connected to the Internet of Things will exceed 64 billion

For Web 3.0, IoT devices act not only as network access terminals, but also as permanent sources of data about the physical world. So the network accumulates detailed and unbiased summaries of the routes of people in traffic jams with reference to time and geography.

With advanced features for searching and analyzing information on the web, such data can be used as you like: in urban studies, statistics, or in search of the best route to the office. On the other hand, when a centralized structure has control over big data, the risk of information leakage increases. And the interests of such a structure may not coincide with the interests of the community.

Blockchain is a distributed database technology. The information in the blockchain is recorded in a chain of blocks connected in a strictly defined sequence. The blockchain-based system is able to work without a central administration and trust between participants. Instead of the director, decisions in such a system are made through voting. And the actions of the participants are subject to the consensus protocol — a set of rules for creating and writing blocks to the registry.

Blockchain technologies play the role of a connecting element of the Web 3.0 ecosystem. A distributed registry is the basis of a decentralized network infrastructure in which web applications can exchange information directly and all participants are equal.

Thanks to decentralization, the transition to Web 3.0 can solve the problems of opacity of web services, censorship in the network and privacy of personal data. An open public registry ensures transparent reporting. Without a central authority, one participant cannot impose decisions on others or gain access to someone else’s encrypted data.

The blockchain infrastructure for Web 3.0 is already under construction. For example, the Brave project offers an open source browser and a new approach to online advertising, the Storj project offers a decentralized file storage system, and Waves Keeper is a universal authorization solution.