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Semantic SEO is the practice of translating unstructured data into structured data by reducing your reliance on Google to get things right by removing ambiguity between similar entities.
Semantic SEO should not be viewed as a different form of search engine optimization. Instead, using descriptive and context-rich structured data that reflects on-page content will help search engines better understand your content.
Anything and everything can be an entity. They can be real, visible, imaginary, a work of fiction, or otherwise.
Entities are things humans create and understand. Machines, however, have difficultly understanding the nuances between similar things and this is why schema markup exists to help machines (such as search engines) understand what entities exist on a page and how they relate to each other, to the wider website, and to the search intent of its users.
Schema markup is a way to convert unstructured data into structured data and structured data is a way that machines can process and understand all the complicated things, meanings and nuances humans have created.
Schema markup is done through one or more syntax where a syntax is simply a coding language.
For example, JSON-LD is a syntax just as Microdata and RDFa are a syntaxes.
Therefore, the syntax is the language used to convert unstructured data into structured data.
Schema markup refers to any method that turns unstructured data into structured data.
One way of doing turning unstructured data into structured data is with JSON-LD which is a syntax and a form of schema markup.
There are 803 types of entities as defined by schema.org.
They can be used to describe specific entities or things.
Common schema Types you’ll probably know include:
- Person
- Organization
- WebPage
- Event
- ImageObject
- VideoObject
Schema.org vocabulary is how you describe what an entity is.
Schema.org vocabulary refers to the attributes that can be used to describe an entity. The vocabulary that can be used is specific to each syntax.
That is, JSON-LD has its own set of vocabulary (e.g., Schema.org item properties) just as Microdata has its own set of unique vocabulary to describe entities.
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