What is the Web 3.0 and Web3? From semantic web to blockchain and metaverse

De la búsqueda en Google por palabras clave hacia la web semántica

When we talk about the evolutionary stages in which the Internet and, more specifically, the Web has developed, we all identify three fundamental phases: web 1.0, 2.0, and 3.0. Although it has been easy to distinguish the first and second stages so far, now that we are beginning to delve into Web 3.0, also called the semantic web, many doubts arise. What is the semantic web? Are we all talking about the same thing when we refer to Web 3.0 and Web3? What stage are we in now? In 2.0, 3.0? We will try to answer these questions!

The Evolution of the Web: From 1.0 to 3.0 and web3

The internet has evolved significantly over the years, and the web has gone through three major stages: 1.0, 2.0, and 3.0.

  • Web 1.0 was the first stage of the web, and it was characterized by static pages and limited user interaction.
  • Web 2.0 brought about the rise of social media, user-generated content, and interactive applications.
  • Web 3.0, also known as the semantic web, is the next generation of the web. It is characterized by the use of artificial intelligence to understand natural language and provide more personalized and relevant results to users. Web 3.0 is still in its early stages of development, but it has the potential to revolutionize the way we interact with the web.

However, in recent years, another concept has gained greater traction: Web3 or the decentralized web. What is the difference between Web 3.0 or the semantic web and web3 or the decentralized web? While Web 3.0 or the semantic web focuses on understanding the meaning of natural language, Web3 is focused on blockchain and the metaverse. Let’s explore the concepts and, then the differences!

What is web 3.0 or semantic web?

Currently, we find ourselves in a stage where we are fully entering the so-called web 3.0 or semantic web. This is the web that can understand, thanks to artificial intelligence, the natural language of people. To understand this, we should review how users normally communicate with web applications. Let’s take, for example, the case of search engines like Google. When we want to make a query, we usually use keywords to obtain the information we want. If our goal is to find information about the cast of a movie like “Fight Club”, we generally type into Google: “Fight Club cast”. However, think of all the possibilities of keyword usage that this query could generate.

  • A user in Spain could write: “Actores El Club de la Lucha”.
  • A user in Mexico might search for: “reparto El Club de la Pelea”.
  • A user in the USA might search for: “Fight Club cast”.

And these are just 3 examples! Imagine the number of possibilities given the synonyms, countries, etc. In the end, search engines locate those words, with exact matches, in the content of different websites and place them in the ranking of results according to a classification algorithm. But they don’t even differentiate one word from another! They simply count that it is present in the content, regardless of its meaning. From this, two things arise: first, that humans are “robotizing” ourselves when searching for information on the internet; and, second, that machines (search engines, applications, etc.) just count the presence or absence of words, without understanding their meaning.

Web 3.0 has radically changed this circumstance. To simplify (a lot), the machines of the semantic web would understand the meaning of words so that for a specific entity, they recognize all the variants of keywords that can denote it and consider it as a single entity. For example, they would know that “Fight Club” “El club de la Lucha” or “El club de la Pelea” is a movie that can be referred to by several titles, but they are all the same film. This entity (the movie) would be related, for example, to the name of its director (David Fincher), the year of its release, cast, country, etc.

Furthermore, machines would understand natural language so well that users wouldn’t have to search simplistically and robotically with keywords but with the usual linguistic formulations in our lives. How? Think about how you ask Alexa, Siri, or OK Google any query. In a very human way!

How the semantic web works

Web 3.0 uses artificial intelligence to understand the meaning of words and concepts. This allows machines to process information in a more human-like way and provide more relevant results to users.

Therefore, web 3.0, or the semantic web will replace the keyword search system to give way to a needs-based search. In this system, machines will understand us naturally and provide extremely personalized results. Therefore, artificial intelligence, recognition support, geolocation, virtual mobile assistants, voice search, and other technologies like wearables will be the most characteristic of this stage.

For example, if you were to search for “The Fight Club cast” on a Web 3.0 search engine, the engine would understand that you are looking for information about the actors who appeared in the movie “The Fight Club.” It would then be able to provide you with a list of actors who appeared in the movie, along with other relevant information such as their filmographies and biographies.

Benefits of Web 3.0

Web 3.0 offers several benefits over previous generations of the web. These benefits include:

  • More personalized results: Web 3.0 can provide more personalized results to users because it understands the meaning of words and concepts.
  • More relevant information: Web 3.0 can provide more relevant information to users because it can understand the context of their searches.
  • More efficient search: Web 3.0 can make search more efficient because it can understand the intent of users’ queries.

Challenges the future of semantic web

Web 3.0 also faces many challenges, including:

  • Privacy concerns: Artificial intelligence in Web 3.0 raises privacy concerns. Some people worry that AI will be used to collect and track personal data without users’ consent.
  • Data security: The use of AI in Web 3.0 also raises data security concerns. Some people worry that AI will be used to hack into systems and steal data.
  • Technological complexity: Web 3.0 is a complex technology, and it may be difficult for some people to use.

Web 3.0 is still in its early stages of development, but it has the potential to revolutionize the way we interact with the web. As AI technology continues to develop, Web 3.0 is likely to become more sophisticated and user-friendly.

In this old video, created to promote an entrepreneurial project idea called Metaweb, they brilliantly explain what later became something very similar to the current concept of the semantic web. Metaweb was a company that Google acquired to move closer, precisely, to Web 3.0. We recommend you to watch!

What is web3 or the decentralized web?

