Websemantics & SEO

As opposed to web 1.0, which was essentially a consultative web, a spectator's web, the current web is very collaborative, social. It is logically called web 2.0. Its inventor, Tim Berners-Lee predicted a few years ago that we were entering the 3rd phase of the web. This is the semantic web. 

To sum up, people can now collaborate, but machines still do not have standards enabling them to do so. Web 3.0 allows, thanks to standards being finalized, communication between databases and their intelligent processing. The web will be semantic because the Internet offers a particularly powerful playing field for standards that have existed for a long time. These systems are now fully powerful thanks to the mass of data stored on the web.

Technically, How Does it Work?

The basic notion of a semantic web is ontology, a representation of the properties of what exists in the real world in a formalism allowing automatic processing. There are ontologies in all areas. If we take the cinema as an example, we will integrate into the system that the director of the film “For a Fistful of Dollars” is “Sergio Leone” and that Clint Eastwood is the main actor. If we extrapolate this example to the web, made up of millions of data items, it can give intelligent reconciliations.

How to make your site more semantic?

The semantic web will be useful for a large number of applications:

- Make search engines smarter

- Describe and process multimedia documents

- Building multilingual and multicultural solutions

- Allow the fusion of very diverse information

In general, the semantic web is still in its infancy. It is still complex to develop your site with this type of functionality. Despite everything, you have to get into the habit of thinking "semantically" by installing, for example, a tag cloud system on your site or by structuring your data as much as possible.

According to Fabien Gandon, no one is yet very familiar with this concept to which many names are attributed, which themselves represent a different aspect of the semantic web. There is therefore the web of data, the “Giant Global Graph”, the “Linked Open Data”, the web 3.0, etc. To fully understand them independently of each other, we must start from the web of data. 

As the web is characterized by linked pages, we remain in the documentary domain. With data web, on the contrary, works directly with databases. The data is also related via links. We therefore no longer work only on documents but on raw data. This vision gives birth to the Giant Global Graph as soon as millions of users will be able to link and exchange data between them. Linked Open Data is a set of data that can be put online and linked. 

We are thinking in particular of government, university, etc. data. Finally, websemantics consists of giving meaning to data by explaining their pattern. For example, when an Internet user searches for a report, we can link report to document, which will make it possible to present to the Internet user not only reports but also documents. These will be classified into sub-type. We therefore create data classes. which will allow him to present not only reports but also documents to the Internet user. These will be classified into sub-type. We therefore create data classes. which will allow him to present not only reports but also documents to the Internet user. These will be classified into sub-type. We therefore create data classes.

As you will understand, the semantic web is a model that allows data to be shared and reused between several applications. The aim is to make it easier for users to find, share and combine information without intermediaries.

Websemantics Applications

RDF language

RDF (Resource Description Framework) is a standard language for describing and structuring resources which, as its name suggests, delimits them in a frame in the form of triples:

- subject,

- predicate,

- object

Resources can be defined as an identifiable object. The language is expressed in the form of a graph that can be transposed into coded language, independent of any syntax, and is used to define models for the representation of data whatever they may be. RDF is therefore the precursor language of web semantics from which other languages ​​have been based, notably OWL. If you have passed the CESEO exam, you will certainly have seen a question pass on it😉

OWL Language

Founded from RDF, the OWL language (Web Ontology Language) pursues RDF's desire to give meaning to data in order to make them interpretable by machines. Currently, the raw data does not allow them to return convincing results to the Internet user when it comes to a precise search (we will see that there are fields of applications that are starting to produce significant results. Google's Knowledge Graph in particular). 

Here, we are no longer talking about keyword queries proper, but questions to which web users will expect an answer. Example: let's say that I want to accompany my menu with a good wine and that I ask the following question to the search engine: which wine to pair with my bœuf bourguignon? Only the websemantics and the description of the data, grouped together as interrelated classes and properties, will allow the machine to return a consistent result. 

