Resource Description Framework

Last updated
RDF 1.1 Concepts and Abstract Syntax
StatusPublished, W3C Recommendation
Year started1996
EditorsRichard Cyganiak, David Wood, Markus Lanthaler
Base standards URI
Related standards RDFS, OWL, RIF, RDFa
Domain Semantic Web
AbbreviationRDF
Website www.w3.org/TR/2014/REC-rdf11-concepts-20140225/

The Resource Description Framework (RDF) is a family of World Wide Web Consortium (W3C) specifications [1] originally designed as a metadata data model. It has come to be used as a general method for conceptual description or modeling of information that is implemented in web resources, using a variety of syntax notations and data serialization formats. It is also used in knowledge management applications.

Contents

RDF was adopted as a W3C recommendation in 1999. The RDF 1.0 specification was published in 2004, the RDF 1.1 specification in 2014.

Overview

The RDF data model [2] is similar to classical conceptual modeling approaches (such as entity–relationship or class diagrams). It is based on the idea of making statements about resources (in particular web resources) in expressions of the form subjectpredicateobject, known as triples . The subject denotes the resource, and the predicate denotes traits or aspects of the resource, and expresses a relationship between the subject and the object.

For example, one way to represent the notion "The sky has the color blue" in RDF is as the triple: a subject denoting "the sky", a predicate denoting "has the color", and an object denoting "blue". Therefore, RDF uses subject instead of object (or entity) in contrast to the typical approach of an entity–attribute–value model in object-oriented design: entity (sky), attribute (color), and value (blue).

RDF is an abstract model with several serialization formats (i.e. file formats), so the particular encoding for resources or triples varies from format to format.

This mechanism for describing resources is a major component in the W3C's Semantic Web activity: an evolutionary stage of the World Wide Web in which automated software can store, exchange, and use machine-readable information distributed throughout the Web, in turn enabling users to deal with the information with greater efficiency and certainty. RDF's simple data model and ability to model disparate, abstract concepts has also led to its increasing use in knowledge management applications unrelated to Semantic Web activity.

A collection of RDF statements intrinsically represents a labeled, directed multi-graph. This in theory makes an RDF data model better suited to certain kinds of knowledge representation than are other relational or ontological models. However, in practice, RDF data is often stored in relational database or native representations (also called Triplestores—or Quad stores, if context such as the named graph is also stored for each RDF triple). [3]

As RDFS and OWL demonstrate, one can build additional ontology languages upon RDF.

History

The initial RDF design, intended to "build a vendor-neutral and operating system-independent system of metadata," [4] derived from the W3C's Platform for Internet Content Selection (PICS), an early web content labelling system, [5] but the project was also shaped by ideas from Dublin Core, and from the Meta Content Framework (MCF), [4] which had been developed during 1995–1997 by Ramanathan V. Guha at Apple and Tim Bray at Netscape. [6]

A first public draft of RDF appeared in October 1997, [7] [8] issued by a W3C working group that included representatives from IBM, Microsoft, Netscape, Nokia, Reuters, SoftQuad, and the University of Michigan. [5]

In 1999, the W3C published the first recommended RDF specification, the Model and Syntax Specification ("RDF M&S"). [9] This described RDF's data model and an XML serialization. [10]

Two persistent misunderstandings about RDF developed at this time: firstly, due to the MCF influence and the RDF "Resource Description" initialism, the idea that RDF was specifically for use in representing metadata; secondly that RDF was an XML format rather than a data model, and only the RDF/XML serialisation being XML-based. RDF saw little take-up in this period, but there was significant work done in Bristol, around ILRT at Bristol University and HP Labs, and in Boston at MIT. RSS 1.0 and FOAF became exemplar applications for RDF in this period.

