JSON-LD - Linked Data Expression in JSON 1.0

1.1 How to Read this Document

This document is a detailed specification for a serialization of JSON for Linked data. The document is primarily intended for the following audiences:

• Web developers that want to understand the design decisions and language syntax for JSON-LD.
• Software developers that want to encode Microformats, RDFa, or Microdata in a way that is cross-language compatible via JSON.
• Software developers that want to write implement processors and APIs for JSON-LD.

To understand the basics in this specification you must first be familiar with JSON, which is detailed in [ RFC4627 ]. To understand the API and how it is intended to operate in a programming environment, it is useful to have working knowledge of the JavaScript programming language [ ECMA-262 ] and WebIDL [ WEBIDL ]. To understand how JSON-LD maps to RDF, it is helpful to be familiar with the basic RDF as described in concepts [ RDF-CONCEPTS ].

Examples may contain references to existing vocabularies and use abbreviations in CURIEs and source code. The following is a list of all vocabularies and their abbreviations, as used in this document:

• The Dublin Core vocabulary (abbreviation: dc , e.g., dc:title )
• The Friend of a Friend vocabulary (abbreviation: foaf , e.g., foaf:knows )
• The RDF vocabulary (abbreviation: rdf , e.g., rdf:type )
• The XSD vocabulary (abbreviation: xsd , e.g., xsd:integer )

1.2 Contributing

There are a number of ways that one may participate in the development of this specification:

• All comments and Technical discussion takes place typically occurs on the public mailing list: public-linked-json@w3.org
• Public teleconferences are held on Tuesdays at 1500UTC on the second and fourth week of each month.
• Specification bugs and issues should be reported in the issue tracker .
• Source code for the specification can be found on Github.
• The #json-ld IRC channel is available for real-time discussion on irc.freenode.net.

2.1 Goals and Rationale

A number of design considerations were explored during the creation of this markup language:

Simplicity

Developers don't need to only know RDF in order JSON and three keywords to use the basic functionality provided by in JSON-LD. No extra processors or software libraries are necessary to use JSON-LD in its most basic form. The language attempts to ensure that developers have an easy learning curve.

Compatibility

The JSON-LD markup should must be 100% compatible with JSON. This ensures that all of the standard JSON libraries work seamlessly with JSON-LD documents.

Expressiveness

All major RDF concepts The syntax must be expressible via the JSON-LD syntax. able to express directed graphs, which have been proven to be able to simply express almost every real world data model.

Terseness

The JSON-LD syntax must be very terse and human readable. readable, requiring as little as possible from the developer.

Pragmatism

Mixing the expression of pure Linked Data with data that is not linked was an approach that was driven by pragmatism. JSON-LD attempts to be more practical than theoretical in its approach to Linked Data.

Zero Edits, most of the time

JSON-LD provides a mechanism that allows developers to specify context in a way that is out-of-band. This allows organizations that have already deployed large JSON-based infrastructure to add meaning to their JSON in a way that is not disruptive to their day-to-day operations and is transparent to their current customers. At times, mapping JSON to RDF a graph representation can become difficult - in difficult. In these instances, rather than having JSON-LD support esoteric markup, we chose not to support the use case and support a simplified syntax instead. So, while we strive for Zero Edits, Edits was a goal, it was not always possible without adding great complexity to the language.

Streaming

The format supports both document-based and stream-based processing.

2.2 Map Terms Linked Data

The following definition for Linked Data is the one that will be used for this specification.

1. Linked Data is a set of documents, each containing a representation of a linked data graph.
2. A linked data graph is a labeled directed graph, where nodes are subject s or object s, and edges are properties.
3. A subject is any node in a linked data graph with at least one outgoing edge.
4. A subject should be labeled with a IRI.
5. A property is an edge of the linked data graph .
6. A property must be labeled with an IRI.
7. An object is a node in a linked data graph with at least one incoming edge.
8. An object may be labeled with an IRI.
9. An IRI that is a label in a linked data graph should be dereferencable to IRIs a Linked Data document describing the labeled subject , object or property .
10. A literal is an object with a label that is not an IRI

Note that the definition for Linked Data above is silent on the topic of unlabeled nodes. Unlabeled nodes are not considered Linked Data . However, this specification allows for the expression of unlabled nodes, as most graph-based data sets on the Web contain a number of associated nodes that are not named and thus are not directly de-referenceable.

2.3 Linking Data

An Internationalized Resource Identifier ( IRI ) ), as described in [ RFC3987 ], is a mechanism for representing unique identifiers on the web. In Linked Data, IRIs (or URI references) are Data , an IRI is commonly used for describing entities and properties. expressing a subject , a property or an object .

Establishing JSON-LD defines a mechanism to map JSON values to IRIs will help in the mapping of JSON objects to RDF. IRIs. This does not mean that JSON-LD must requires every key or value to be restrictive in declaring a set of terms, rather, experimentation an IRI, but rather ensures that keys and innovation should values can be supported as part of mapped to IRIs if the core design of JSON-LD. developer so desires to transform their data into Linked Data. There are, however, are a number of very small design criteria few techniques that can ensure that developers will generate good RDF data that will create value Linked Data for the greater semantic web community and JSON/REST-based Web Services community. Web. JSON-LD formalizes those techniques.

