Building RDF Graphs#

While individual triples are useful for making simple statements, the real power of RDF comes from connecting multiple triples together to form a graph. A graph allows us to represent complex relationships and build up rich descriptions of things we encounter every day.

What is a Graph?#

In RDF, a graph is simply a collection of connected triples. Each triple can be visualized as two nodes (the subject and object) connected by an arrow (the predicate). When multiple triples share common nodes, they form a network structure.

Let’s build up a simple example about a book and its author:

This can be visualized as a graph where: * Nodes represent resources (books, people, organizations) * Arrows represent properties (relationships) * Text in quotation marks represents literal values

RDF graph of book and author

A simple RDF graph describing a book and its author#

Common Graph Patterns#

Certain patterns appear frequently in RDF graphs. Here are some of the most common:

Star Pattern#

A single subject connected to multiple objects, like spokes on a wheel. This pattern is common when describing various properties of an item:

Chain Pattern#

Resources connected in sequence, forming a path. This is useful for representing sequences of events or relationships:

Tree Pattern#

Hierarchical relationships, often used for classification or organizational structures:

Connecting Graphs Together#

One of the most powerful features of RDF is the ability to combine graphs from different sources. Let’s see how information about a movie might be combined from different databases:

Movie Database:

Review Database:

Because both sources use the same identifier (ex:Inception), we can automatically combine this information into a single, comprehensive description of the movie.

Common Modeling Patterns#

Here are some typical patterns you might encounter when building graphs:

Event Planning#

Representing an event with multiple associated entities:

Best Practices for Building Graphs#

When building RDF graphs, consider these guidelines:

  1. Keep it Connected

Make sure all parts of your graph are connected - avoid isolated “islands” of information.

  1. Use Standard Patterns

Reuse common patterns when possible. This makes your data more predictable and easier to query.

  1. Balance Detail and Complexity

Include enough detail to be useful, but don’t add relationships that won’t be used.

  1. Think About Queries

Consider how the graph will be queried. Structure it to make common queries straightforward.

  1. Maintain Consistency

Use consistent patterns for similar types of information.

Summary#

RDF graphs allow us to represent complex, interconnected information in a way that’s both human-readable and machine-processable. By understanding common patterns and structures, we can:

  • Build meaningful connections between different pieces of information

  • Combine data from multiple sources

  • Create flexible, extensible data models

  • Represent real-world relationships clearly

Remember these key points when building your own graphs:

  1. Start simple and build up complexity gradually

  2. Use standard vocabularies like schema.org where possible

  3. Keep your graph connected - avoid isolated pieces of information

  4. Choose the right patterns for your use case

  5. Consider how your data will be queried and used

The next section will explore how to query these graphs using SPARQL, allowing us to extract specific information from our connected data.