The recommendation of 1999 was replaced in 2004 by a set of six specifications: [11] "The RDF Primer", [12] "RDF Concepts and Abstract", [13] "RDF/XML Syntax Specification (revised)", [14] "RDF Semantics", [15] "RDF Vocabulary Description Language 1.0", [16] and "The RDF Test Cases". [17]

This series was superseded in 2014 by the following six "RDF 1.1" documents: "RDF 1.1 Primer," [18] "RDF 1.1 Concepts and Abstract Syntax," [19] "RDF 1.1 XML Syntax," [20] "RDF 1.1 Semantics," [21] "RDF Schema 1.1," [22] and "RDF 1.1 Test Cases". [23]

RDF topics

Vocabulary

The vocabulary defined by the RDF specification is as follows: [24]

Classes

rdf
  • rdf:XMLLiteral – the class of XML literal values
  • rdf:Property – the class of properties
  • rdf:Statement – the class of RDF statements
  • rdf:Alt, rdf:Bag, rdf:Seq – containers of alternatives, unordered containers, and ordered containers (rdfs:Container is a super-class of the three)
  • rdf:List – the class of RDF Lists
  • rdf:nil – an instance of rdf:List representing the empty list
rdfs
  • rdfs:Resource – the class resource, everything
  • rdfs:Literal – the class of literal values, e.g. strings and integers
  • rdfs:Class – the class of classes
  • rdfs:Datatype – the class of RDF datatypes
  • rdfs:Container – the class of RDF containers
  • rdfs:ContainerMembershipProperty – the class of container membership properties, rdf:_1, rdf:_2, ..., all of which are sub-properties of rdfs:member

Properties

rdf
  • rdf:type – an instance of rdf:Property used to state that a resource is an instance of a class
  • rdf:first – the first item in the subject RDF list
  • rdf:rest – the rest of the subject RDF list after rdf:first
  • rdf:value – idiomatic property used for structured values
  • rdf:subject – the subject of the RDF statement
  • rdf:predicate – the predicate of the RDF statement
  • rdf:object – the object of the RDF statement

rdf:Statement, rdf:subject, rdf:predicate, rdf:object are used for reification (see below).

rdfs
  • rdfs:subClassOf – the subject is a subclass of a class
  • rdfs:subPropertyOf – the subject is a subproperty of a property
  • rdfs:domain – a domain of the subject property
  • rdfs:range – a range of the subject property
  • rdfs:label – a human-readable name for the subject
  • rdfs:comment – a description of the subject resource
  • rdfs:member – a member of the subject resource
  • rdfs:seeAlso – further information about the subject resource
  • rdfs:isDefinedBy – the definition of the subject resource

This vocabulary is used as a foundation for RDF Schema, where it is extended.

Serialization formats

RDF 1.1 Turtle serialization
Filename extension .ttl
Internet media type text/turtle [25]
Developed by World Wide Web Consortium
Standard RDF 1.1 Turtle: Terse RDF Triple Language January 9, 2014;6 years ago (2014-01-09)
Open format?Yes
RDF/XML serialization
XML.svg
Filename extension .rdf
Internet media type application/rdf+xml [26]
Developed by World Wide Web Consortium
Standard Concepts and Abstract Syntax February 10, 2004;15 years ago (2004-02-10)
Open format?Yes

Several common serialization formats are in use, including:

RDF/XML is sometimes misleadingly called simply RDF because it was introduced among the other W3C specifications defining RDF and it was historically the first W3C standard RDF serialization format. However, it is important to distinguish the RDF/XML format from the abstract RDF model itself. Although the RDF/XML format is still in use, other RDF serializations are now preferred by many RDF users, both because they are more human-friendly, [34] and because some RDF graphs are not representable in RDF/XML due to restrictions on the syntax of XML QNames.

With a little effort, virtually any arbitrary XML may also be interpreted as RDF using GRDDL (pronounced 'griddle'), Gleaning Resource Descriptions from Dialects of Languages.

RDF triples may be stored in a type of database called a triplestore.

