> For the complete documentation index, see [llms.txt](https://docs.graph.build/EGeX4aTAJLlpg9Hh8kfl/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.graph.build/EGeX4aTAJLlpg9Hh8kfl/getting-started-tutorial/rdf-ontologies-and-models.md).

# RDF Ontologies and Models

An **OWL ontology** is a formal, structured representation of knowledge about a specific domain, defined using the **Web Ontology Language (OWL)**. OWL is a powerful language developed for use on the **Semantic Web**, and it allows the creation of rich, machine-readable descriptions of concepts, relationships, and constraints within a particular field of interest.

OWL ontologies are made of:

1. **Classes (Concepts)**: These represent the fundamental ideas or categories in the domain. For instance, in a medical ontology, classes could be things like "Patient", "Doctor", or "Disease".
2. **Properties (Relations)**: Properties define how classes and individuals are related to each other. OWL supports two main types:
   * **Object properties**: These link individuals to other individuals. For example, "hasDoctor" might relate a "Patient" to a "Doctor".
   * **Data properties**: These link individuals to data values (such as numbers or strings). For instance, "hasAge" might relate a "Patient" to an integer representing their age.

Use Graph.Build studio to draft, edit and publish OWL Ontologies with no-code.

### The Credit Card Transactions ontology

A common use case for graphs is to identify financial crimes. 

In this tutorial we will create an ontology that represents credit cards, credit card transaction events and account holders, as illustrated here:

<figure><img src="/files/5YigHVV3W1CXpdsAOpR1" alt=""><figcaption></figcaption></figure>