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Meta Data – Understanding Semantic Web and Structured Data

Meta Data – Understanding Semantic Web and Structured Data

PURPOSE: Introduce the new Meta data used in semantic SEO, along with a glossary of terms to provide a basic understanding of the terminology, language and acronyms used to implement structured data markup.

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Semantic SEO Solutions


The Semantic web and semantic technology have been around for many decades for the purpose of creating a system to identify relationships between people, places and things.

To illustrate, let’s see how a machine understands a specifically named person such as “Barack Obama”.

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A machine such as a search engine robot (bot) has a very difficult time verifying a person is actually THE person being displayed in web content when using HTML on a web page. With structured data markup on the semantic web, we now have a process and language available to provide search robot machines with precise and accurate methods for identifying supporting data to verify the identity of this person.

Verified data is more trusted and useful for machines (bots) than a backlink to a webpage explaining who that person is.

Therefore, when we connect various relationships and concepts to identify a specific person, a bot can more easily validate and subsequently trust that a specifically named person is who we say it is on the web page.

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For instance: on a webpage referring to Barack Obama, the relationships to gender, date of birth (DOB), height, address, etc., greatly improve the bot’s ability to verify this specific person thusly: male, DOB August 4th 1961, height 6’1”, address The White House.

Of course, the same methods can be used for identifying your brand, products, offers, services and many other aspects of the business.

Sir Tim Berners-Lee, the inventor of the hyperlink, envisions a noteworthy transition we should all pay close attention to when he stated that we are currently moving “from a Web of documents to a Web of data.”

The semantic web includes concepts of reference to word relations in the form of structured (linked) data.

Semantic technology provides the method for connecting related topics, themes, ideas, text, video, audio and all digital assets (data) to machines on the web. Search engines are machines desperately looking for what is known as structured data markup to order the web into a coherent flow of accurate information.

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Search engine robots (bots) such as Google, Bing, Yandex and others are consuming, converting and displaying structured data into rich display formats, positioning the top 3% of participating websites for the highest visibility within their search result pages (SERPs).


Understanding The Language

To participate and provide properly coded structured data markup, we must first grasp a clear understanding of the terms used in the semantic web community.
The objective of this article is to provide you with examples, definitions and resources to better understand the words used by the semantic web community.

For instance, let’s examine the word “vocabulary” as an example.

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The term “vocabulary” as commonly used can be defined as “the body of words used in a particular language,” e.g., the English vocabulary, French vocabulary, Italian vocabulary, etc. However, the term “vocabulary” within the semantic community means something entirely different.

A Vocabulary as defined by W3C is “A collection of ‘terms’ for a particular purpose. Vocabularies can range from simple vocabularies such as the widely used RDF, Schema, FOAF and Dublin Core Metadata Element Set to complex vocabularies with thousands of terms such as those used in healthcare to describe symptoms, diseases and treatments. Vocabularies play a very important role in Linked Data, specifically to help with data integration. The use of this term overlaps with Web Ontology (a formal way to describe taxonomies and classification networks, defining the structure of knowledge for various domains with nouns representing classes of objects and verbs representing relations between the objects).

It is safe to say, search engines as you’ve known them in the past, have been rapidly adjusting and changing behind the scenes over the past six years. Subsequently, search engine optimization (SEO) has morphed into what I’m going to refer to here as “Semantic SEO,” the addition of structured data markup to web page content.

What Is Structured Data Markup?

Structured data markup is basically a new meta data, but a much more sophisticated meta data which is nothing like Title elements or description Meta Tags. Structured Data can be expressed as strategic deep linking in SEO terms, and it comes with a very steep academic learning curve to it.

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We’re not talking about “linking” as in anchor text or link building; no…this is strategic deep linking of very specific URIs within various relevant vocabularies and linked open data.

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You really have to know what you’re doing or you will seriously destroy the credibility of a website; there’s no room for error.

Properly coded structured data markup achieves trust and authority with search engines, and it can be deployed using JSON-LD.

What Is JSON-LD?