We will be using the following JSON object markup as the example for the rest of this section:

{
  "a": "Person",

  "name": "Manu Sporny",
  "homepage": "http://manu.sporny.org/"

  "homepage": "http://manu.sporny.org/",

  "avatar": "http://twitter.com/account/profile_image/manusporny"
}

2.3 2.4 The JSON-LD Context

A In JSON-LD, a context is used to allow developers to use aliases for map term s to IRI s. A term is a short word that may be expanded to an IRI . The semantic web, just like the document-based web, uses IRIs for unambiguous identification. The idea is that these terms term s mean something, which you will eventually want to query. A context allows the expression of a number something that may be of terms which map directly use to IRI s. other developers. For example, the term name may map directly to the IRI http://xmlns.com/foaf/0.1/name . This allows JSON-LD documents to be constructed using the common JSON syntax practice of using simple name/value pairs. pairs while ensuring that the data is useful outside of the database or page in which it resides.

To reduce These Linked Data term s are typically collected in a context and then used by adding a single line to the number of different JSON markup above:

{
  "@context": "http://example.org/json-ld-contexts/person",
  "name": "Manu Sporny",
  "homepage": "http://manu.sporny.org/",
  "avatar": "http://twitter.com/account/profile_image/manusporny"
}

The addition above transforms the previous JSON document into a JSON document with added semantics because the @context specifies how the name , homepage , and avatar terms that must be defined, JSON-LD also map to IRIs. Mapping those keys to IRIs gives the data global context. If two developers use the same IRI to describe a property, they are more than likely expressing the same concept. This allows terms both developers to be used re-use each others data without having to expand Compact URIs ( CURIE ). agree to how their data will inter-operate on a site-by-site basis.

The semantic web specifies this via uses a special type of document called a Web Vocabulary Documents , in which to define term s. A context is a type of Web vocabulary. Typically, these Web Vocabulary documents have prefix is es associated with a document, them and contain a suffix number of term declarations. A prefix , like a term , is used a short word that expands to create an IRI based on this a Web Vocabulary IRI. Prefix es are helpful when a developer wants to mix multiple vocabularies together in a context, but does not want to go to the trouble of defining every single term in every single vocabulary. Some Web Vocabularies may have 10-20 terms defined. If a developer wants to use 3-4 different vocabularies, the number of terms that would have to be declared in a single context would become quite large. To reduce the number of different terms that must be defined, JSON-LD also allows prefixes to be used to compact IRIs.

For example, the IRI http://xmlns.com/foaf/0.1/ specifies a Web Vocabulary Document, and which may be represented using the foaf prefix . The foaf Web Vocabulary contains a term called name . If you join the foaf prefix with the name is suffix, you can build a term in compact IRI that vocabulary. Join the two items together and you have will expand out into an unambiguous identifier absolute IRI for a the http://xmlns.com/foaf/0.1/name vocabulary term. The Compact URI Expression, That is, the compact IRI, or short-form, is foaf:name and the expanded-form is http://xmlns.com/foaf/0.1/name . This vocabulary term identifies the given name for something, for example - is used to specify a person's name.

Developers, and machines, would be are able to use this IRI (plugging it directly into a web browser, for instance) to go to the term and get a definition of what the term means. Much like we can use WordNet today to see the definition of words in the English language. Machines Developers and machines need the same sort of dictionary of terms, and URIs terms. IRIs provide a way to ensure that these terms are unambiguous.

The context provides a collection of vocabulary terms term s and prefix es that can be used for a to expand JSON object. keys and values into IRI s.

{
  "",
  "": "Manu Sporny",
  "": "http://manu.sporny.org"
  "": "http://twitter.com/account/profile_image/manusporny"

    "name": "http://xmlns.com/foaf/0.1/name",
    "homepage": "http://xmlns.com/foaf/0.1/homepage",
    "avatar": "http://xmlns.com/foaf/0.1/avatar"

}

3. 2.5 Markup Examples The JSON-LD markup examples below demonstrate how JSON-LD can be used From JSON to express semantic data marked up in other languages such as RDFa, Microformats, and Microdata. These sections are merely provided as proof that JSON-LD is very flexible in what it can express across different Linked Data approaches. 3.1 RDFa

The following example describes three people with their respective names If a set of terms such as, name , homepage , and homepages. <div > <ul> <li > <a >Bob</a> </li> <li > <a >Eve</a> </li> <li > <a >Manu</a> </li> </ul> </div> An example JSON-LD implementation is described below, however, there avatar , are other ways to mark-up this information such defined in a context, and that the context is not repeated. [ { "@": "_:bnode1", "a": "foaf:Person", "foaf:homepage": "http://example.com/bob/", "foaf:name": "Bob" }, { "@": "_:bnode2", "a": "foaf:Person", "foaf:homepage": "http://example.com/eve/", "foaf:name": "Eve" }, { "@": "_:bnode3", "a": "foaf:Person", "foaf:homepage": "http://example.com/manu/", "foaf:name": "Manu" } ] 3.2 Microformats The following example uses a simple Microformats hCard example used to express how resolve the Microformat is represented names in JSON-LD. <div class="vcard"> <a class="url fn" href="http://tantek.com/">Tantek Çelik</a> </div> The representation of the hCard expresses JSON objects, machines are able to automatically expand the Microformat terms in the context and uses them directly for the url and fn properties. Also note that the Microformat to JSON-LD processor has generated the proper URL type for http://tantek.com . something meaningful and unambiguous, like this:

{
  "@context": 
  {
    "vcard": "http://microformats.org/profile/hcard#vcard",
    "url": "http://microformats.org/profile/hcard#url",
    "fn": "http://microformats.org/profile/hcard#fn",
    "@coerce": { "xsd:anyURI": "url" }
  },
  "@": "_:bnode1",
  "a": "vcard",
  "url": "http://tantek.com/",
  "fn": "Tantek Çelik"

  "http://xmlns.com/foaf/0.1/name": "Manu Sporny",
  "http://xmlns.com/foaf/0.1/homepage": "http://manu.sporny.org"
  "http://rdfs.org/sioc/ns#avatar": "http://twitter.com/account/profile_image/manusporny"

}

Note that the JSON-LD representation of the Microdata information stays true to the desires of the Microdata community Doing this allows JSON to avoid contexts and instead refer be unambiguously machine-readable without requiring developers that use JSON to items by drastically change their full IRI. workflow.