Resource identification

The subject of an RDF statement is either a uniform resource identifier (URI) or a blank node, both of which denote resources. Resources indicated by blank nodes are called anonymous resources. They are not directly identifiable from the RDF statement. The predicate is a URI which also indicates a resource, representing a relationship. The object is a URI, blank node or a Unicode string literal. As of RDF 1.1 resources are identified by IRI's. IRI is a generalization of URI. [35]

In Semantic Web applications, and in relatively popular applications of RDF like RSS and FOAF (Friend of a Friend), resources tend to be represented by URIs that intentionally denote, and can be used to access, actual data on the World Wide Web. But RDF, in general, is not limited to the description of Internet-based resources. In fact, the URI that names a resource does not have to be dereferenceable at all. For example, a URI that begins with "http:" and is used as the subject of an RDF statement does not necessarily have to represent a resource that is accessible via HTTP, nor does it need to represent a tangible, network-accessible resource — such a URI could represent absolutely anything. However, there is broad agreement that a bare URI (without a # symbol) which returns a 300-level coded response when used in an HTTP GET request should be treated as denoting the internet resource that it succeeds in accessing.

Therefore, producers and consumers of RDF statements must agree on the semantics of resource identifiers. Such agreement is not inherent to RDF itself, although there are some controlled vocabularies in common use, such as Dublin Core Metadata, which is partially mapped to a URI space for use in RDF. The intent of publishing RDF-based ontologies on the Web is often to establish, or circumscribe, the intended meanings of the resource identifiers used to express data in RDF. For example, the URI:

http://www.w3.org/TR/2004/REC-owl-guide-20040210/wine#Merlot

is intended by its owners to refer to the class of all Merlot red wines by vintner (i.e., instances of the above URI each represent the class of all wine produced by a single vintner), a definition which is expressed by the OWL ontology — itself an RDF document — in which it occurs. Without careful analysis of the definition, one might erroneously conclude that an instance of the above URI was something physical, instead of a type of wine.

Note that this is not a 'bare' resource identifier, but is rather a URI reference, containing the '#' character and ending with a fragment identifier.

Statement reification and context

Basic RDF triple comprising (subject, predicate, object). Basic RDF Graph.svg
Basic RDF triple comprising (subject, predicate, object).

The body of knowledge modeled by a collection of statements may be subjected to reification, in which each statement (that is each triple subject-predicate-object altogether) is assigned a URI and treated as a resource about which additional statements can be made, as in "Jane says that John is the author of document X". Reification is sometimes important in order to deduce a level of confidence or degree of usefulness for each statement.

In a reified RDF database, each original statement, being a resource, itself, most likely has at least three additional statements made about it: one to assert that its subject is some resource, one to assert that its predicate is some resource, and one to assert that its object is some resource or literal. More statements about the original statement may also exist, depending on the application's needs.

Borrowing from concepts available in logic (and as illustrated in graphical notations such as conceptual graphs and topic maps), some RDF model implementations acknowledge that it is sometimes useful to group statements according to different criteria, called situations, contexts, or scopes, as discussed in articles by RDF specification co-editor Graham Klyne. [36] [37] For example, a statement can be associated with a context, named by a URI, in order to assert an "is true in" relationship. As another example, it is sometimes convenient to group statements by their source, which can be identified by a URI, such as the URI of a particular RDF/XML document. Then, when updates are made to the source, corresponding statements can be changed in the model, as well.

Implementation of scopes does not necessarily require fully reified statements. Some implementations allow a single scope identifier to be associated with a statement that has not been assigned a URI, itself. [38] [39] Likewise named graphs in which a set of triples is named by a URI can represent context without the need to reify the triples. [40]

Query and inference languages

The predominant query language for RDF graphs is SPARQL. SPARQL is an SQL-like language, and a recommendation of the W3C as of January 15, 2008.

The following is an example of a SPARQL query to show country capitals in Africa, using a fictional ontology:

PREFIXex:<http://example.com/exampleOntology#>SELECT?capital?countryWHERE{?xex:cityname?capital;ex:isCapitalOf?y.?yex:countryname?country;ex:isInContinentex:Africa.}

Other non-standard ways to query RDF graphs include:

Validation and description

There are several proposals to validate and describe RDF:

Examples

Example 1: Description of a person named Eric Miller [46]

The following example is taken from the W3C website [46] describing a resource with statements "there is a Person identified by http://www.w3.org/People/EM/contact#me, whose name is Eric Miller, whose email address is e.miller123(at)example (changed for security purposes), and whose title is Dr.

