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Schema.org is a joint effort between Google, Bing, Yahoo, and Yandex to help people create and promote schemas for structured data on the internet.
From an implementation perspective, the Schema website provides several schemas on a range of topics and examples on how to use those on your web pages. So I thought I’d write about the idea of what a schema is in a little more depth, and how schemas are related to entities.
Related Content:
Schemas and Entities
In 2012, when Google introduced the knowledge graph, they told us that they were going to start focusing more upon things, not strings in how they indexed content on the Web. They started detecting entities in queries that people performed and showing off knowledge panels related to those entities within search results. But just how does “Schema” fit into this concept of entities? One way to think of schema is as a way of describing and organizing information about entities in a machine-readable way. This definition of what a database schema fits well into that perception of how a schema works:
A database schema (/ˈski.mə/ skee-mə) of a database system is its structure described in a formal language supported by the database management system (DBMS). The term “schema” refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases). The formal definition of a database schema is a set of formulas (sentences) called integrity constraints imposed on a database.[citation needed] These integrity constraints ensure compatibility between parts of the schema. All constraints are expressible in the same language. A database can be considered a structure in the realization of the database language.[1] The states of a created conceptual schema are transformed into an explicit mapping, the database schema. This describes how real-world entities are modeled in the database.
The relationship between schema and entities is that schema tells us how real-world entities are modeled and what the different parts and pieces of entities are.
Real World Entities
The Schema.org website tells us about schema vocabulary “cover[s] entities, relationships between entities and actions.” This reminds me of when Google introduced its knowledge graph as being about “things, not strings.” With the coming of the knowledge graph to Google, the focus of search shifted from matching keyword phrases in queries and documents on the web, to providing search results that uncovered entities at places on the Web. By using markup with Schema vocabulary within it, on your web pages, you can help search engines recognize when they’ve found pages that contain information about specific entities.
The purpose behind schema.org is to enable you to collaborate on creating schemas that define and describe entities, such as Businesses. Let’s look at an example business entity, and how a schema applies to that entity.
A Local Business Entity Example
One type of Entity might be a business such as a restaurant. The Schema that describes that entity and the parts that make it up can be found on this page from Schema.org. If we look there, we can see things such as:
- Currenciesaccepted
- Openinghours
- Pricerange
- Address
- Menu
- Acceptsreservations
- Logo
- Photo
- Telephone
These data points or properties of an entity are things that customers would want to know about a restaurant and would expect to see on a website about a restaurant. They are the kinds of things that help to describe an entity that is a Restaurant. Having entity information on your site (with or without claiming the business on Google My Business) could lead to a knowledge panel appearing when your company name is searched, such as:
The Schema.org site, on its Home page, tells us this about its purpose:
Schema.org is a collaborative, community activity with a mission to create, maintain, and promote schemas for structured data on the Internet, on web pages, in email messages, and beyond.
If you are creating content on the Web about a business, and want that business to rank well in local search, it is in your best interest to consider using schema vocabulary in markup on your pages to create content about that business. The schema for that business type includes properties that subject matter experts creating the schema have determined to be the kind of data that people might be interested in for that type of business (see the list of properties above for a restaurant.)
Schema Extensions
There is a section of the Schema.org site that provides information on how schemas might be extended to make them richer and more detailed about certain types of entities:
Schema.org provides a core, basic vocabulary for describing the kind of entities the most common web applications need. There is often a need for more specialized and/or deeper vocabularies, that build upon the core. The extension mechanisms facilitate the creation of such additional vocabularies.
With most extensions, we expect that some small frequently used set of terms will be in core schema.org, with a long tail of more specialized terms in the extension.
Some of the extensions for Schema that are taking place at present include:
- Bibliographic Schema – a range of schemas that involve written entities such as the following types: Atlas, Audiobook, Chapter, Collection, ComicCoverArt, ComicIssue, ComicSeries, ComicStory, CoverArt, Newspaper, Thesis
- Automotive Schema – a range of schemas that involve the automotive industry and include entities of the following types: BusOrCoach, Motorcycle, MotorizedBicycle. It also adds to the type “Car” as well
- A Product Data Schema Extension from GS1 provides a richer set of Schema involving different product types
If You are in San Diego…
I am a co-administrator of the Lotico San Diego Semantic Web Meetup Group, along with Barbara Starr, and on April 19th and 20th we are joining up with the EDW (Enterprise Data World) conference in San Diego to offer a complimentary session on Schema.org and FIBO (Financial Industry Business Ontology). If you can join us, please do. It focuses upon how schema.org is being extended to include the financial industry.
The offer we received from the person putting on the conference, Tony Shaw, included attendance at the reception and exhibits for the conference or a $200.00 discount off of the conference as a whole. In addition to joining the Meetup group and sending in an RSVP, you should also register with the conference using the special code mentioned on the meetup group event page (this is required for you to be able to get in). We will be meeting at one of the restaurants at the Sheraton San Diego after the session for discussion and networking.
So, these extensions to Schema.org will be helpful to the search engines involved in indexing entities involving different book types, automotive types, product types, and financial industry types. We are hoping that having the chance to see more closely how the extension process works with financial businesses will provide some insight into how the schema.org extension process works overall.
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