Per W3C, JSON-LD (JavaScript Object Notation for Linking Data).is a language-independent data format for representing Linked Data based on JavaScript Object Notification. JSON-LD is capable of serializing any RDF graph or dataset, and most but not all JSON-LD documents can be directly transformed to RDF. JSON-LD Syntax is easy for humans to read and write and is also easy for machines to parse and generate. JSON-LD is an appropriate Linked Data interchange language for JavaScript environments, Web Service and NoSQL databases.”
JSON-LD and structured data are 100% search engine compliant; in fact, search engines are desperately looking for high quality structured data being delivered with JSON-LD because it provides excellent semantic parity.

What Is Semantic Parity?

My definition: semantic parity maps and matches relevant, indexable website content to the crawlable semantic web community. of data found in Linked Open Data (LOD) and Linked Open Vocabularies (LOV), Freebase and Wikidata, also known as the semantic web community.

What Is The Semantic Web?

The semantic web is machine-readable data in RDF and presents an ability to query that information in standard ways (e.g., via SPARQL).

Are you beginning to see a pattern here? A clear understanding of the terms used within the semantic web community is essential. The following resources provide a convenient glossary of terms and definitions used in this article. For a more comprehensive list see the W3C Linked Data Glossary. Datahub also provides a good definition of Linked Open Vocabularies (LOV).

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Freebase is a community curated database of 3 billion facts and 50 million topics. Freebase allows you to uniquely identify identities anywhere on the web.

Wikidata is a free linked database that can be read and edited by both humans and machines.

Pool Party Linked Data Service provides a “Visual” view and drills-down into any area of interest.

RDF (Resource Description Framework) is a family of World Wide Web Consortium (W3C) specifications originally designed as a metadata data model.

Schema.org is an initiative launched in 2011 by Google, Bing, Yahoo, and subsequently Yandex, to “create and support a common set of schemas for structured data markup on web pages.”

FOAF (Friend of a friend) is a machine-readable ontology describing persons, their activities and their relations to other people and objects.

Dublin Core Metadata Element Set is a vocabulary of fifteen properties for use in resource description.

Linked Data is a pattern for hyperlinking machine-readable data sets to each other using Semantic Web techniques

Linked Open Data enables distributed SPARQL queries of the data sets and a “browsing” or “discovery” approach to finding information as compared to a search strategy

Ontology is a formal way to describe taxonomies and classification networks to define the structure of knowledge for various domains in which nouns representing classes of objects and verbs representing relations between the objects.

Semantic SEO refers to search results that don’t contain the user’s exact search term instead using artificial intelligence to understand user intent and query meaning and not parsing through keywords like a dictionary. Semantic SEO requires the addition of structured data markup to website and web page content that was previously optimized using SEO best practices.

Structured Data (as Google stated in 2012) is becoming an increasingly important part of the web ecosystem used to allow websites to highlight specific types of content in search results, marking up content using industry-standard formats and schemas.

Structured Data Markup is a standard way to annotate your content so machines (search engine bots) can understand it.

The Semantic Web is an extension of the web through standards by the World Wide Web Consortium (W3C) which promote common data formats and exchange protocols on the web, fundamentally the Resource Description Framework (RDF). The Semantic Web is an evolution or part of the World Wide Web that consists of machine-readable data in RDF and an ability to query that information in standard ways (e.g., via SPARQL)

Summary & What’s Next

This was the first article in a 10-article series to help developers, business owners and SEO practitioners understand the Semantic Web and structured markup — basically an introduction to the Semantic Web and structured data markup terms. The next article will provide a detailed explanation of the first step necessary before deploying effective structured data markup – checking your site health to ensure SEO compliance.

This entire series of 10 articles can help SEO practitioners better understand how and why the new meta data is so important to generating legitimate organic search engine traffic over the next 5-10 years.

We are at a convergence of technologies, transforming a new order and flow of data on the web. Besides detailed implementation tactics, future articles will include how to mark up for brand messaging, knowledge graph alignment, the appropriate tools required, and many more topics that are critical path to success on the web and with search engines.

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