An RDF Graph Describing Eric Miller Rdf graph for Eric Miller.png
An RDF Graph Describing Eric Miller

The resource "http://www.w3.org/People/EM/contact#me" is the subject.

The objects are:

The subject is a URI.

The predicates also have URIs. For example, the URI for each predicate:

In addition, the subject has a type (with URI http://www.w3.org/1999/02/22-rdf-syntax-ns#type), which is person (with URI http://www.w3.org/2000/10/swap/pim/contact#Person).

Therefore, the following "subject, predicate, object" RDF triples can be expressed:

In standard N-Triples format, this RDF can be written as:

<http://www.w3.org/People/EM/contact#me><http://www.w3.org/2000/10/swap/pim/contact#fullName>"Eric Miller".<http://www.w3.org/People/EM/contact#me><http://www.w3.org/2000/10/swap/pim/contact#mailbox><mailto:e.miller123(at)example>.<http://www.w3.org/People/EM/contact#me><http://www.w3.org/2000/10/swap/pim/contact#personalTitle>"Dr.".<http://www.w3.org/People/EM/contact#me><http://www.w3.org/1999/02/22-rdf-syntax-ns#type><http://www.w3.org/2000/10/swap/pim/contact#Person>.

Equivalently, it can be written in standard Turtle (syntax) format as:

@prefixeric:<http://www.w3.org/People/EM/contact#>.@prefixcontact:<http://www.w3.org/2000/10/swap/pim/contact#>.@prefixrdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>.eric:mecontact:fullName"Eric Miller".eric:mecontact:mailbox<mailto:e.miller123(at)example>.eric:mecontact:personalTitle"Dr.".eric:merdf:typecontact:Person.

Or, it can be written in RDF/XML format as:

<?xml version="1.0" encoding="utf-8"?><rdf:RDFxmlns:contact="http://www.w3.org/2000/10/swap/pim/contact#"xmlns:eric="http://www.w3.org/People/EM/contact#"xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><rdf:Descriptionrdf:about="http://www.w3.org/People/EM/contact#me"><contact:fullName>Eric Miller</contact:fullName></rdf:Description><rdf:Descriptionrdf:about="http://www.w3.org/People/EM/contact#me"><contact:mailboxrdf:resource="mailto:e.miller123(at)example"/></rdf:Description><rdf:Descriptionrdf:about="http://www.w3.org/People/EM/contact#me"><contact:personalTitle>Dr.</contact:personalTitle></rdf:Description><rdf:Descriptionrdf:about="http://www.w3.org/People/EM/contact#me"><rdf:typerdf:resource="http://www.w3.org/2000/10/swap/pim/contact#Person"/></rdf:Description></rdf:RDF>

Example 2: The postal abbreviation for New York

Certain concepts in RDF are taken from logic and linguistics, where subject-predicate and subject-predicate-object structures have meanings similar to, yet distinct from, the uses of those terms in RDF. This example demonstrates:

In the English language statement 'New York has the postal abbreviation NY' , 'New York' would be the subject, 'has the postal abbreviation' the predicate and 'NY' the object.

Encoded as an RDF triple, the subject and predicate would have to be resources named by URIs. The object could be a resource or literal element. For example, in the N-Triples form of RDF, the statement might look like:

<urn:x-states:New%20York><http://purl.org/dc/terms/alternative>"NY".

In this example, "urn:x-states:New%20York" is the URI for a resource that denotes the US state New York, "http://purl.org/dc/terms/alternative" is the URI for a predicate (whose human-readable definition can be found at here [47] ), and "NY" is a literal string. Note that the URIs chosen here are not standard, and don't need to be, as long as their meaning is known to whatever is reading them.

Example 3: A Wikipedia article about Tony Benn

In a like manner, given that "http://en.wikipedia.org/wiki/Tony_Benn" identifies a particular resource (regardless of whether that URI could be traversed as a hyperlink, or whether the resource is actually the Wikipedia article about Tony Benn), to say that the title of this resource is "Tony Benn" and its publisher is "Wikipedia" would be two assertions that could be expressed as valid RDF statements. In the N-Triples form of RDF, these statements might look like the following:

<http://en.wikipedia.org/wiki/Tony_Benn><http://purl.org/dc/elements/1.1/title>"Tony Benn".<http://en.wikipedia.org/wiki/Tony_Benn><http://purl.org/dc/elements/1.1/publisher>"Wikipedia".

