RDF Vocabularies for Dart - Type-safe RDF Constants

Overview

rdf_vocabularies provides type-safe access to standard RDF vocabulary terms as Dart constants for use with rdf_core.

The library is designed for both RDF newcomers and experts, offering structured ways to work with semantic data while maintaining compilation-time safety.

Part of a whole family of projects

If you are looking for more rdf-related functionality, have a look at our companion projects:

basic graph classes as well as turtle/jsonld/n-triple encoding and decoding: rdf_core
encode and decode rdf/xml format: rdf_xml
generate your own easy-to-use constants for other vocabularies with a build_runner: rdf_vocabulary_to_dart
map Dart Objects ↔️ RDF: rdf_mapper

Package Characteristics

Zero Runtime Overhead: Nearly all content is composed of compile-time constants
Small Binary Size: Minimal impact on your application's size
Type Safety: Catch vocabulary usage errors at compile time
IDE Assistance: Get autocompletion and documentation directly in your editor

Features

Dual Interface: Choose between class-specific access for beginners or full vocabulary access for experts
Comprehensive Coverage: Access terms from popular RDF vocabularies (Schema.org, FOAF, Dublin Core, etc.)
Rich Documentation: Each term includes its original description from the vocabulary
Seamless Integration: Works perfectly with the rdf_core library

Getting Started

Add the package to your pubspec.yaml:

dependencies:
  rdf_vocabularies: ^0.3.0
  rdf_core: ^0.9.0  # Required for RDF data structures

Usage

For RDF Newcomers: Class-Specific Approach

If you're new to RDF, the class-specific approach guides you to use the correct properties for each type of resource:

import 'package:rdf_core/rdf_core.dart';
import 'package:rdf_vocabularies/schema.dart';
import 'package:rdf_vocabularies/xsd.dart';

void main() {
  final personIri = IriTerm('http://example.org/person/jane_doe');
  final addressNode = BlankNodeTerm();
  
  // Create a graph with triples using class-specific constants
  final graph = RdfGraph.fromTriples([
    // Declare the resource type using SchemaPerson constants
    Triple(personIri, SchemaPerson.rdfType, SchemaPerson.classIri),
    
    // Use properties specific to Person - your IDE will help you discover valid properties
    Triple(personIri, SchemaPerson.name, LiteralTerm.string('Jane Doe')),
    Triple(personIri, SchemaPerson.email, LiteralTerm.string('jane.doe@example.com')),
    Triple(personIri, SchemaPerson.birthDate, LiteralTerm('1990-01-01', datatype: Xsd.date)),

    // Even those defined in other vocabularies, if their relationship is known to the library
    Triple(personIri, SchemaPerson.foafAge, LiteralTerm.integer(42)),

    // For properties from foreign vocabularies that are not restricted to a specific class, 
    // but are designed to be used universally, you can use the generated UniversalProperties
    // classes. 
    Triple(personIri, DcUniversalProperties.creator, LiteralTerm.string('System')),

    // Create a complex structure with an address
    Triple(personIri, SchemaPerson.address, addressNode),
    Triple(addressNode, SchemaPostalAddress.rdfType, SchemaPostalAddress.classIri),
    Triple(addressNode, SchemaPostalAddress.streetAddress, LiteralTerm.string('123 Main St')),
    Triple(addressNode, SchemaPostalAddress.addressLocality, LiteralTerm.string('Anytown')),
  ]);
}

Benefits of this approach:

Your IDE shows only relevant properties for each class
Compile-time type safety prevents mixing incompatible vocabulary terms
Discoverability through autocomplete helps you learn the vocabulary structure

For RDF Experts: Full Vocabulary Approach

Experienced RDF developers who know exactly which vocabulary terms they need can use the more direct full vocabulary classes:

import 'package:rdf_core/rdf_core.dart';
import 'package:rdf_vocabularies/schema.dart';
import 'package:rdf_vocabularies/rdf.dart';
import 'package:rdf_vocabularies/foaf.dart';
import 'package:rdf_vocabularies/xsd.dart';

void main() {
  final personIri = IriTerm('http://example.org/person/jane_doe');
  final addressNode = BlankNodeTerm();
  
  // Create a graph with direct vocabulary access
  final graph = RdfGraph.fromTriples([
    Triple(personIri, Rdf.type, Schema.Person),
    
    // Mix properties from different vocabularies freely
    Triple(personIri, Schema.name, LiteralTerm.string('Jane Doe')),
    Triple(personIri, Foaf.age, LiteralTerm.integer(42)),
    Triple(personIri, Schema.email, LiteralTerm.string('jane.doe@example.com')),
    
    // Create a complex structure with an address
    Triple(personIri, Schema.address, addressNode),
    Triple(addressNode, Rdf.type, Schema.PostalAddress),
    Triple(addressNode, Schema.streetAddress, LiteralTerm.string('123 Main St')),
  ]);
}

Benefits of this approach:

Maximally flexible - combine terms from any vocabulary
More concise syntax for those who know exactly what they need
Natural for developers coming from other RDF environments

Supported Vocabularies

This package includes constants for these vocabularies:

ACL: Web Access Control vocabulary
Contact: Contact information vocabulary
DC: Dublin Core basic elements
DCMIType: Dublin Core type vocabulary
DCTerms: Dublin Core terms
EventOwl: Event vocabulary
FOAF: Friend of a Friend vocabulary
GEO: Geospatial vocabulary
LDP: Linked Data Platform vocabulary
OWL: Web Ontology Language
RDF: Resource Description Framework base vocabulary
RDFS: RDF Schema vocabulary
Schema: Schema.org vocabulary
SKOS: Simple Knowledge Organization System
Solid: Solid platform vocabulary
VCard: vCard ontology for contacts
VS: Vocabulary Status ontology
XSD: XML Schema Datatypes

Performance Impact

Including rdf_vocabularies in your project:

Package Size: Minimal impact on package size as it consists primarily of constants
Runtime Performance: Zero runtime overhead since values are compile-time constants
Memory Usage: Negligible increase in memory usage
Build Time: May slightly increase initial build time, but no impact on runtime performance

🛣️ Roadmap / Next Steps

🤝 Contributing

Contributions, bug reports, and feature requests are welcome!

Fork the repo and submit a PR
See CONTRIBUTING.md for guidelines
Join the discussion in GitHub Issues

🤖 AI Policy

This project is proudly human-led and human-controlled, with all key decisions, design, and code reviews made by people. At the same time, it stands on the shoulders of LLM giants: generative AI tools are used throughout the development process to accelerate iteration, inspire new ideas, and improve documentation quality. We believe that combining human expertise with the best of AI leads to higher-quality, more innovative open source software.

Libraries

acl
contact
dc
dcmitype
dcterms
eventowl
foaf
geo
ldp
owl
rdf
rdfs
schema
schema_http
skos
solid
vcard
vs
xsd