Raptor RDF: The Ultimate C Library for RDF Syntax

Raptor is a powerful, open-source C library designed for parsing and serializing Resource Description Framework (RDF) data. For developers working with semantic web technologies and linked data, Raptor provides a robust and efficient solution for handling various RDF syntaxes. This guide delves into the Raptor RDF Syntax Library, highlighting its capabilities and why it stands out as a crucial tool in the RDF ecosystem.

Overview of the Raptor RDF Syntax Library

At its core, Raptor is engineered to bridge the gap between different RDF formats, offering a comprehensive suite of parsers and serializers. It takes RDF data in various syntaxes and converts it into RDF triples, the fundamental building blocks of RDF. Conversely, Raptor can serialize these triples back into a chosen syntax. This versatility makes Raptor indispensable for applications that need to process RDF data in diverse formats.

Raptor supports an extensive range of parsing syntaxes, ensuring compatibility with widely used standards. These include:

RDF/XML: The foundational XML-based syntax for RDF.
N-Quads: An extension of N-Triples for RDF datasets, incorporating context graphs.
N-Triples: A straightforward, line-based syntax for RDF graphs.
Turtle: A more compact and human-readable RDF triple language.
TRiG: An RDF Dataset Language extending Turtle for named graphs.
RDFa: Attributes in HTML and XML for embedding RDF.
RSS and Atom: Syndication formats, including various RSS versions, Atom 0.3, and Atom 1.0.
GRDDL and Microformats: Techniques for extracting RDF from HTML, XHTML, and XML.

On the serialization front, Raptor is equally comprehensive, supporting:

RDF/XML: In regular, abbreviated, and XMP variations.
Turtle: For concise RDF serialization.
N-Quads and N-Triples: For line-based serialization.
Atom 1.0 and RSS 1.0: For syndication feeds.
GraphViz DOT: For visualizing RDF graphs.
HTML: For embedding RDF in web pages.
JSON and mKR: Modern data formats for RDF representation.

Raptor is designed for seamless integration with the Redland RDF library but functions independently, offering portability across various POSIX systems, including Unix, Linux, BSD, macOS, and Windows (via Cygwin and native Win32).

Key features of Raptor include:

Redland Integration: Designed to work harmoniously with the Redland RDF library.
Web Content Parsing: Capable of parsing content directly from the web using libcurl, libxml2, or BSD libfetch.
Full RDF Term Support: Handles all RDF terms, including datatyped and XML literals.
Configurable Features: Optional parsers and serializers can be selected during configuration.
Language Bindings: Accessible via Perl, PHP, Python, and Ruby through Redland.
Memory Efficiency: Engineered to prevent memory leaks, ensuring stability.
High Performance: Optimized for speed in RDF parsing and serialization.
Standalone Utility: Comes with the rapper utility for command-line RDF parsing.

Raptor Parsers in Detail

Raptor’s parsing capabilities are extensive, covering a wide spectrum of RDF syntaxes to accommodate diverse data sources and standards.

RDF/XML Parser

The RDF/XML parser in Raptor adheres to the W3C standard for RDF/XML syntax. This parser is essential for handling RDF data encoded in XML, the original and still widely used syntax for RDF.

N-Quads Parser

Raptor’s N-Quads parser is compliant with the RDF 1.1 N-Quads specification. N-Quads extends N-Triples by allowing a fourth element to represent the graph context, making it suitable for RDF datasets where triples are associated with named graphs.

N-Triples Parser

Supporting the RDF 1.1 N-Triples syntax, Raptor’s N-Triples parser handles this line-based, straightforward format for RDF graphs. It’s based on the earlier N-Triples specification and is crucial for processing simple RDF data exchanges.

Turtle Parser

Raptor incorporates a parser for Turtle (Terse RDF Triple Language). Turtle’s concise and readable syntax makes it a popular choice for writing and sharing RDF data, and Raptor’s parser fully supports this format.

TRiG Parser

For handling RDF datasets with named graphs in a Turtle-like syntax, Raptor provides a TRiG parser. TRiG is essential for more complex RDF structures, and Raptor ensures robust parsing, although it’s noted that graph delimiters {} and the GRAPH keyword are required.

RSS “Tag Soup” Parser

Raptor includes a flexible parser for various RSS formats, often referred to as “tag soup” due to their inconsistent use of elements. This parser aims to convert RSS feeds into RSS 1.0 RDF triples, including support for RSS enclosures. It also extends to Atom syndication formats, supporting both Atom 1.0 and earlier Atom 0.3 versions.

