Semantic SEO as a developing consequence
The good point in ageing is perspective. That’s why I no longer worry about fitting my work into today’s “Everything AI-powered” narrative.
From the beginning, I’ve followed one guiding principle: stick to long-term foundational standards. That mindset led me to early readings through W3C working groups and technologies like RDF, FOAF, Dublin Core, and the Semantic Web—drawn by Tim Berners-Lee’s vision of a web built not just on links, but on meaning.
Today, I see Semantic SEO not as a trend, but as the natural continuation of that vision.
It’s not about chasing rich snippets or JSON-LD—it’s about building structured, meaningful content that serves both humans and machines.
RAG, Query Fan-Out, tokens, MUVERA… all chasing the same thing: semantic depth.
And while the tech evolves, the principles remain: structure, clarity, and meaning.
That’s why and how I developed my way, crystallizing in the shape of the DSH (Descriptor Semántico Homogéneo)—not a new format or vocabulary, but a methodological framework. DSH is a flexible work process that adapts to any client case, regardless of their tech stack or content maturity.
It’s the backbone of my Growth By Method approach at SOLID SEO. You see, a lot of I-my-me. But the DSH truly works fine. You may scratch the paint, but the frame is SOLID.
In this post, I’ll walk you through how Semantic SEO and the Semantic Web converge—and how my DSH approach to Semantic SEO helps bridge that gap with clarity, consistency, and purpose.
Semantic SEO and Metadata: From Notepad to LLMs
I’ve been embedding metadata in my web pages since the early days of HTMLing in legacy Notepad, relying on Dublin Core to tag every resource I published.
During the SEO for Flash era, fragments of my metatag toolkit would pop up across the web.
Proof that some marketers sensed its power, even if they couldn’t name it, as I hardly could explain by those days.
Many laughed at those of us championing Dublin Core, calling it useless.
They missed the point: resource discovery and classification has always been the bedrock of the Semantic Web.
Ultimate goal: To create and exploit Knowledge. Whose Knowledge? Common.
The Whole Knowledge, queryable as a live distributed Knowledge Base. Wait… Isn’t this RDF ??
DC was our first step toward a universal “labeling” system.
In the years that followed, FOAF, IPTC, SKOS, LOD, GEO, GoodRelations and countless vocabularies followed—not to complicate things, but to bridge the gap between finding something and truly understanding it.
Semantic Web Standards
| Year | Standard | Role in the Semantic Web |
|---|---|---|
| 1995 | Dublin Core | First universal metadata descriptors |
| 2000 | FOAF | Describing people and social networks |
| 2004 | SKOS | Thesauri & controlled vocabularies |
| 2007 | Linked Open Data (LOD) | Web-wide graph of interlinked data |
| 2008 | W3C Basic Geo (GEO) & IPTC | Geolocation + photo metadata standards |
| 200x | GoodRelations | E-commerce ontology (later in Schema) |
| 2011 | Schema.org | Unified vocab for rich snippets & graphs |
| 2024 | DSH (Descriptor Semántico…) | Your next-gen Semantic SEO framework |
Schema.org: The Game Changer
In June 2011, Google, Microsoft, Yahoo! and Yandex launched Schema.org, marking a seismic shift. For the first time, a single, unified vocabulary structured web content at scale.
Rich snippets, knowledge graphs and a practical Semantic Web leapt from whiteboards into production.
Schema.org didn’t just help search engines—it laid the semantic rails that modern LLMs now ride to improve data quality, disambiguation, and contextual understanding.
Yet it also fueled controversial shifts like Google AIO, prompting renewed cries of “SEO is dead” and spawning semantic confusion through acronyms like GEO—a geolocation-focused vocabulary that could be mistakenly tout as SEO’s successor.
Who said only Schema.org?
Of course Google repeated over and over about their preference for JSON-LD (format) and Schema.org (vocabulary), why involving themselves into such crusade?
Just preparing the shape of things to come!
- JSON is a lightweight and widely supported format that’s easy to process and ideal for web applications.
While not the most bandwidth-efficient, it strikes a balance between readability and performance. - Schema.org provides a semantic foundation for meaningful content, and when combined with JSON, it forms JSON-LD, a powerful format for embedding structured data in web pages.
Regarding the next comparison, it is obvious why Google advocates for this format/vocabulary pair: it is reliable and cost-effective.
[TL;DR this sorting could be changed by specific conditions, please be flex]
Unified Data Formats with Processing & Syntax Complexity
| Processing | Syntax Complexity | Format | Category | Description |
|---|---|---|---|---|
| Lightest | Simplest | CSV | General | Tabular format, great for spreadsheets and flat data |
| Lightest | Simplest | N-Triples | Semantic Web | Simple, line-based RDF serialization |
| Light | Simple | JSON | General | Lightweight, widely used in web APIs and apps |
| Light | Moderate | JSON-LD | Semantic Web | JSON with linked data capabilities for semantic markup |
| Moderate | Simple | YAML | General | Readable config format, popular in DevOps |
| Moderate | Moderate | Turtle | Semantic Web | Human-readable RDF syntax |
| Moderate | Moderate | N-Quads | Semantic Web | RDF serialization with context (graph name) |
| Heavy | Complex | XML | General | Hierarchical markup, common in legacy systems |
| Heavy | Complex | RDF/XML | Semantic Web | XML-based RDF serialization, legacy-friendly |
| Heavy | Complex | RDF | Semantic Web | Core model for representing semantic triples |
| Heaviest | Opaque | Parquet | General | Columnar format for big data and analytics |
Syntax Complexity Scale
- Simplest: Minimal structure, easy to write by hand (e.g., CSV, N-Triples)
- Simple: Clear structure, readable and writable with ease (e.g., JSON, YAML)
- Moderate: Requires some understanding of semantics or nesting (e.g., Turtle, JSON-LD)
- Complex: Verbose, nested, and often requires tooling (e.g., XML, RDF/XML)
- Opaque: Not human-readable (without tools); designed for machines (e.g., Parquet)
Under Google Search dominance, most marketers chant “JSON-LD” and many developers cheer “I love Schema!” but few remember Schema (specialised) ancestors: GoodRelations, Dublin Core Initiative, and other foundational ontologies.
