The semantic web & structured data

The amount of data on the web is constantly growing. To solve common challenges with this trend, the semantic web describes a common vision for a web of linked data. The World Wide Web Consortium (W3C) is helping to build a tech stack to support this vision. The ultimate goal is to to enable people and organizations to create data stores, build vocabularies and introduce rules for handling data. As a content strategist (to-be) or someone who works in a content- or web-related discipline, you should know what the semantic web is and how you can use the available standards properly.

Machines & data on the web

Machines need structured data to understand complex issues. From voice assistants to search engines, without standardized and structured data, algorithms won’t be able to understand any context. In fact, structured data is the fuel of the semantic web. This is also one of the most important key takeaways from my research on RDFa and the semantic web from our XML & Content Management course during our second semester at the Content Strategy Master programme of the FH Joanneum Graz.

Why structured data matters

With a rising number of connected devices, data becomes the fuel of our knowledge society. Although we are already producing an incredible amount of data, this won’t necessarily result in knowledge creation. In order to assist us, machines need to understand data, derive information and maybe also create meaning or deduce knowledge. Structured data and the semantic web build the foundations for ubiquitous web.

In the context of search engine optimization (SEO), structured data helps search engines to understand the context of information on a website. Eventually, search engines use these bits of machine-readable information to deliver the best search results for their users. Google and other search engines try to personalize their user experience and answer questions directly on their result pages. That’s also where structured data comes in.

Featured Snippet Example
Google uses structured data to generate featured snippets.

When to use structured data

As a content strategist you may ask yourself when you should implement structured data. The simplest answer would be “always”. In general, as soon as you plan or design content you should think about structuring your content. When conducting a content audit you could also take a look at how structured the content you are auditing already is.

If you are currently working on a (re-)launch of a website for example, the best time to think about structured data would be during content modelling. Usually, while modelling content you also think about the content types required for a digital experience (see the well-known CSA templates).

Content modelling already requires some form of structuring information. If you are planning to present content in different forms and contexts, this is an important step.

Similar to semantic web technologies, content models usually consist of:

  • Types
  • Attributes
  • Relationships

Future-friendly content

As a result, structured data is future-friendly content which can be stored, structured and connected to other data. It allows to reuse the content across different devices and platforms. Once, structured data is implemented properly, it is also highly scalable.

To make your content future-proof, always think of how you can structure your content properly. To finally implement your structured content, I can recommend to take a closer look at schema.org. There you will find various schemas for structured data and instructions on how to use them with different standards such as RDFa.

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