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Most of the content on the web is designed for humans. Computers cannot successfully process the meaning of content, though there are efforts towards the same. This is where the semantic web stack, also known as web 3.0 or comes in. It helps the content on web pages to have structure. This makes it possible for bots and search engines to carry out more sophisticated tasks, thus giving more precise results.

For instance, a user searching for a football jersey is able to receive information about their favorite team, their particular details like bio and even when the next match is being played. In this article, we will look at web 3.0, how to understand the 3.0 stack and how you can integrate it into your SEO efforts:

Last week, we covered the Semantic Web for Dummies and its benefits. Consider this the second part of Semantic Web as we dissect and try to understand how everything works.

Understanding Web 3.0

Web 3.0 is, in essence, an advanced version of what we currently have. Information has a meaning that is more defined. Weaving the new version of the web into the existing one has started already.

The fact that the web is universal is what has made it so powerful over the years. It, however, has developed due to a linking of documents, making it harder for results to be relevant.

There are efforts to make the 3.0 decentralized. Computers will need to access structured information sets rules used for "inference", which will be used for automated reasoning. This technology is referred to as knowledge representation.

Thus far, knowledge representation has developed to the level of hypertext during the early stages of the web. This technology will act on the basis of vital applications but it needs to be linked to a global system for its effectiveness to be reached.

At this point, you may not understand web 3.0. Let’s do a little more digging. The current web has been based on a concept we could call "similarity in definition". For you to get results about “parent”, then the meaning of “parent” has to be universal, a mean feat to achieve. If for instance one searched for “Phil Knight’s parents” then the search engine and the source of information (in this case the web page) need to have a similar meaning or interpretation of the word “parent”.

Let’s take the word "parent" and use it in a different context. What if we wanted to search for the parent company of one of Phil Knight’s companies? The meaning of “parent” in this case would be different. Web 3.0 wants to form a system where the meaning of “parent” in both cases can be traced back to the same person, in this case, the Wests, and with each meaning being clear and distinct.

The current web limits the information about a person or thing that can be queried. For a system to be considered successful, it needs to encompass even the questions that could be considered "unanswerable". This is what 3.0 aims at achieving.

Now that we have a clue about what web 3.0 is all about, why don’t we try and understand how it will be structured?

Understanding the Web 3.0 Stack:

Data and information

So far, we have mentioned that web 3.0 will comprise the data and information rather than documents. Rather than being able to link documents via hyperlinks, it will now be possible to link specific data.

Inference rules

The web has been operating on universal inference rules, making it possible to give results. For instance, if the universal rule is for "parent" is "caretaker of a child", then all the results for the word “parent” will need to comply with this rule. Any meaning outside this rule will, therefore, be deemed irrelevant. But what about the meaning of “parent” in another context (as in parent company)?

The inference rule structure of web 3.0 has a more expressive language to allow for the web to "reason widely". The rule also helps to answer questions and determine what action to take. The challenge is, however, coming up with a way to express both the data and the rules that search engines will use for reasoning. The language will need to allow for knowledge information rules to be integrated into the web.

This means that 3.0 will need to use logic in its structure for it to become successful at delivering relevant results.

Web 3.0 Technologies:

There are several technologies being used in the development of the web 3.0. These include XML, SPARQL, SKOS, RDF, and OWL.

Modeling data with the semantic web

By Linkdatatools.com

These technologies play an important part in the structure of web 3.0. They will determine how the above-discussed rules will be created. XML allows for the creation of tags for web page annotation or even the annotation of particular sections. The user can add structure to their documents. The limitation with XML is that the user cannot add meaning to the tags and text sections. This makes it difficult for the people who will create the scripts or programs since they will need to attach the tags to their meanings.

To support XML, RDF (Resource Description Framework) comes on board to bring meaning. RDF encodes meaning in threes. A good example would be a sentence like "The boy ate an apple." In this sentence, the subject is “The boy”, “ate” is the verb, and “an apple” is the object. RDF stores meaning in a similar way to the verb, object and subject.

XML is used to encode the threes. It is, however, the work of RDF to determine whether things have properties that make them the subject, for instance, if it is a person, are they the "owners or guest authors of" or “a sister or brother to” a web page or another person.

This structure makes it easier to describe the data that machines process. URIs (Universal Resource Identifiers) will be used to identify the subjects and objects. A good example of common URIs is URLs. URIs are also used to identify verbs.

Information is encoded using RDFs. This way, concepts are linked to unique meanings that are easy to find around the web.

Ontologies

While RDF makes it easier to relate concepts, it is difficult to tell when two different URIs refer to one thing. This is where ontologies come in. The web is able to create a sort of taxonomy with object clusters and their relations to each other.

For instance, an address could be seen as a location type, while a city code could only be seen as referring to locations. These classes become very important for web 3.0. If a city code is related to a website that discusses that specific city, then it is possible to associate the two even without databases that link the city code and the site.

How Can We Integrate 3.0 Into Our SEO Efforts?

The gist of web 3.0 is to make the web understand more of human language and its complexities. For an SEO expert or digital marketer, this means that you need to take a similar approach in your marketing efforts. Let’s look at how to go about this:

Engaging, resourceful content

There is need to create more engaging and useful content. The focus should not be on the keywords and how well or poorly they are distributed in your content, but on whether your content delivers quality and relevance, and is engaging.

Display factors

Things like title tags and meta descriptions will need to be as good, if not better than your content. They should be engaging from the get go.

Offer assets

Instead of creating backlinks of little value, you can give assets on your website, things that your user will benefit from. Eventually, Google is going try to identify what your site is all about using Semantic web SEO. The more you can describe your site and its layer, the better search engines will start ranking you.

Add more content layers to your site. A good example are content materials, gamifications, free trials, free courses, etc. Many sites need this keep visitors engaged and coming back for more, something that your target market would need and find useful. You can also give a tool or app that your users will find useful, some bonus features to bring value. These content layers can also help search engines identify what you are providing.

Understanding search intent

There are two ways to approach keyword research. You can find the best possible keyword based on rank, volume, competitors rank, etc. But keywords should always be focused on how a user would search. User search intent matters more in the era of semantic web search. Hint: Semantic search is all about identifying intent!

So focus on latent semantic keywords to help with users finding relevant results.