What is the Recommended Format for Schema Markup?

Jasmine Drudge-Willson — Fri, 14 Jun 2024 17:50:16 +0000

Schema Markup is a form of structured data that allows website owners to provide additional context and meaning to the content on their pages. It effectively communicates the purpose and relationships of different elements on your site to search engines.

It’s crucial to express Schema Markup in a format accepted by major search engines to take advantage of the Schema.org vocabulary, become eligible for rich results, and accurately describe your website content.

Popular search platforms like Google and Bing recognize three primary formats for Schema Markup:

Microdata
RDFa
JSON-LD

Implementing the appropriate format ensures that your structured data is accurately understood, enhancing your site’s visibility, aligning your content with more relevant search queries, and supporting rich result eligibility.

Understanding the Different Schema Markup Formats

Microdata, RDFa, and JSON-LD have unique features and implementation methods. Each of the three available formats has unique features and implementation methods. Let’s examine the pros and cons of each format to help you understand which format you should utilize for your website.

What is Microdata?

Microdata is an open-community HTML specification used to nest structured data within HTML content. Similar to RDFa, it utilizes HTML tag attributes to name the properties we want to present as structured data.

Microdata is typically implemented within the element but can also be used in the element.


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Pros of Using Microdata Format for Schema Markup

1. Markup is Dynamic

The microdata is added as an attribute for individual HTML elements, so your markup will be updated dynamically if any content changes are made.

For example, consider a

element attributed to the “Organization” type. This

can contain properties like “name” and “address.” If you change the content within any of these elements, the markup will automatically update to reflect the latest content.

2. Easy to Implement

Microdata can be easily inserted into HTML, making it more straightforward for those without coding skills to implement the Schema Markup. Microdata is generally easier to understand and maintain than other formats like RDFa.

Cons of Using Microdata Format for Schema Markup

1. Less Suitable for Advanced Schema Markup

While microdata works well for basic Schema Markup, it can become more complicated when dealing with advanced Schema Markup involving many nested entities.

Consider the Product schema type, which requires HTML elements for various attributes like price, ratings, reviews, and return policies to be nested. If your product page only had an image and a price, you can easily use microdata to markup your page.

However, the complexity increases with additional elements such as FAQs located lower on the page, branding information in a separate section, and ratings and reviews in a separate tab. These extra layers make the implementation messy and difficult to manage.

2. Messy Implementation

Since microdata has to be applied to each individual element on the webpage, the markup can become cluttered and messy, especially for larger websites, where your code can become “bloated” very quickly.

3. Unsuitable for Larger Websites

Due to the potential for clutter and the limitations of complex schemas, microdata is generally better suited for smaller websites with simpler structured data requirements.

What is RDFa?

RDFa (Resource Description Framework in Attributes) is an HTML5 extension that supports linked data. It does this by introducing HTML tag attributes that correspond to the user-visible content you want to describe for search engines.

RDFa is considered a W3C (World Wide Web Consortium) recommendation, meaning that it is a web standard. It can be used to chain structured data vocabularies together, which is especially useful if you want to add structured data that extends beyond the limits of Schema.org.

You can breathe a sigh of relief, however, as RDFa isn’t much different from Microdata. Similar to microdata, RDFa tags are incorporated with your webpage’s preexisting HTML code and are commonly used in both the and sections of an HTML page.


  Schema App
Contact Details:
  
    Address:
     412 Laird Road
     N1G 3X7
     Guelph
     Ontario
     Canada

  Tel:+1 855-444-8624,
  E-mail: support@schemaapp.com

Pros of Using RDFa Format for Schema Markup

1. Flexibility

RDFa allows you to combine multiple vocabularies, making it more flexible than Microdata or JSON-LD for complex structured data requirements.

2. Widely Adopted Standard

Since RDFa is a standardized format recommended by the W3C, it ensures broad compatibility across various platforms, browsers, and search engines. This means that structured data marked up with RDFa will be more consistently interpreted and utilized by different web services.

3. Integrates with Existing HTML

Like Microdata, RDFa seamlessly integrates with your existing HTML code, making implementation easier.

Cons of Using RDFa Format for Schema Markup

1. Steep Learning Curve

RDFa has a steeper learning curve compared to Microdata or JSON-LD, as it requires a deeper understanding of linked data principles and vocabularies.

2. Messy implementation

Also similar to microdata, RDFa markup can become verbose and cluttered, especially for complex structured data implementations.

3. Limited Browser Support

While search engines support RDFa, some older browsers may have limited or no support for rendering RDFa markup.

Overall, RDFa offers a flexible and standards-compliant approach to structured data markup, but it may be more suitable for advanced use cases or when combining multiple vocabularies is necessary.

What is JSON-LD?

JSON-LD stands for JavaScript Object Notation for Linked Data. It is a method of encoding structured data using the JSON format, which is a lightweight data-interchange format that is easy for machines to parse and generate.

The key difference between RDFa, Microdata, and JSON-LD is their implementation method on a page. Both RDFa and Microdata are added as properties within the content itself. Conversely, JSON-LD is added independently, typically in the header or footer of the HTML.

This resolves the issue of messy and cluttered implementation associated with both RDFa and microdata.

.

JSON-LD SchemaFilter.remove([],'json-ld'); or SchemaFilter.removeJSONLD();
Microdata SchemaFilter.remove(); or SchemaFilter.removeMicroData();
RDFa SchemaFilter.remove([],'rdfa'); or SchemaFilter.removeRDFa();

Specifying specific Types
Specifying particular schema classes is done through passing an array to the remove function. If all classes are to be removed then the array may be left empty ([]), or passed in as null.

// This will remove all Event and Organization types on Microdata
<script>SchemaFilter.remove(['Event', 'Organization']);</script>

// This will remove LocalBusiness, Organization, and WebSite classes in a JSON-LD format. 
<script>SchemaFilter.remove(['LocalBusiness', 'Organization', 'WebSite'], 'json-ld');</script>

// Remove all classes of rdfa (notice the empty array).
<script>SchemaFilter.remove([],'rdfa');</script>

// Remove all Organizations of RDFa
<script>SchemaFilter.remove(['Organization'], 'rdfa');</script>

// Remove all classes of JSON-LD (notice we can also use null for the array).
<script>SchemaFilter.remove(null,'json-ld');</script>


Running the script on your page
Once the script is imported you may the run script in another block of JavaScript. The script should be run when the document is ready or after another event that injects Schema Markup into the page. If the markup is embedded in the source you may run when the document is loaded as shown below.

<script>SchemaFilter.remove(null, 'json-ld');</script>

If you want to alter the event in which the code is loaded you can specify the string event value into the onLoad property of the SchemaFilter.

<script>
SchemaFilter.onLoad = 'SomeEventHere'; // the default value
SchemaFilter.remove();
</script>

At Schema App, we look at schema markup as an iterative process. Through enhanced analytics and content recommendations, we help our customers maximize their results through structured data. If you need help getting started, get in touch today!
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