Posted by alexis-sanders
Schema.org is cryptic. Or at least that’s what I had always thought. To me, it was a confusing source of information: missing the examples I needed, not explaining which item properties search engines require, and overall making the process of implementing structured data a daunting task. However, once I got past Schema.org’s intimidating shell, I found an incredibly useful and empowering tool. Once you know how to leverage it, Schema.org is an indispensable tool within your SEO toolbox.
The first part of any journey is finding the map. In terms of structured data, there are a few different guiding resources:
Tip: If any of the item types listed in the feature guides are relevant to your site, ensure that you’re annotating these elements.
Tip: Click “Core plus all extensions” to see extended Schema.org’s libraries and what’s in the pipeline.
As an example, I’m going to walk through the Aquarium item type Schema.org markup. For illustrative purposes, I’m going to stick with JSON-LD moving forward; however, if there are any microdata questions, please reach out in the comments.
When you first enter a Schema.org item type’s page, notice that every page has the same layout, starting with the item type name, the canonical reference URL (currently the HTTP version*), where the markup lives within the Schema.org hierarchy, and that item type’s usage on the web.
*Leveraging the HTTPS version of a Schema.org markup is acceptable
An item type is a piece of Schema.org’s vocabulary of data used to annotate and structure elements on a web page. You can think about it as what you’re marking up.
At the highest level of most Schema.org item types is Thing (alternatively, we’d be looking at DataType). This intuitively makes sense because almost everything is, at its highest level of abstraction, a Thing. The item type Thing has multiple children, all of which assume Thing’s properties in a cascading in a hierarchical fashion (i.e., a Product is a Thing, both can have names, descriptions, and images).
Explore Schema.org’s item types here with the various visualizations:
Item types are going to be the first attribute in your markup and will look a little like this (remember this for a little later):
Tip: Every Schema.org item type can be found by typing its name after Schema.org, i.e. http://schema.org/Aquarium (note that case is important).
Below, this is where things start to get fun — the properties, expected type, and description of each property.
Item properties are attributes, which describe item types (i.e., it’s a property of the item). All item properties are inherited from the parent item type. The value of the property can be a word, URL, or number.
For every item type, there is a column the defines the expected item type of each item property. This is a signal which tells us whether or not nesting will be involved. If the expected property is a data type (i.e., text, number, etc.) you will not have to do anything; otherwise get ready for some good, old-fashioned nesting.
One of the things you may have noticed: under “Property” it says “Properties from CivicStructure.” We know that an Aquarium is a child of CivicStructure, as it is listed above. If we scan the page, we see the following “Properties from…”:
This looks strikingly like the hierarchy listed above and it is (just vertical… and backward). Only one thing is missing – where are the “Properties from Aquarium”?
The answer is actually quite simple — Aquarium has no item properties of its own. Therefore, CivilStructures (being the next most specific item type with properties) is listed first.
Structuring this information with more specific properties at the top makes a ton of sense intuitively. When marking up information, we are typically interested in the most specific item properties, ones that are closest conceptually to the thing we’re marking up. These properties are generally the most relevant.
A huge thanks to Max Prin (@maxxeight), Adam Audette (@audette), and the @MerkleCRM team for reviewing this article. Plus, shout outs to Max (again), Steve Valenza (#TwitterlessSteve), and Eric Hammond (@elhammond) for their work, ideas, and thought leadership that went into the Schema Generator Tool!
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