To an English-speaking person, the same information could be represented simply as:

The title of this resource, which is published by Wikipedia, is 'Tony Benn'

However, RDF puts the information in a formal way that a machine can understand. The purpose of RDF is to provide an encoding and interpretation mechanism so that resources can be described in a way that particular software can understand it; in other words, so that software can access and use information that it otherwise couldn't use.

Both versions of the statements above are wordy because one requirement for an RDF resource (as a subject or a predicate) is that it be unique. The subject resource must be unique in an attempt to pinpoint the exact resource being described. The predicate needs to be unique in order to reduce the chance that the idea of Title or Publisher will be ambiguous to software working with the description. If the software recognizes http://purl.org/dc/elements/1.1/title (a specific definition for the concept of a title established by the Dublin Core Metadata Initiative), it will also know that this title is different from a land title or an honorary title or just the letters t-i-t-l-e put together.

The following example, written in Turtle, shows how such simple claims can be elaborated on, by combining multiple RDF vocabularies. Here, we note that the primary topic of the Wikipedia page is a "Person" whose name is "Tony Benn":

@prefixrdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>.@prefixfoaf:<http://xmlns.com/foaf/0.1/>.@prefixdc:<http://purl.org/dc/elements/1.1/>.<http://en.wikipedia.org/wiki/Tony_Benn>dc:publisher"Wikipedia";dc:title"Tony Benn";foaf:primaryTopic[afoaf:Person;foaf:name"Tony Benn"].

Applications

Some uses of RDF include research into social networking. It will also help people in business fields understand better their relationships with members of industries that could be of use for product placement. [55] It will also help scientists understand how people are connected to one another.

RDF is being used to have a better understanding of road traffic patterns. This is because the information regarding traffic patterns is on different websites, and RDF is used to integrate information from different sources on the web. Before, the common methodology was using keyword searching, but this method is problematic because it does not consider synonyms. This is why ontologies are useful in this situation. But one of the issues that comes up when trying to efficiently study traffic is that to fully understand traffic, concepts related to people, streets, and roads must be well understood. Since these are human concepts, they require the addition of fuzzy logic. This is because values that are useful when describing roads, like slipperiness, are not precise concepts and cannot be measured. This would imply that the best solution would incorporate both fuzzy logic and ontology. [56]

See also

Notations for RDF
Similar concepts
Other (unsorted)

Related Research Articles

The Semantic Web is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of Semantic Web is to make Internet data machine-readable. To enable the encoding of semantics with the data, technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL) are used. These technologies are used to formally represent metadata. For example, ontology can describe concepts, relationships between entities, and categories of things. These embedded semantics offer significant advantages such as reasoning over data and operating with heterogeneous data sources.

Reification is the process by which an abstract idea about a computer program is turned into an explicit data model or other object created in a programming language. A computable/addressable object—a resource—is created in a system as a proxy for a non computable/addressable object. By means of reification, something that was previously implicit, unexpressed, and possibly inexpressible is explicitly formulated and made available to conceptual manipulation. Informally, reification is often referred to as "making something a first-class citizen" within the scope of a particular system. Some aspect of a system can be reified at language design time, which is related to reflection in programming languages. It can be applied as a stepwise refinement at system design time. Reification is one of the most frequently used techniques of conceptual analysis and knowledge representation.

RDF Schema is a set of classes with certain properties using the RDF extensible knowledge representation data model, providing basic elements for the description of ontologies, otherwise called RDF vocabularies, intended to structure RDF resources. These resources can be saved in a triplestore to reach them with the query language SPARQL.

SPARQL RDF query language

SPARQL is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in Resource Description Framework (RDF) format. It was made a standard by the RDF Data Access Working Group (DAWG) of the World Wide Web Consortium, and is recognized as one of the key technologies of the semantic web. On 15 January 2008, SPARQL 1.0 became an official W3C Recommendation, and SPARQL 1.1 in March, 2013.


