Posted by Mike_Arnesen
Structured data has never been more important than it is today. We'll talk about why briefly below, but that's not what this post is about. This post is about giving you a new tool to add to your semantic SEO tool belt. My goal is to empower you implement semantic markup and structured data with greater ease and enable you to architect a more robust and complete web of linked data on your website (and beyond).
Structured data is more important than ever
I don't think that's an exaggeration. When Schema.org launched in June of 2011, search marketers gained access to an incredibly powerful tool: an extensive vocabulary, agreed upon by the world's leading search engines, with which we could give our data meaningful structure.
However, there were two things holding us back from realizing the dream of a truly semantic web.
- The difficulty of actually implementing said markup on our sites.
- The markup's limited utility in actually achieving some kind of tangible SEO return on our investment.
I believe JSON-LD's big day at Google was a watershed moment in making implementation less daunting and, hopefully in the coming years, ubiquitous across the web (well, at least more so). Now that we have rapidly growing JSON-LD support from Google and powerful semantic attributes like Itemref and Itemid, the ability to give structure to the unstructured is within everyone's reach.
The tangible SEO return has also never been greater! Beyond tried and true rich snippets for star ratings, pricing, availability, and breadcrumbs in search, we're seeing richer and richer results, previews, and cards show up in Google. These are powered by, you guessed it, structured data and, more often than not, the recommended format is in JSON-LD. In light of Google's recent launch of Rich Cards (starting with Recipes and Movies, but sure to be expanding to other Schema types soon), Top Stories with AMP, and Knowledge Panel Critic Reviews (which is currently by request and with Google approval only), we need flexible models for structuring bigger and bigger data sets.
Through using itemref and itemid, you'll be able to mark up your data that much easier to keep up with the rapid evolution of semantic SEO. You'll also be positioned to fully capitalize on new search features, regardless of whether or not they require JSON-LD or in-line microdata (remember that while Google is now all about JSON-LD, they're not the only game in town).
That's enough of an intro; let's talk itemref and itemid.
What are itemref & itemid?
At their core, itemref and itemid are just HTML attributes. They're actually very similar to other attributes that you're already familiar with if you've worked with semantic markup before.
The 3 most common attributes in semantic SEO
Let's quickly recap what itemscope, itemtype, and itemprop do. Feel free to skip to the next section, though it never hurts to brush up.
Itemscope: an attribute without a value that defines the scope of an semantic entity within your data. Everything within that itemscope is considered a part of that entity and everything outside of it is separate.
Itemtype: an attribute that goes hand-in-hand with itemscope and that does have a value. The value of the itemtype attribute is going to specify the type of entity you're marking up and is most commonly a link to a URL on schema.org.
Itemprop: an attribute used to declare specific attributes of your entity (e.g. itemprop= "name", itemprop="description", etc.)
The 2 hidden attributes in semantic SEO
It's fairly easy to guess what itemref and itemid are just by looking at their names, but it's a little harder to figure out how to use them (don't worry, we'll get to that part later).
Itemref: an attribute that allows you to reference other data points outside of the itemscope.
Itemid: an attribute that allows you to give an entity a unique identifier. This entity can then be used to flesh out another entity as an embedded entity.
itemscope itemtype="http://schema.org/Organization" >