4.1 3.1 IRIs

Expressing IRIs are fundamental to Linked Data as that is how most subjects subject s and many objects object are identified. named. IRIs can be expressed in a variety of different ways in JSON-LD.

1. In general, an IRI is generated if it is term s in the key position in an associative array. array that have a mapping to an IRI or another key in the context are expanded to an IRI by JSON-LD processors. There are special rules for processing keys in @context and when dealing with keys that start with the @ @subject character.
2. An IRI is generated for the value specified using @ @subject , if it is a string.
3. An IRI is generated for the value specified using a @type .
4. An IRI is generated for the value specified using the @iri keyword.
5. An IRI is generated when there are @coerce rules in effect for xsd:anyURI for a particular vocabulary term. key named @iri .

An example of IRI generation for a IRIs can be expressed directly in the key outside of a @context : position like so:

{
...
  "http://xmlns.com/foaf/0.1/name": "Manu Sporny",
...
}

In the example above, the key http://xmlns.com/foaf/0.1/name is interpreted as an IRI, as opposed to being interpreted as a string..

Term expansion occurs for IRIs if a term is defined within the active context :

{
  "@context": {"name": "http://xmlns.com/foaf/0.1/name"},
...
  "name": "Manu Sporny",
...
}

CURIE expansion also occurs for keys Prefix es are expanded when used in JSON-LD: keys:

{
  "@context": {"foaf": "http://xmlns.com/foaf/0.1/"},

...
  "foaf:name": "Manu Sporny",
...
}

foaf:name above will automatically expand out to the IRI http://xmlns.com/foaf/0.1/name .

An IRI is generated when a value is associated with a key using the @iri keyword:

{
...
  "foaf:homepage": { "@iri": "http://manu.sporny.org" }
...
}

If type coercion rules are specified in the @context for a particular vocabulary term, an IRI is generated:

{
  "@context": 
  { 

  {
    ...

    "@coerce": 
    {
      "xsd:anyURI": "foaf:homepage"
    } 

      "@iri": "foaf:homepage"
    }

  }
...
  "foaf:homepage": "http://manu.sporny.org",

  "foaf:homepage": "http://manu.sporny.org/",

...
}

Even though the value http://manu.sporny.org/ is a string, the type coercion rules will transform the value into an IRI when processed by a JSON-LD Processor

4.2 3.2 Identifying the Subject

A subject is declared using the @ @subject key. The subject is the first piece of information needed by the JSON-LD processor in order to create the (subject, property, object) tuple, also known as a triple.

{
...
  "",

  "@subject": "http://example.org/people#joebob",

...
}

The example above would set the subject to the IRI http://example.org/people#joebob .

4.3 3.3 Specifying the Type

The type of a particular subject can be specified using the a @type key. Specifying the type in this way will generate a triple of the form (subject, type, type-url).

{
...
  "@": "http://example.org/people#joebob",
  "",

  "@subject": "http://example.org/people#joebob",
  "@type": "http://xmlns.com/foaf/0.1/Person",

...
}

The example above would generate the following triple if the JSON-LD document is mapped to RDF (in N-Triples notation):

<http://example.org/people#joebob> 
   <http://www.w3.org/1999/02/22-rdf-syntax-ns#type>
<http://xmlns.com/foaf/0.1/Person>
.

4.4 3.4 Plain Literals Strings

Regular text strings are called a strings, also refered to as plain literal in RDF and s, are easily expressed using regular JSON strings.

{
...
  "foaf:name": "Mark Birbeck",
...
}

4.5 3.5 Language Specification in Plain Literals String Internationalization

JSON-LD makes an assumption that plain literal s strings with associated language encoding information is are not very common when used in JavaScript and Web Services. Thus, it takes a little more effort to express plain literals in a specified language. strings with associated language information.

{
...
  "foaf:name": 
  {
    "@literal": "花澄",
    "@language": "ja"
  }
...
}

The example above would generate a plain literal for 花澄 and associate the ja language tag code with the triple that is generated. Languages must be expressed in [ BCP47 ] format.

4.6 3.6 Typed Literals Datatypes

A value with an associated datatype, also known as a typed literal , is indicated by attaching a IRI to the end of associating a plain literal , and this with an IRI which indicates the typed literal's datatype. Literals Typed literals may be typed expressed in JSON-LD in three ways:

1. By utilizing the @coerce keyword.
2. By utilizing the expanded form for specifying objects.
3. By using a native JSON datatype.

The first example uses the @coerce keyword to express a typed literal:

{
  "@context": 
  { 

  {
    "dc":  "http://purl.org/dc/terms/",
    "xsd": "http://www.w3.org/2001/XMLSchema#"

    "@coerce": 
    {
      "xsd:dateTime": "dc:modified"
    }
  }
...
  "dc:modified": "2010-05-29T14:17:39+02:00",
...
}

The second example uses the expanded form for specifying objects:

{
...
  "dc:modified": 
  {
    "@literal": "2010-05-29T14:17:39+02:00",
    "@datatype": "xsd:dateTime"
  }
...
}

Both examples above would generate an object with the literal value of 2010-05-29T14:17:39+02:00 and the datatype of http://www.w3.org/2001/XMLSchema#dateTime .

