Ontology vs. Metadata vs. Knowledge Graph: What’s the Difference?

Tech buzzwords like metadata, ontology, and knowledge graph are everywhere — especially in search, AI, and content strategy. But what do they actually mean? And how do they relate to each other?

In this post, we’ll break each concept down in simple terms, give you real-world examples (yes, including tabbouleh), and help you understand how these ideas shape the web, content, and the tools we all use.

🔖 Metadata: Descriptions and Labels

Metadata is data about data. It doesn’t explain meaning — it describes content. It’s what helps us search, filter, and organize things online.

Common metadata for a recipe might include:

"title": "Tabbouleh Salad"
"prepTime": "20 minutes"
"diet": "Vegan"
"cuisine": "Levantine"
"keywords": "parsley, Mediterranean, healthy"

Analogy: Metadata is like a nutrition label on food packaging — it tells you what you’re getting, but doesn’t explain how or why the dish exists.

🧠 Ontology: Meaning and Relationships

An ontology is a formal structure that defines concepts and how they relate to each other. It creates a shared vocabulary that both people and machines can use to reason about the world.

In an ontology for food, you might find relationships like:

Tabbouleh → isA → Salad
Salad → isA → Dish
Parsley → isA → Herb
Herb → isUsedIn → Recipe

Ontologies are powerful because they define how knowledge is structured — not just what exists, but how it fits together.

Analogy: An ontology is like the index or table of contents of a cookbook — it defines the structure behind the content.

Popular ontologies:

schema.org – Used across the web for structured content like recipes, events, and articles
FOODON – A global ontology of food, nutrition, and culinary terms
SSSOM – Standard for mapping between ontologies

🌐 Knowledge Graph: Data With Context

A knowledge graph is where everything comes together. It applies an ontology to real-world data. Think of it as a smart database where facts are connected — not just listed.

Example knowledge graph facts:

Tabbouleh → hasIngredient → Parsley
Parsley → flavorProfile → Fresh
Tabbouleh → isA → Salad
Tabbouleh → origin → Levant

Analogy: A knowledge graph is like a well-annotated, cross-referenced recipe binder — one that “understands” how dishes, ingredients, and cultures connect.

Well-known knowledge graphs:

Google Knowledge Graph
Wikidata – Used by Wikipedia and many open data projects
DBpedia – Structured data extracted from Wikipedia

📚 A Real Example: Tabbouleh, Explained Three Ways

Let’s say you have a post about tabbouleh — the iconic parsley-based salad. Here’s how each concept applies:

Metadata: Vegan, Salad, Mediterranean, Prep time: 20 mins
Ontology: Tabbouleh isA Salad; Parsley isAn Herb; Bulgur isA Grain
Knowledge Graph: Tabbouleh → hasIngredient → Parsley → flavorProfile → Fresh

This shows how content moves from basic labels (metadata), to structured meaning (ontology), to rich, intelligent connections (knowledge graph).

🧱 Visualizing a Knowledge Graph

Tabbouleh
  ├── isA: Salad
  ├── hasIngredient:
  │     ├── Parsley
  │     ├── Bulgur
  │     ├── Tomato
  └── cuisine: Levantine

This kind of structure allows search engines, apps, and AI systems to “understand” what a dish is, where it fits, and how it might relate to user queries.

🤖 Where You See This in Real Life

Google Search: Shows rich cards for recipes, books, movies — thanks to metadata + ontology + knowledge graphs
Recipe Apps: Filter recipes by dietary tags or ingredient combinations
Voice Assistants: Answer “What can I make with parsley and lemon?” based on linked food concepts
Streaming Services: Suggest “romantic 90s comedies” by understanding category overlaps

These systems aren’t just searching — they’re reasoning.

🧩 Summary Table

Concept	What It Does	Real-World Role
Metadata	Describes content	Tags, categories, filters
Ontology	Defines meaning + relationships	Structure behind smart content
Knowledge Graph	Connects real-world facts	Enables search, AI, recommendations

🧠 Why Should You Care?

Even if you’re not a developer or data scientist, this matters:

If you’re a blogger, this helps you write content that Google understands and ranks
If you’re a content creator, this helps you structure your ideas for clarity and reuse
If you’re building a digital product, this helps you think like a system designer

The web is no longer just about text — it’s about meaningful, structured information. The more structured your knowledge, the more discoverable and usable it becomes.