The data alone does not make it possible to be intelligible to the machine which needs an encompassing structure. Unlike RDF, OWL provides additional information. Indeed, where RDF was content to assign classes and parameters to resources, OWL goes so far as to compare them, in order to help the machine to interpret the request. OWL uses a less restricted vocabulary thanks to comparison tools such as identity, cardinality, equivalence, etc. a bit like in object-oriented programming for example. 

The data alone does not make it possible to be intelligible to the machine which needs an encompassing structure. Unlike RDF, OWL provides additional information. Indeed, where RDF was content to assign classes and parameters to resources, OWL goes so far as to compare them, in order to help the machine to interpret the request. OWL uses a less restricted vocabulary thanks to comparison tools such as identity, cardinality, equivalence, etc. a bit like in object-oriented programming for example. 

The data alone does not make it possible to be intelligible to the machine which needs an encompassing structure. Unlike RDF, OWL provides additional information. Indeed, where RDF was content to assign classes and parameters to resources, OWL goes so far as to compare them, in order to help the machine to interpret the request. 

OWL uses a less restricted vocabulary thanks to comparison tools such as identity, cardinality, equivalence, etc. a bit like in object-oriented programming for example. OWL uses a less restricted vocabulary thanks to comparison tools such as identity, cardinality, equivalence, etc. a bit like in object-oriented programming for example. OWL uses a less restricted vocabulary thanks to comparison tools such as identity, cardinality, equivalence, etc. a bit like in object-oriented programming for example.

Other languages ​​are used to define websemantics: Sparql, SWRL, Dublin Core, Good Relations for e-commerce, DocBook for IT technical documentation, etc.

SEO Oriented Web Semantics

Google's Knowledge Graph

As you know, Google's Knowledge Graph has enabled the Mountain View giant to display enriched results within its SERPs that prevent the Internet user, on many requests, from looking for information by browsing through sites. Site (s. Indeed, Google brings information directly to it within its engine. In addition to the fact that this device penalizes the traffic of many sites, it allows Internet users to "discover new information quickly and simply" according to Google. You can quickly obtain information on a personality, a monument, a city, a sports team, etc. This data presentation model brings together data from the web to present it clearly to the Internet user.

Rich Snippet

To help search engines understand the content of pages, several rich data languages ​​have emerged:

- RDFa

- Microformats

- Microdata

To go faster, we will only present you the microdata whose format is recommended by Google itself. Microdata are thus used to mark up various content such as opinions from Internet users, people, events, products, cooking recipes or even business establishments. To enrich the content of a web page, the microdata will therefore be combined with the HTML tags by means of additional attributes intended to clarify certain terms of a page and give them meaning.

The differences between microdata, microformats and RDFa

Microdata

Microdata is the most recent and comprehensive format of the three. Recommended by Google for tagging its content, it is above all the format of the future for the semantic web. It uses attributes in HTML tags ("span" or "div"). Each type of information is associated with a particular element (person, company, opinion, products). Its use is often recognized by the presence of "itemprop" attributes. Microdata is a feature provided by the HTML5 language.

Microformats

The microformat is the oldest and simplest of the three. The microformat provides data similar to microdata: it structures the data of a web page. The use of microformat is often recognized by the use of specific "class" attributes in HTML tags. Microformats, unlike microdata, can be used on sites developed with versions lower than HTML5 (xHTML, HTML4 ..).

RDFa

The RDFa (Resource Description Framwork in Attributes) is the most complex format of the three. It works the same as other formats through attributes in HTML tags. It is a strict format often associated with xHTML (strict writing specific to HTML) and recommended by the W3C. However, RDFa is more complicated to implement than the other formats, its vocabulary is free (therefore less efficient during indexing) and there are several versions of the format (1.0 and 1.1).

In conclusion, to mark up and structure the data of your website, it is recommended to use microformats (site in xHTML, HTML4 and lower) and microdata (site in HTML5).