As we have showed in our previous articles, SEO and Semantic Markup have become a key point into increasing your online (and not only) sales and revenue. Now that you understand the importance of Structured Data, let’s take a look at how it works and what it does to make Google understand what exactly your website contains.
When the Search Engines bots crawl your website from the internet, they collect all the info provided within your webpages and add it to the Global Knowledge Graph – a very complex and large database, similar to a spider web, which contains all data crawled from the internet.
If during this process, the bots find no Structured Data present on your website, all they get is a block of text. This text may – or most of the times may not be – representative for what you really want your website to show.
To clearly define the semantic-related content on the pages, the bots need Semantic Markup to help them understand the elements present on the webpage, e.g.: the name of your product, the product image, the price, the reviews, etc. In our language these are easily defined by words such as price, product, reviews etc, but in computer language they mean nothing – this is where vocabularies/ontologies and structured data come along.
What is a Vocabulary, an Ontology, and why do we need that?
“On the Semantic Web, vocabularies define the concepts and relationships (also referred to as “terms”) used to describe and represent an area of concern. Vocabularies are used to classify the terms that can be used in a particular application, characterize possible relationships, and define possible constraints on using those terms…
Vocabularies are the basic building blocks for inference techniques on the Semantic Web.”
An ontology is a conceptual model of an observed reality: namely a repository of interlinked concepts pertaining to a given application domain. It is a classification system necessary in Semantic Markup to organize the knowledge present within the informational elements of your webpage, an essential component to developing the Web of Data.
For a better understanding, here’s an example of a very simple ontology studied in school biology class:
Ontologies used in Structured Data are far more complex and the best examples for such ontologies can be found on schema.org, that contains ontologies supported by all major search engines.
A schema is defined as a representation of a plan or theory in the form of an outline or model.
In June 2011, schema.org was launched as an initiative of Bing, Google, and Yahoo (the operators of the world’s largest search engines) to “create and support” a common set of schemas for structured data markup on web pages – schema.org is an entry-level ontology, based on RDF Classes, which covers most of the types of data that can be found on websites.
Although the already existent schemas (provided by schema.org) cover lots of domains, they’re not enough, if you want to provide a set of very complete, and accurate info about your products, services, entities or events.
In order to solve this issue, the WWW Consortium (W3C) developed the Resource Description Framework (RDF), a language for encoding knowledge on Web pages to make it understandable to bots searching for information. The RDF was later extended through a Web Ontology Language (OWL), customized for creating ontologies.
How is an Ontology created?
Ontologies are built as documents in different formats, all approved by the w3c.org: OWL, RDF, XML or XHTML, but the preferred one is OWL. They can be stored in an online repository (a dedicated server, a CDN – content delivery network, or even a website), and are linked to the HTML elements in the web pages through Structured Data (RDFa,microdata, or LD+JSON), which is recognized and read by all Search Engines.
The construction of an ontology (and its constant evolution, necessary to keep it aligned with reality) is a lengthy and costly process: it requires a lot of knowledge, both on the targeted field/domain, and on how to create the specific Ontology, with all objects, classes, sub-classes, properties, sub-properties, and actions.
While creating the ontology, the developer must have an extensive knowledge on the targeted domain, in order to create usable classes, with well defined relationship between them (subject » action » object).
The creation of a new ontology can make use of all existing vocabularies as well as other existing ontologies, so the Search Engines are able to create the best, and correct relationships between the information on your website and other similar information on the internet.
These relationships represent Linked Data added to the Global Knowledge Graph.
Who makes an Ontology?
In support for w3.org, other authorities in the field of data and knowledge, like Universities, or large Corporations, created complementary languages, which can be used in combination with OWL to more clearly define new Classes, Objects, and Properties in custom ontologies; therefore, when creating a new ontology, a combination of vocabularies can be used.
The most notorious vocabularies supported by W3C are:
- FOAF – for persons, their activities and their relations to other people and objects,
- Dublincore – for expanded cataloging information and improved document indexing,
- Good Relations – for annotating offerings and other aspects of e-commerce on the Web,
- SKOS – for representation of thesauri, classification schemes, taxonomies, subject-heading systems, or any other type of structured controlled vocabulary,
- SIOC – for interconnecting discussion methods such as blogs, forums and mailing lists to each other
- POWDER – for providing means for individuals or organizations to describe a group of resources.
- Productontology – to define Wikipedia Classes as Structured Data
Other than that, for any particular website / email / video etc that needs Structured Data, a new ontology can be created: this should be done in the situation when the information that receives Structured Data belongs to a domain for which there is currently no ontology to fit well enough.
If you find tech talk intimidating and complex, and you ignore these developments, you could be undermining your own competitiveness.
Thankfully, our crack Structured Data Team at Semantic SEO Solutions can help you with using Ontologies and implement Structured Data for your business. With a skilled team of semantic strategists, software gurus, marketing pros and SEO experts, we have everything it takes to help your business leverage the full advantage of Structured Data.
While using structured data is not a requirement,
eBay heavily encourages its sellers to adhere to its terms.
As of Q1 2016, 60% of listed items on the marketplace used its structured data rules, according to eBay’s earnings report. This is up from 37% in Q4 2015.
After a disappointing earnings report in the first quarter, eBay announced its intentions to completely revamp its marketplace experience with Structured Data reflecting new user experiences and product categories to draw in shoppers.
We will help make the changes that can make your pages more visible to the right people, the rich snippets more relevant to the searcher’s intent and the probability of click through far higher than before!
Talk to us now to ensure that your business is getting all the advantages of Google’s advancing search techniques.
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With our 2-step strategy of applying both Semantic Markup and Structured Data to your website, you will experience between 5% to 10% monthly growth in traffic and sales.
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