About format and complexity for delivering meaningful content, JSON is just a serialization format easy to read and Human-friendly; easier to learn, easier to write.
Very embeadable as a webpage component: It’s a pragmatic choice for most web implementations.
But as a Semantic SEO practicioner, I would rather write for machines (LLMs) after my human-readable web content is set, since these LLMs will bring my content and customer’s content before consumer eyes.
RDF comes in Turtle, RDF/XML and more. RDFS has you covered with multi-vocabulary work.
It’s the semantics behind the syntax that powers true discovery—and ultimately, intelligent systems behind next-gen SEO.
While not for the average SEO and marketeer, ask yourself why most (not to say all) Knowledge Graphs offer same content in multiple formats, one of them being RDF and/or RDF/XML.
Like potatoes for all, served in different styles: semantic data comes in varied formats—each suited to its audience.
A Framework, Not a Format
Vocabularies provide context, but Semantic SEO still demands a serializable work process
Introducing DSH: Descriptor Semántico Homogéneo
If Semantic Web advocates were ahead of their time, we’re only now catching up.
Data is only as powerful as the meaning we give it.
As you architect your next AI or content strategy, ask yourself: are you merely feeding tokens into a model, or are you serving up rich semantics that unlock deeper understanding?
Are you doing old fashioned string based SEO, (only) chasing keywords, or genuine, meaningful Semantic SEO?
For this reason, I’ve launched DSH (Descriptor Semántico Homogéneo or Descriptor Semàntic Homogeni or Homogeneous Semantic Descriptor)—my own foundation for true Semantic SEO.
DSH does more than combining vocabularies under one roof, it magically doubles as SEO for AI, GEO, LLMs and whatever next-gen buzzword emerges.
Plain SEO, up to date with today’s technology and infrastructure.
Another distinguishable feature is my decision on Spanish/Catalan branding. I did my homeworks, I know DSH or HSD can read like a ton of funny things out of my context. But I just care for my deliverables.
Ready to give your content the meaning it deserves?
Why not just use Schema.org alone?
Schema.org offers a broad, one-size-fits-all vocabulary.
It is fine to use it alone if you don’t know, or don’t care, about the difference between delivering Linked-Data and trying to be awarded Google’s Rich Snippets.
By layering in DSH, you gain domain-specific descriptors and cross-ontology harmony, unlocking richer, more precise contents ready for SEO competing.
Isn’t JSON-LD enough for structured data?
JSON-LD is the format of choice for Google Search. RDFa, or RDF/XML work just as well. The real deliverable lies in the semantic layer.
Your SEO success lives in your vocabulary, not your syntax. You can offer the SAME entity in DIFFERENT vocabularies and formats, up to your buyer-persona.
Why an XML file instead of your initial RDF descriptors?
This was decided from a human friendly perspective. Same as XML Sitemaps can be browsed nicely using XSLT (stylesheet transformations), whilst being easily ingested by machines. I personally prefer RDF extension, but regarding browser support for XSLT I went for XML. After all it is RDF/XML MIME, you just need to change the file extension.
Why Homogeneous Semantic Descriptor when you defend extensibility, thus difference?
DSH is the Semantic cog in my Semantic SEO deployment. It is always used the same way, in the same place and for all cases.
This sounds like coffee for all, but again, ontologies, client industry know-how and experience bring the precise flavour at SOLID SEO Management Services.
What SEO benefits can I expect?
- Expect higher click-through rates from rich snippets, improved crawl efficiency, and stronger contextual relevance signals, all contributing to better rankings, mentions and LLM listings over time.
- Certainty and precision make content a trustworthy source. This will play a significant role in an increasing RAG and Query Fan-Out activity on the field.
- Last, but not least, a wisely combined SEO strategy will deliver Authority at the long term.
Is this Semantic SEO another buzzword?
Not at all. The concept is as old as the WWW, despite the twist towards Search/Retrieval purposes came by the times of the browser wars and the “This site is best viewed 800×600” footers.
And with “browser wars” I mean dial-up times, Explorer vs Netscape; Because today there is another browser war in progress, last news is Perplexity offer for buying Google’s Chrome browser.
However, if you happen to hire an SEO consultant talking Semantic SEO like “using synonims and variations because the search engines will understand them”, you better look further on for help: probably an SEO pretender.
© Ricard Menor SOLID SEO Management Services
© Spanish SEO Expert - SOLID SEO Management Services