A web resource, or simply resource, is any identifiable thing, whether digital, physical, or abstract. Resources are identified using Uniform Resource Identifiers. In the Semantic Web, web resources and their semantic properties are described using the Resource Description Framework.

Notation3, or N3 as it is more commonly known, is a shorthand non-XML serialization of Resource Description Framework models, designed with human-readability in mind: N3 is much more compact and readable than XML RDF notation. The format is being developed by Tim Berners-Lee and others from the Semantic Web community. A formalization of the logic underlying N3 was published by Berners-Lee and others in 2008.

GRDDL is a markup format for Gleaning Resource Descriptions from Dialects of Languages. It is a W3C Recommendation, and enables users to obtain RDF triples out of XML documents, including XHTML. The GRDDL specification shows examples using XSLT, however it was intended to be abstract enough to allow for other implementations as well. It became a Recommendation on September 11, 2007.

RDFa is a W3C Recommendation that adds a set of attribute-level extensions to HTML, XHTML and various XML-based document types for embedding rich metadata within Web documents. The RDF data-model mapping enables its use for embedding RDF subject-predicate-object expressions within XHTML documents. It also enables the extraction of RDF model triples by compliant user agents.

RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information. The library contains an RDF/XML parser/serializer that conforms to the RDF/XML Syntax Specification (Revised). The library also contains both in-memory and persistent Graph backends. It is being developed by a number of contributors and was created by Daniel Krech who continues to maintain it.

Terse RDF Triple Language (Turtle) is a syntax and file format for expressing data in the Resource Description Framework (RDF) data model. Turtle syntax is similar to that of SPARQL, an RDF query language. It is a common data format for storing RDF data, along with N-Triples, JSON-LD and RDF/XML.

An RDF query language is a computer language, specifically a query language for databases, able to retrieve and manipulate data stored in Resource Description Framework (RDF) format.

Redland is a set of free software libraries written in C that provide support for the Resource Description Framework (RDF), created by Dave Beckett.

Blank node RDF node

In RDF, a blank node is a node in an RDF graph representing a resource for which a URI or literal is not given. The resource represented by a blank node is also called an anonymous resource. According to the RDF standard a blank node can only be used as subject or object of an RDF triple.

The Rule Interchange Format (RIF) is a W3C Recommendation. RIF is part of the infrastructure for the semantic web, along with (principally) SPARQL, RDF and OWL. Although originally envisioned by many as a "rules layer" for the semantic web, in reality the design of RIF is based on the observation that there are many "rules languages" in existence, and what is needed is to exchange rules between them.

N-Triples is a format for storing and transmitting data. It is a line-based, plain text serialisation format for RDF graphs, and a subset of the Turtle format. N-Triples should not be confused with Notation3 which is a superset of Turtle. N-Triples was primarily developed by Dave Beckett at the University of Bristol and Art Barstow at the World Wide Web Consortium (W3C).

A triplestore or RDF store is a purpose-built database for the storage and retrieval of triples through semantic queries. A triple is a data entity composed of subject-predicate-object, like "Bob is 35" or "Bob knows Fred".

TriX is a serialization format for RDF graphs. It is an XML format for serializing Named Graphs and RDF Datasets which offers a compact and readable alternative to the XML-based RDF/XML syntax. It was jointly created by HP Labs and Nokia.

Named graph database model

Named graphs are a key concept of Semantic Web architecture in which a set of Resource Description Framework statements are identified using a URI, allowing descriptions to be made of that set of statements such as context, provenance information or other such metadata.

XHTML+RDFa is an extended version of the XHTML markup language for supporting RDF through a collection of attributes and processing rules in the form of well-formed XML documents. XHTML+RDFa is one of the techniques used to develop Semantic Web content by embedding rich semantic markup. Version 1.1 of the language is a superset of XHTML 1.1, integrating the attributes according to RDFa Core 1.1. In other words, it is an RDFa support through XHTML Modularization.

A semantic triple, or simply triple, is the atomic data entity in the Resource Description Framework (RDF) data model. As its name indicates, a triple is a set of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions.

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Sources

Further reading