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 <body> element but can also be used in the <head> element.
<div itemscope itemtype="https://schema.org/Organization"> <span itemprop="name">Schema App</span> Contact Details: <div itemprop="address" itemscope itemtype="https://schema.org/PostalAddress"> Address: <span itemprop="streetAddress">412 Laird Road</span> <span itemprop="postalCode">N1G 3X7</span> <span itemprop="addressLocality">Guelph</span> <span itemprop="addressRegion">Ontario</span> <span itemprop="addressCountry">Canada</span> </div> Tel:<span itemprop="telephone">+1 855-444-8624</span>, E-mail: <span itemprop="email">[email protected]</span>
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 <div> element attributed to the “Organization” type. This <div> 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 <head> and <body> sections of an HTML page.
<div vocab="https://schema.org/" typeof="Organization"> <span property="name">Schema App</span> Contact Details: <div property="address" typeof="PostalAddress"> Address: <span property="streetAddress">412 Laird Road</span> <span property="postalCode">N1G 3X7</span> <span property="addressLocality">Guelph</span> <span property="addressRegion">Ontario</span> <span property="addressCountry">Canada</span> </div> Tel:<span property="telephone">+1 855-444-8624</span>, E-mail: <span property="email">[email protected]</span>
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.
<script type="application/ld+json">
{
"@context": "https://schemaapp.com",
"@type": "Organization",
"name": "Schema App",
"address": {
"@type": "PostalAddress",
"addressLocality": "Guelph",
"addressRegion": "Ontario",
"addressCountry": "Canada",
"postalCode": "N1G 3X7",
"streetAddress": "412 Laird Rd",
},
"email": "[email protected]",
"telephone": "+1 855-444-8624",
}
JSON-LD is also a W3C recommendation and Google’s recommended format for structured data due to its simplicity and readability for both machines and humans. It offers several advantages.
Pros of Using JSON-LD Format for Schema Markup
1. Easiest Format for Machines to Interpret
JSON-LD is designed to be easily parsed and understood by machines, making it an efficient and accessible format for structured data.
2. Easy to Implement and Update
JSON-LD can be read even when dynamically injected into the page’s contents via JavaScript code or embedded widgets. It can be used to describe all types of media on a website—videos, audio, images, and interactive content—not just what exists in HTML documents.
JSON-LD also exists as a single block of code embedded within HTML, so you are not restricted by the structure of the content you are marking up.
3. Ability to Handle Complex Schema Markup
JSON-LD supports the management of complex, nested structured data, making it ideal for advanced use cases. Unlike Microdata, JSON-LD is not restricted by the content and structure of the HTML, offering greater flexibility. For instance, the ratings and reviews for a product can be positioned anywhere on the product page. With JSON-LD, you can easily nest the properties and values in the structured data regardless of where the content is placed in the HTML.
Cons of Using JSON-LD Format for Schema Markup
1. Learning Curve
JSON-LD can be difficult to learn and write manually, especially for those without prior experience with JSON or linked data concepts.
2. Technical Complexity
Implementing JSON-LD may require a higher level of technical expertise compared to Microdata or RDFa.
3. Update to Schema Markup Required If Done Manually
If you author the JSON-LD manually, you’ll need to update the JSON-LD code whenever you make content updates, as it’s separate from the main content.
This is why our customers **** using the Schema App Highlighter, a scalable Schema Markup tool that generates and deploys JSON-LD Schema Markup to thousands of similarly templated pages on your site.
The Schema App Highlighter dynamically updates the Schema Markup on your page when content changes are made. This ensures that all content changes are automatically reflected in your JSON-LD markup in real time. This prevents Schema Drift and reduces the risk of manual coding errors.
What Format Should I Use for Schema Markup?
While Microdata, RDFa, and JSON-LD are all accepted formats for Schema Markup, JSON-LD emerges as our recommended choice. This is due to its flexibility and scalability for complex structured data implementations.
Despite its steeper learning curve and technical expertise requirements, JSON-LD is the format also endorsed by Google and other major search engines for its ease of readability for both machines and humans.
At Schema App, we understand the challenges of implementing JSON-LD at scale. This is why we created tools like the Schema App Highlighter to enable SEO teams to generate and deploy dynamic JSON-LD markup at scale.
With our end-to-end Schema Markup solution, we can help your team deploy robust Schema Markup to your site seamlessly, ensuring optimal search engine understanding and accurate representation of your brand in search results.
Get started with us today and unlock the full potential of JSON-LD Schema Markup for your organization.
Jasmine is the Product Manager at Schema App. Schema App is an end-to-end Schema Markup solution that helps enterprise SEO teams create, deploy and manage Schema Markup to stand out in search.