The third example uses a built-in native JSON type, a number, to express a datatype:

{
...
  "@subject": "http://example.org/people#joebob",
  "foaf:age": 31
...
}

The example above would generate the following triple:

<http://example.org/people#joebob> 
   <http://xmlns.com/foaf/0.1/age> 
"31"^^<http://www.w3.org/2001/XMLSchema#integer>
.

4.7 3.7 Multiple Objects for a Single Property

A JSON-LD author can express multiple triples in a compact way by using arrays. If a subject has multiple values for the same property, the author may express each property as an array.

In JSON-LD, Multiple objects on a property are not ordered. This is because typically graphs are not inherently ordered data structures. To see more on creating ordered collections in JSON-LD, see Lists .

{
...
  "@": "http://example.org/people#joebob",

  "@subject": "http://example.org/people#joebob",

  "foaf:nick": ["joe", "bob", "jaybee"],
...
}

The markup shown above would generate the following triples:

<http://example.org/people#joebob> 
   <http://xmlns.com/foaf/0.1/nick>
      "joe" .
<http://example.org/people#joebob> 
   <http://xmlns.com/foaf/0.1/nick>
      "bob" .
<http://example.org/people#joebob> 
   <http://xmlns.com/foaf/0.1/nick>
"jaybee"
.

4.8 3.8 Multiple Typed Literals for a Single Property

Multiple typed literal s may also be expressed using the expanded form for objects:

{
...
  "@": "http://example.org/articles/8",

  "@subject": "http://example.org/articles/8",

  "dcterms:modified": 
  [
    {
      "@literal": "2010-05-29T14:17:39+02:00",
      "@datatype": "xsd:dateTime"
    },
    {
      "@literal": "2010-05-30T09:21:28-04:00",
      "@datatype": "xsd:dateTime"
    }
  ]
...
}

The markup shown above would generate the following triples:

<http://example.org/articles/8> 
   <http://purl.org/dc/terms/modified>
      "2010-05-29T14:17:39+02:00"^^http://www.w3.org/2001/XMLSchema#dateTime .
<http://example.org/articles/8> 
   <http://purl.org/dc/terms/modified>
"2010-05-30T09:21:28-04:00"^^http://www.w3.org/2001/XMLSchema#dateTime
.

4.9 3.9 Blank Nodes Expansion

At times, it becomes necessary to be able to express information without being able Expansion is the process of taking a JSON-LD document and applying a context such that all IRI, datatypes, and literal values are expanded so that the context is no longer necessary. JSON-LD document expansion is typically used when re-mapping JSON-LD documents to specify application-specific JSON documents or as a part of the subject. Typically, this Normalization process.

For example, assume the following JSON-LD input document:

{
   "name": "Manu Sporny",
   "homepage": "http://manu.sporny.org/",
   "@context": 
   {
      "name": "http://xmlns.com/foaf/0.1/name",
      "homepage": "http://xmlns.com/foaf/0.1/homepage",
      "@coerce": 
      {
         "@iri": "homepage"
      }
   }
}

Running the JSON-LD Expansion algorithm against the JSON-LD input document provided above would result in the following output:

{
   "http://xmlns.com/foaf/0.1/name": "Manu Sporny",
   "http://xmlns.com/foaf/0.1/homepage": 
   {
      "@iri": "http://manu.sporny.org/"
   }
}

3.10 Compaction

Compaction is where blank nodes come into play. In JSON-LD, blank node identifiers the process of taking a JSON-LD document and applying a context such that the most compact form of the document is generated. JSON is typically expressed in a very compact, key-value format. That is, full IRIs are automatically created if rarely used as keys. At times, a subject JSON-LD document may be received that is not specified using in its most compact form. JSON-LD, via the @ keyword. However, authors may name blank nodes by using API, provides a way to compact a JSON-LD document.

For example, assume the special _ CURIE prefix. following JSON-LD input document:

{
...
  "@": "",
...

   "http://xmlns.com/foaf/0.1/name": "Manu Sporny",
   "http://xmlns.com/foaf/0.1/homepage": 
   {
      "@iri": "http://manu.sporny.org/"
   }

}

The example Additionally, assume the following developer-supplied JSON-LD context:

{
   "name": "http://xmlns.com/foaf/0.1/name",
   "homepage": "http://xmlns.com/foaf/0.1/homepage",
   "@coerce": 
   {
      "@iri": ["homepage"]
   }
}

Running the JSON-LD Compaction algorithm given the context supplied above against the JSON-LD input document provided above would set result in the subject following output:

{
   "name": "Manu Sporny",
   "homepage": "http://manu.sporny.org/",
   "@context": 
   {
      "name": "http://xmlns.com/foaf/0.1/name",
      "homepage": "http://xmlns.com/foaf/0.1/homepage",
      "@coerce": 
      {
         "@iri": "homepage"
      }
   }
}

The compaction algorithm also enables the developer to map any expanded format into an application-specific compacted format. While the context provided above mapped _:foo , which http://xmlns.com/foaf/0.1/name to name , it could have also mapped it to any arbitrary string provided by the developer.