GRDDL and Microformats Parser

To extract RDF from HTML, XHTML, and XML documents, Raptor offers a GRDDL (Gleaning Resource Descriptions from Dialects of Languages) parser. This parser leverages profiles within documents to apply XSLT transformations into RDF/XML or other RDF syntaxes. It also handles microformats like hCard and hReview using public XSL stylesheets, making it a versatile tool for web data extraction.

RDFa Parser

Raptor integrates an RDFa parser supporting both RDFa 1.0 and RDFa 1.1. Implemented via the bundled librdfa library, this parser is crucial for extracting semantic data embedded within web pages using RDFa attributes.

Raptor Serializers in Detail

Raptor’s serialization capabilities are as comprehensive as its parsing, providing serializers for a range of RDF syntaxes to output RDF triples in various formats.

RDF/XML Serializer

Raptor offers an RDF/XML serializer compliant with the W3C RDF Core working group revisions. It provides a straightforward triple-based RDF/XML serialization without optimizations. Additionally, Raptor includes a serializer that uses RDF/XML abbreviations for a more compact and readable output, suitable for smaller documents.

N-Quads Serializer

For serializing RDF datasets, Raptor provides an N-Quads serializer. This serializer outputs RDF triples in the N-Quads format, including the context graph for each triple, aligning with the RDF 1.1 N-Quads specification.

N-Triples Serializer

The N-Triples serializer in Raptor outputs RDF graphs in the simple, line-based N-Triples format. It adheres to the RDF 1.1 N-Triples specification and the earlier N-Triples syntax, making it ideal for basic RDF data serialization.

Atom 1.0 Serializer

Raptor includes a serializer for the Atom 1.0 syndication format. This serializer enables the generation of Atom feeds from RDF data, useful for creating semantic web feeds.

JSON Serializers

Raptor provides two JSON serializers to cater to different needs:

json: Serializes RDF into a resource-centric, abbreviated JSON format, similar to Turtle or RDF/XML-Abbreviated, as defined in RDF 1.1 JSON Alternate Serialization (RDF/JSON).
json-triples: Outputs a triple-centric JSON format, based on the SPARQL results in JSON format, suitable for data exchange and processing.

Note that JSON-LD is not directly supported due to its complexity.

GraphViz DOT Serializer

For visualizing RDF graphs, Raptor offers a GraphViz DOT serializer. This serializer outputs RDF data in the DOT format, which can be used by GraphViz tools to generate graphical representations of RDF graphs, aiding in understanding and presentation.

RSS 1.0 Serializer

Raptor includes a serializer for the RDF Site Summary (RSS) 1.0 format. This allows for the creation of RSS 1.0 feeds from RDF data, contributing to the semantic web by providing RDF-based syndication.

Turtle Serializer

The Turtle serializer in Raptor outputs RDF data in the Turtle syntax. This serializer is valuable for generating human-readable and compact RDF representations.

XMP Serializer

Raptor provides an alpha-quality XMP (Extensible Metadata Platform) serializer. This serializer outputs RDF/XML in the Adobe XMP profile, suitable for embedding metadata within external documents.

mKR Serializer

For the mKR (my Knowledge Representation) Language, Raptor includes a dedicated serializer. This allows for serialization of RDF data into the mKR format, catering to specific knowledge representation needs.

Documentation and Resources

Comprehensive documentation for Raptor is available through the libraptor.3 UNIX manual page, detailing the public API. The rapper utility program serves as a practical demonstration of Raptor’s usage, showcasing parsing and serialization functionalities. For users integrating Raptor with Redland, Redland’s documentation provides guidance on utilizing Raptor’s parsers. Further examples are included in the Raptor distribution’s example directory. Installation instructions are provided in the Installation document.

Source and Licensing

Raptor’s source code is readily accessible. Packaged sources can be downloaded from http://download.librdf.org/source/. The development is actively managed using GIT, with sources browsable and clonable from GitHub at git://github.com/dajobe/raptor.git.

Raptor is released under open-source licenses, specifically LGPL (GNU Lesser General Public License) or Apache License 2.0, offering flexibility in its use and distribution. Full license details are available in the LICENSE.html file.

Community and Support

The Redland mailing lists serve as a central hub for discussions related to Raptor and Redland, covering development, usage, future directions, and release announcements. This community support is invaluable for users and developers alike.

In conclusion, the Raptor RDF Syntax Library is a vital asset for anyone working with RDF data. Its extensive parser and serializer support, combined with its efficiency, portability, and robust feature set, makes it an indispensable tool for the semantic web and linked data landscape.