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Web 3.0: Semantic Web

The World Wide Web, the invention of Tim Berners-Lee in 1989, has been a phenomenal success.In just under 30 years, more than 3.81 billion people worldwide have used it, and the Web has grown more prominent over the years with a vast amount of information.

Fortunately, solutions exist to find relevant information in all this content.

Today, search engines, thanks to their crawlers, can recursively browse through the links of billions of web pages and index their content in massive databases. Thus a user performing a search will obtain a list of results classified in order of relevance corresponding to criteria specific to the search engine such as the frequency of keywords, density index, etc.

The solution: the Semantic Web!

The Semantic Web is a concept designed to enable machines to understand the meaning of information on the Web.

The aim is thus to set up, in addition to the network of hyperlinks between traditional web pages, a network of links between structured data. Tim Berners-Lee, director of the W3C, coined the term. He oversees the development of Semantic Web standards proposals.

Resource Description Framework (RDF)

Created in 1999, RDF is a data exchange format on the Web and is the primary language of the Semantic Web. RDF adopts a graph model whose objective is to describe resources on the Internet (Companies, Books, Articles, etc….).

Three characteristics define an RDF data:

  • its subject: the address of the targeted resource
  • its predicate: the property assigned to the targeted resource
  • the object: the value related to the property of the targeted resource


In computer science, an ontology represents a structured set of terms and concepts representing the meaning of an information field. The purpose of ontologies is to express the world around us in such a way that it is understandable by a machine and then to be able to make deductions from it.

There are particular languages to create these ontologies. Among them, we have for example OWL (Web Ontology Language) which is a knowledge representation language built on RDF.
FOAF (Friend Of A Friend) is a project whose aim is to create a network of web documents that can be understood by machines describing individuals and the relationships between them. Without the need for a centralized directory, FOAF allows people to be linked to each other as if everything was described in a single database.

Thanks to these technologies, the machines will be able to understand questions like the one asked earlier.

Various Semantic Web applications:

Different application areas use the Semantic Web technologies.

In social networks where the Semantic Web makes it possible to increase search possibilities and connect members. For bibliographic/documentary classification, the semantic web is also present in companies to collect and analyze large volumes of data.

Even in the E-commerce industry, to describe in a structure the products, prices, and information related to the company, it allows search engines to exploit this essential data better to restore them in their search context.

Importance of the Semantic Web

To say the internet is in a state of flux is an understatement. The internet is always changing, evolving and adjusting. And one of the changes that we could start to see in the next few years is the development of the semantic web.

But what is the semantic web? Why is it useful? And what purpose does it serve?

Understanding the Semantic Web

Before we go too deep into the semantic web, let us break down what it means. The word semantic implies that it has something to do with language. After all, semantics is the concept of properly arranging variables such as letters, numbers, symbols and spaces so words and phrases can be understood.

The same concept is true of the semantic web. It is about arranging information that is located online so that it can be easily understood. But the key aspect to the semantic web is that information should be organized so that it is better understood by machines!

Machine Learning

People are already able to understand information online. Whether you are searching for a recipe, the price of a book or the latest television show episode, information is laid out in a way that you would understand. It is laid out so that you can understand and interpret that information to your liking.

But the problem is that our way of arranging this information online, which is done through HTML and other computer languages, is not applicable to machines. The machines are not able to understand or interpret enough of this information accurately enough or quickly enough.

The semantic web is the idea that machines should be able to do what we are doing today. That machines should be able to seek out and understand the information that is listed online.

Everyone Benefits

The idea of a machine being able to “go online” and seek out information, understand it and then interpret it is scary. But the truth is that everyone would benefit. Not only would machines have an easier time understanding and interpreting the information, but they would also be able to determine if it is accurate. They would be able to distinguish between random information and details that come from a proper source. And that would lead to a lot less misleading and downright false information that we find online today.

Major Organizations Benefit Too

There is so much information on the web. Being able to quickly search through that information for specific details is a hard job. While there are search engines and other tools that can serve this purpose, they are still not perfect.

Having the semantic web in place would mean that sifting through data would be even faster and more accurate than it is right now. Such a concept would be useful for big companies, educational institutes, medical facilities, law offices and more!

Adding Meaning to Data

The problem is that right now machines are able to sift through data based on parameters we set. However, machines are not sure what the data means. There is a huge difference between a machine looking up a phrase and regurgitating the first result, compared to the machine understanding the query and the resulting information that it is receiving.

And with online assistants, AI and other tech on the rise, it will be interesting to see how the semantic web plays into everything. Even future tech such as driverless cars, which may become mainstream in a decade, will be linked to the semantic web. It is all about leveraging the power of machines and the vast information that is available online, so that machines are able to interpret that information in a more accurate and productive way.

Semantic Web and Online Assistants

There is a lot of buzz around online assistants in the past couple years. If you had asked most people five or six years ago about having a personal online assistant in their home, they would find it absurd. But now we have devices from Apple, Amazon, Google and other companies in many first world homes.

People have embraced technology such as the Echo from Amazon or Google Home. Why? Because these devices are designed to make our life easier. Want to know the weather? Ask Alexa. Want to set an alarm or set aside time for a meeting next week? Tell the online assistant and it will do the relevant bookings for you.

But what if online assistants could do so much more? And not just for people, but for companies and educational institutes too.

Semantic Web

Most people have heard about the semantic web in passing, but not in any great deal. The concept of the semantic web is to create a web where information is easily accessible and understandable by machines.

Why is the semantic web an important concept? Because machines have a hard time understanding and interpreting information when it is written out for humans.

For instance, many of the sites that we use to gather information have words formatted around our way of understanding details. Amazon will have the title of a book and its price listed in a way that you can understand. But it does not necessarily mean that a machine could understand that information. Many times, machines cannot understand that information.

It is why online assistants are so limited in what they can do. Setting meetings and finding basic details are easy, repeatable tasks that online assistants are programmed to do. But it is still very hard for machines to gather complex information, determine its accuracy and interpret that information.

That is why so many experts believe the semantic web is a crucial concept.

Future of AI

In many ways, the future of AI will be determined by the success of establishing the semantic web. If there is a version of the web where machines are able to easily read, understand and interpret information, it can only benefit people, organizations and businesses.

It is complicated work to develop languages and concepts so that information we consume is processable by machines. But it is vital work that is going to shape the coming decade of innovation.