3.11 Framing

A JSON-LD document is a representation of a directed graph. A single directed graph can have many different serializations, each expressing exactly the same information. Developers typically work with trees, also called associative arrays, when dealing with JSON. While mapping a graph to a tree can be done, the layout of the end result must be specified in advance. A Frame can then be used later by a developer on a JSON-LD document to specify a deterministic layout for a graph.

Framing is the process of taking a JSON-LD document, which expresses a graph of information, and applying a specific graph layout (called a Frame ).

The JSON-LD document below expresses a library, a book and a chapter:

{
   "@coerce": {
    "dc":  "http://purl.org/dc/terms/",
    "ex":  "http://example.org/"
   },
   "@subject": 
   [{
      "@subject": "http://example.org/library",
      "@type": "ex:Library",
      "ex:contains": "http://example.org/library/the-republic"
   }, 
   {
      "@subject": "http://example.org/library/the-republic",
      "@type": "ex:Book",
      "dc:creator": "Plato",
      "dc:title": "The Republic",
      "ex:contains": "http://example.org/library/the-republic#introduction"
   }, 
   {
      "@subject": "http://example.org/library/the-republic#introduction",
      "@type": "ex:Chapter",
      "dc:description": "An introductory chapter on The Republic.",
      "dc:title": "The Introduction"
   }],
   "@context": 
   {
      "@coerce": 
      {
         "@iri": "ex:contains"
      },
      "dc": "http://purl.org/dc/elements/1.1/",
      "ex": "http://example.org/vocab#"
   }
}

Developers typically like to operate on items in a hierarchical, tree-based fashion. Ideally, a developer would want the data above sorted into top-level libraries, then the books that are contained in each library, and then the chapters contained in each book. To achieve that layout, the developer can define the following frame :

{
   "@context": {
      "dc": "http://purl.org/dc/elements/1.1/",
      "ex": "http://example.org/vocab#"
   },
   "@type": "ex:Library",
   "ex:contains": {
      "@type": "ex:Book",
      "ex:contains": {
         "@type": "ex:Chapter"
      }
   }
}

When the framing algorithm is run against the previously defined JSON-LD markup document, paired with the frame above, the following JSON-LD document is the end result:

{
   "@context": 
   {
      "ex": "http://example.org/vocab#",
      "dc":  "http://purl.org/dc/terms/",
   }
   "@subject": "http://example.org/library",
   "@type": "ex:Library",
   "ex:contains": 
   {
      "@subject": "http://example.org/library/the-republic",
      "@type": "ex:Book",
      "dc:creator": "Plato",
      "dc:title": "The Republic",
      "ex:contains": 
      {
         "@subject": "http://example.org/library/the-republic#introduction",
         "@type": "ex:Chapter",
         "dc:description": "An introductory chapter on The Republic.",
         "dc:title": "The Introduction"
      },
   },
}

The JSON-LD framing algorithm allows developers to refer back query by example and force a specific tree layout to the named blank node. a JSON-LD document.

5.1 4.1 Automatic Typing

Since JSON is capable of expressing typed information such as doubles, integers, and boolean values. As demonstrated below, JSON-LD utilizes that information to create typed literal s:

{
...
  // The following two values are automatically converted to a type of xsd:double
  // and both values are equivalent to each other.
  "measure:cups": 5.3,
  "measure:cups": 5.3e0,
  // The following value is automatically converted to a type of xsd:double as well
  "space:astronomicUnits": 6.5e73,
  // The following value should never be converted to a language-native type
  "measure:stones": { "@literal": "4.8", "@datatype": "xsd:decimal" },
  // This value is automatically converted to having a type of xsd:integer
  "chem:protons": 12,
  // This value is automatically converted to having a type of xsd:boolean
  "sensor:active": true,
...
}

When dealing with a number of modern programming languages, including JavaScript ECMA-262, there is no distinction between xsd:decimal and xsd:double values. That is, the number 5.3 and the number 5.3e0 are treated as if they were the same. When converting from JSON-LD to a language-native format and back, datatype information is lost in a number of these languages. Thus, one could say that 5.3 is a xsd:decimal and 5.3e0 is an xsd:double in JSON-LD, but when both values are converted to a language-native format the datatype difference between the two is lost because the machine-level representation will almost always be a double . Implementers should be aware of this potential round-tripping issue between xsd:decimal and xsd:double . Specifically objects with a datatype of xsd:decimal must not be converted to a language native type.

5.2 4.2 Type Coercion

JSON-LD supports the coercion of types values to ensure that the zero-edit goal of JSON-LD can be accomplished. particular data types. Type coercion allows someone deploying JSON-LD to coerce and the incoming or outgoing types to the proper RDF data type based on a mapping of data type IRIs to RDF property types. Using type conversion, coercion, one may convert simple JSON data to properly typed RDF data.

The example below demonstrates how a JSON-LD author can coerce values to plain literal s, typed literal s and IRIs.

{
  "@context": 
  {  
     "rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#",
     "xsd": "http://www.w3.org/2001/XMLSchema#",
     "name": "http://xmlns.com/foaf/0.1/name",
     "age": "http://xmlns.com/foaf/0.1/age",
     "homepage": "http://xmlns.com/foaf/0.1/homepage",
     "@coerce":
     {
        "xsd:integer": "age",
        "xsd:anyURI": "homepage",

        "@iri": "homepage"

     }
  },
  "name": "John Smith",
  "age": "41",
  "homepage": "http://example.org/home/"
}

The example above would generate the following triples:

_:bnode1
   <http://xmlns.com/foaf/0.1/name>
      "John Smith" .
_:bnode1
   <http://xmlns.com/foaf/0.1/age>
      "41"^^http://www.w3.org/2001/XMLSchema#integer .
_:bnode1
   <http://xmlns.com/foaf/0.1/homepage>
<http://example.org/home/>
.