The Web3, also known as the decentralized web (and, sometimes, also mentioned as Web 3.0), is a future vision of the Internet based on three fundamental pillars:

  1. Decentralization: Instead of relying on large companies and centralized servers to store data and run applications, Web3 seeks to distribute power and responsibility among a global network of users. This is achieved through technologies like blockchain and peer-to-peer (P2P) networks.
  2. Interoperability: Web3 aspires to create an Internet where data and applications are interoperable, meaning they can communicate and function seamlessly with each other, regardless of platform or provider. This will facilitate the creation of new services and experiences that combine different applications and data.
  3. Permissionless trust: Web3 aims to eliminate the need for trusted intermediaries on the Internet. Instead, transactions and authentication will be conducted through smart contracts and cryptography, allowing users to interact with each other securely and transparently without relying on third parties.

In summary, Web3 promises a more open, secure, and democratic internet, where users have greater control over their data and privacy.

Some of the key technologies driving Web3 include:

  • Blockchain: A distributed ledger technology that enables secure and transparent data storage.
  • Cryptocurrencies: Decentralized digital currencies that can be used for transactions in Web3.
  • Smart contracts: Self-executing computer programs that run on the blockchain, enabling the creation of decentralized applications (dApps).
  • Metaverse: A 3D virtual space where users can interact with each other and digital objects.

Web3 is still in its early stages of development. In this video (in Spanish) you can easily understand how blockchain is changing the website to the web3.

So, what’s the difference between the semantic web (web 3.0) and the decentralized web (web3)?

Web 3.0:

  • Focuses on efficiency and intelligence by reusing and linking data across websites.
  • Utilizes metadata and ontologies for machines to understand the meaning of information.
  • Aims to create a more personalized and relevant web for each user.
  • Represents an evolution of the current web, not a radical shift in internet architecture.


  • Emphasizes decentralization and user ownership of data.
  • Leverages technologies like blockchain and cryptocurrencies for a more secure and transparent web.
  • Seeks to eliminate the need for intermediaries on the internet.
  • Represents a more fundamentally different vision of the internet compared to Web 3.0.
FeatureWeb 3.0Web3
FocusEfficiency & Intelligence, Meaning & UnderstandingDecentralization & Data Ownership
Key TechnologiesMetadata, Ontologies, AI, RDF, OWLBlockchain, Crypto, Smart Contracts
GoalPersonalized & Relevant Web Machine Understanding of Web InformationSecure & Transparent Web
Relation to Current WebEvolutionRevolution

Have you got a better understanding on the differences? Hope this post helps you! Let us know in comments!

Acerca del autor

Mariché Navío Navarro

Mariché Navío trabaja en diferentes proyectos del sector de la comunicación online y el marketing digital, compaginando su labor docente e investigadora con la profesional. Sus principales áreas de especialización e interés están relacionadas con la comunicación digital, la innovación docente en la educación superior, el emprendimiento y la aplicación de la neurociencia cognitiva en marketing (neuromarketing), aprendizaje (neuroeducación e innovación docente) y mindfulness.

Es Doctora por la Universidad CEU San Pablo, Máster Universitario en Neuromarketing (UNIR), Máster en Marketing Interactivo & New Media (IEBS), Posgrado en Big Data Marketing (IEBS), Máster en Mayeutik Coaching (Kuestiona) y Licenciada en Periodismo (USPCEU) y en Comunicación Audiovisual (USPCEU). Además, ha llevado a cabo numerosas titulaciones, entre las que se encuentran el Título Propio en Nuevas Tecnologías (USPCEU) y en Liderazgo, Gestión de Equipos y Teletrabajo (UNIR), además de numerosos programas superiores vinculados a la publicidad digital (Google Ads, Social Ads, Analítica Web, Programación Web, etc.) el emprendimiento (Talent MBA, Scrum Máster, etc.) y la Neurociencia Cognitiva.

Como docente, imparte asignaturas sobre comunicación en redes sociales, analítica web y marketing y publicidad online en el Grado de Comunicación Digital de la Universidad CEU San Pablo. Además, es profesora consultora en la Universitat Oberta de Catalunya, para el Máster Universitario en Marketing Digital, donde ha impartido asignaturas como SEO, Email Marketing o Mobile Marketing y dirige Trabajos Final de Máster (TFM). Imparte docencia en otros másteres de la USPCEU como el Máster Universitario en Trade Marketing y Comercio Electrónico o Máster Universitario en Relaciones Públicas y Organización de Eventos, además del progrma de Doctorado. Igualmente, es profesora en Next Educación, donde se encarga de diversas asignaturas vinculadas a Neuromarketing, Inteligencia Artificial y Big Data, Google Ads y SOcial Ads, Google Analytics, Email Marketing, etc.

Como profesional, ha trabajado como Content Manager y Responsable de Comunicación en distitnas empresas y fundado y dirigido startups y proyectos de emprendimiento como Dygeat, Communitools o Funadtics.

Desde el punto de vista formativo, ha llevado a cabo diversas especializaciones universitarias y programas superiores, entre los que podemos encontrar el Curso Universitario de Especialización en Instructor de Meditación y Mindfulness (Universidad Europea Miguel de Cervantes), el Programa Superior de Facebook Ads y Social Ads (AdveiSchool) y el Programa Superior de Google Ads (AdveiSchool), entre otros programas vinculados al emprendimiento y el marketing,

En la actualidad, Mariché es miembro de los grupos de investigación ICOIDI e INECO y los proyectos Algorlit e IBERIFIER. Además ha sido vocal
de la Junta Directiva de la Asociación Española de Periodismo e Información Tecnológica (AEPITEC), y es, hoy, miembro de la Sociedad Española de Periodística (SEP) y de la Neuromarketing Science & Business Association (NMSBA).

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