6. 4.3 The JSON-LD Processing Algorithm Chaining

The JSON-LD Processing Model describes processing rules for extracting RDF from Object chaining is a JSON-LD document. Note feature that many uses allows an author to use the definition of JSON-LD may not require generation of RDF. objects as property values. This is a commonly used mechanism for creating a parent-child relationship between two subject s.

The processing algorithm described in this section is provided in order to demonstrate how one might implement example shows an two subjects related by a JSON-LD processor. Conformant implementations are only required to produce the same type and number of triples during property from the output process and are not required to implement first subject:

{
...
  "foaf:name": "Manu Sporny",
  "foaf:knows": {
    "@type": "foaf:Person",
    "foaf:name": "Gregg Kellogg",
  }
...
}

An object definition, like the algorithm exactly one used above, may be used as described. The Processing Algorithm is a work JSON value at any point in progress. JSON-LD.

6.1 4.4 Overview Identifying Unlabeled Nodes

This section is non-normative. JSON-LD is intended At times, it becomes necessary to have an easy be able to parse grammar that closely models existing practice in using JSON for describing object representations. This allows express information without being able to specify the use subject. Typically, this type of existing libraries for parsing JSON in a document-oriented fashion, node is called an unlabeled node or can allow for stream-based parsing similar to SAX. As with other grammars used for describing linked data, a key concept is that of blank node. In JSON-LD, unlabeled node identifiers are automatically created if a resource . Resources subject is not specified using the @subject keyword. However, authors may be of three basic types: IRI s, for describing externally named entities, BNodes , resources provide identifiers for unlabeled nodes by using the special _ (underscore) CURIE prefix.

{
...
  "@subject": "_:foo",
...
}

The example above would set the subject to _:foo , which an external name does not exist, or can then be used later on in the JSON-LD markup to refer back to the unlabeled node. This practice, however, is not known, and Literals, which describe terminal entities such as strings, dates and other representations having usually frowned upon when generating Linked Data. If a lexical representation possibly including an explicit language or datatype. developer finds that they refer to the unlabeled node more than once, they should consider naming the node using a resolve-able IRI.

4.5 Overriding Keywords

Data described with JSON-LD may allows all of the syntax keywords, except for @context , to be considered overridden. This feature allows more legacy JSON content to be the representation of a graph made up of subject and object resources related via a predicate resource. However, specific implementations may choose supported by JSON-LD. It also allows developers to operate on design domain-specific implementations using only the document as JSON-LD context.

{
  "@context": 
  {  
     "url": "@subject",     "a": "@type",
     "name": "http://schema.org/name"
  },
  "url": "http://example.com/about#gregg",
  "a": "http://schema.org/Person",
  "name": "Gregg Kellogg"
}

In the example above, the @subject and @type keywords have been overridden by url and a normal JSON description of objects having attributes. , respectively.

6.2 4.6 Processing Algorithm Terms Normalization

Normalization is specified to the process of taking JSON-LD processing algorithm before processing begins. default graph input and performing a deterministic transformation on that input that results in a JSON-LD output that any conforming JSON-LD processor would have generated given the destination same input. The problem is a fairly difficult technical problem to solve because it requires a directed graph for to be ordered into a set of nodes and edges in a deterministic way. This is easy to do when all triples generated by JSON-LD markup. active subject of the currently active subject that nodes have unique names, but very difficult to do when some of the processor should use nodes are not labeled.

Normalization is useful when comparing two graphs against one another, when generating triples. active property the currently active property that the processor should use a detailed list of differences between two graphs, and when generating triples. active object the currently active object that the processor should use a cryptographic digital signature for information contained in a graph or when generating triples. active context a context that is used to resolve CURIEs while hash of the processing algorithm information contained in a graph.

The example below is running. an un-normalized JSON-LD document:

{
   "name": "Manu Sporny",
   "homepage": "http://manu.sporny.org/",
   "@context": 
   {
      "name": "http://xmlns.com/foaf/0.1/name",
      "homepage": "http://xmlns.com/foaf/0.1/homepage",
      "xsd": "http://www.w3.org/2001/XMLSchema#",
      "@coerce": 
      {
         "@iri": ["homepage"]
      }
   }
}

The active context example below is the context contained within normalized form of the processor state . local context a context that JSON-LD document above:

Whitespace is specified at the JSON associative-array level, specified via used below to aid readability. The normalization algorithm for JSON-LD remove all unnecessary whitespace in the @context keyword. processor state fully normalized form.

[{
    "@subject": 
    {
        "@iri": "_:c14n0"
    },
    "http://xmlns.com/foaf/0.1/homepage": 
    {
        "@iri": "http://manu.sporny.org/"
    },
    "http://xmlns.com/foaf/0.1/name": "Manu Sporny"
}]

Notice how all of the processor state , which includes term s have been expanded and sorted in alphabetical order. Also, notice how the active context , current subject , and current property . The processor state is managed as a stack has been labeled with elements from the previous processor state copied into a new processor state when entering a new associative array. blank node identifier . Normalization ensures that any arbitrary graph containing exactly the same information would be normalized to exactly the same form shown above.

6.3 5.1 Processing Syntax Tokens and Keywords

JSON-LD specifies a number of syntax tokens and keywords that are using in all algorithms described in this section:

@context

Used to set the local context .

@base

Used to set the base IRI for all object IRIs affected by the active context .

@profile A reference to a remote context description used to set the local context . @vocab

Used to set the base IRI for all property IRIs affected by the active context .

@coerce

Used to specify type coercion rules.

@literal

Used to specify a literal value.

@iri

Used to specify an IRI value.

@language

Used to specify the language for a literal.

@datatype

Used to specify the datatype for a literal.

:

The separator for CURIEs when used in JSON keys or JSON values.

@ @subject

Sets the active subjects.

a @type

Used to set the rdf:type type of the active subjects. This token may be conferred as syntactic sugar for rdf:type.

5.2 Algorithm Terms

initial context

a context that is specified to the algorithm before processing begins.

active subject

the currently active subject that the processor should use when processing.

active property

the currently active property that the processor should use when processing.

active object

the currently active object that the processor should use when processing.

active context

a context that is used to resolve CURIEs while the processing algorithm is running. The active context is the context contained within the processor state .

local context

a context that is specified at the JSON associative-array level, specified via the @type @context instead of keyword.

processor state

the processor state , which includes the active context , current subject , and current property . The processor state is managed as a ? Note stack with elements from the previous processor state copied into a new processor state when entering a new associative array.

JSON-LD input

The JSON-LD data structure that both are just semantic sugar for rdf:type . is provided as input to the algorithm.

JSON-LD output

The JSON-LD data structure that is produced as output by the algorithm.

6.4 5.3 Context

Processing of JSON-LD data structure is managed recursively using a process described in Sequence . recursively. During processing, each rule is applied using information provided by the active context . Processing begins by pushing a new processor state onto the processor state stack and initializing the active context with the default initial context . If a local context is encountered, information from the local context is merged into the active context .

The active context is used for expanding keys and values of an associative array (or elements of a list (see List Processing )).

A local context is identified within an associative array having a key of @context with string or an associative array value. When processing a local context , special processing rules apply:

1. The key Create a new, empty local context .
2. If the value is a simple string, it must have a lexical form of IRI and used to initialize a new JSON document which replaces the value for subsequent processing.
3. If the value is an associative array, perform the following steps:
   1. If the associative array has a @base key, it must have a value of a simple string with the lexical form of IRI and is saved in an absolute IRI. Add the active base mapping to the local context .

      Turtle allows @base to perform term mapping as described in be relative. If we did this, we would have to add IRI Processing Expansion .

   2. The key If the associative array has a @vocab key, it must have a value of a simple string with the lexical form of IRI and is saved in an absolute IRI. Add the active vocabulary mapping to the local context to perform term mapping as described in after performing IRI Processing . Expansion on the associated value.
   3. The key If the associative array has a @coerce key, it must have a value of an associative array. Processing of Add the associative array is described below @coerce mapping to the local context performing IRI Expansion on the associated value(s).
   4. Otherwise, the key must have the lexical form of NCName and must have the value of a simple string with the lexical form of IRI. Merge each the key-value pair into the active local context , overwriting any duplicate values. .
   A
4. Merge the of local context may also be loaded from an external document using 's @coerce mapping into the active context 's @profile @coerce key mapping as described in Vocabulary Profiles below .
5. Merge all entries other than the @coerce mapping from the local context to the active context overwriting any duplicate values.

{
...
  "foaf:name": "Manu Sporny",
  "": {
    "",
    "",
  }
...

    "@base": document-location,
    "@context": {
      "@iri": "@type"
    }

}

6.6 5.4 IRI Processing Expansion

Keys and some values are evaluated to produce an IRI. This section defines an algorithm for transforming a value representing an IRI into an actual IRI.

IRIs may be represented as an explicit string, or as a CURIE, as a value relative to @base or @vocab .

CURIEs are defined more formally in [ RDFA-CORE ] section 6 "CURIE Syntax Definition" . Generally, a CURIE is composed of a prefix and a suffix separated by a ':'. In JSON-LD, either the prefix may be the empty string, denoting the default prefix .

The procedure algorithm for generating an IRI is:

1. Split the value into a prefix and suffix from the first occurrence of ':'.
2. If the prefix is a '_', generate a named BNode using the suffix as '_' (underscore), the name. IRI is unchanged.
3. If the active context contains a mapping for prefix , generate an IRI by prepending the mapped prefix to the (possibly empty) suffix. suffix using textual concatenation. Note that an empty suffix and no suffix (meaning the value contains no ':' string at all) are treated equivalently.
4. If the IRI being processed is for a property (i.e., a key value in an associative array, or a value in a @coerce mapping) and the active context has a @vocab mapping, join the mapped value to the suffix using the method described in [ RFC3987 ]. textual concatenation.
5. If the IRI being processed is for a subject or object (i.e., not a property) and the active context has a @base mapping, join the mapped value to the suffix using the method described in [ RFC3987 RFC3986 ].
6. Otherwise, use the value directly as an IRI.

5.5 IRI Compaction

Some keys and values are expressed using IRIs. This section defines an algorithm for transforming an IRI to a compact IRI using the term s and prefix es specified in the local context .

The algorithm for generating a compacted IRI is:

1. Search every key-value pair in the active context for a term that is a complete match against the IRI. If a complete match is found, the resulting compacted IRI is the term associated with the IRI in the active context .
2. If a complete match is not found, search for a partial match from the beginning of the IRI. For all matches that are found, the resulting compacted IRI is the prefix associated with the partially matched IRI in the active context concatenated with a colon (:) character and the unmatched part of the string. If there is more than one compacted IRI produced, the final value is the lexicographically least value of the entire set of compacted IRIs.

7. 5.6 Sequence Value Expansion

Some values in JSON-LD can be expressed in a compact form. These values are required to be expanded at times when processing JSON-LD documents.

The algorithm for expanding a value is:

1. If the key that is associated with the value has an associated coercion entry in the local context , the resulting expansion is an object populated according to the following steps:
   1. If the coercion target is @iri , expand the value by adding a new key-value pair where the key is @iri and the value is the expanded IRI according to the IRI Expansion rules.
   2. If the coercion target is a typed literal, expand the value by adding two new key-value pairs. The first key-value pair will be @literal and the unexpanded value. The second key-value pair will be @datatype and the associated coercion datatype expanded according to the IRI Expansion rules.

5.7 Value Compaction

Some values, such as IRIs and typed literals, may be expressed in an expanded form in JSON-LD. These values are required to be compacted at times when processing JSON-LD documents.

The algorithm for compacting a value is:

1. If the local context contains a coercion target for the key that is associated with the value, compact the value using the following steps:
   1. If the coercion target is an @iri , the compacted value is the value associated with the @iri key, processed according to the IRI Compaction steps.
   2. If the coercion target is a typed literal, the compacted value is the value associated with the @literal key.
   3. Otherwise, the value is not modified.

5.8 Expansion

This algorithm is a work in progress, do not implement it.

As stated previously, expansion is the process of taking a JSON-LD input and expanding all IRIs and typed literals to their fully-expanded form. The output will not contain a single context declaration and will have all IRIs and typed literals fully expanded.

5.9 Compaction

This algorithm is a work in progress, do not implement it.

As stated previously, compaction is the process of taking a JSON-LD input and compacting all IRIs using a given context. The output will contain a single top-level context declaration and will only use term s and prefix es and will ensure that all typed literals are fully compacted.

5.10 Framing

This algorithm is a work in progress, do not implement it.

A JSON-LD document is a representation of a directed graph. A single directed graph can have many different serializations, each expressing exactly the same information. Developers typically don't work directly with graphs, but rather, prefer trees when dealing with JSON. While mapping a graph to a tree can be done, the layout of the end result must be specified in advance. This section defines an algorithm for mapping a graph to a tree given a frame .

5.11 Normalization

This algorithm is a work in progress, do not implement it.

Normalization is the process of taking JSON-LD input and performing a deterministic transformation on that input that results in all aspects of the graph being fully expanded and named in the JSON-LD output . The normalized output is generated in such a way that any conforming JSON-LD processor will generate identical output given the same input. The problem is a fairly difficult technical problem to solve because it requires a directed graph to be ordered into a set of nodes and edges in a deterministic way. This is easy to do when all of the nodes have unique names, but very difficult to do when some of the nodes are not labeled.

In time, there may be more than one normalization algorithm that will need to be identified. For identification purposes, this algorithm is named UGNA2011 .

5.12 Data Round Tripping

When normalizing xsd:double values, implementers must ensure that the normalized value is a string. In order to generate the string from a double value, output equivalent to the printf("%1.6e", value) function in C must be used where "%1.6e" is the string formatter and value is the value to be converted.

To convert the a double value in JavaScript, implementers can use the following snippet of code:

// the variable 'value' below is the JavaScript native double value that is to be converted
(value).toExponential(6).replace(/(e(?:\+|-))([0-9])$/,
'$10$2')

When data needs to be normalized, JSON-LD authors should not use values that are going to undergo automatic conversion. This is due to the lossy nature of xsd:double values.

Round-tripping data can be problematic if we mix and match @coerce rules with JSON-native datatypes, like integers. Consider the following code example:

var myObj = { "@context" : { 
                "number" : "http://example.com/vocab#number",
                "@coerce": {
                   "xsd:nonNegativeInteger": "number"
                }
              },
              "number" : 42 };
// Map the language-native object to JSON-LD
var jsonldText = jsonld.normalize(myObj);
// Convert the normalized object back to a JavaScript object
var
myObj2
=
jsonld.parse(jsonldText);

At this point, myObj2 and myObj will have different values for the "number" value. myObj will be the number 42, while myObj2 will be the string "42". This type of data round-tripping error can bite developers. We are currently wondering if having a "coerce validation" phase in the parsing/normalization phases would be a good idea. It would prevent data round-tripping issues like the one mentioned above.

5.13 RDF Conversion

A JSON-LD document may be converted to any other RDF-compatible document format using the algorithm specified in this section.

The JSON-LD Processing Model describes processing rules for extracting RDF from a JSON-LD document. Note that many uses of JSON-LD may not require generation of RDF.

The processing algorithm described in this section is provided in order to demonstrate how one might implement a JSON-LD to RDF processor. Conformant implementations are only required to produce the same type and number of triples during the output process and are not required to implement the algorithm exactly as described.

The RDF Conversion Algorithm is a work in progress.

9.2 6.1 Disjoint Graphs

When serializing an RDF graph that contains two or more sections of the graph which are entirely disjoint, one must use an array to express the graph as two graphs. This may not be acceptable to some authors, who would rather express the information as one graph. Since, by definition, disjoint graphs require there to be two top-level objects, JSON-LD utilizes a mechanism that allows disjoint graphs to be expressed using a single graph.

Assume the following RDF graph:

<http://example.org/people#john> 
   <http://www.w3.org/1999/02/22-rdf-syntax-ns#type>
      <http://xmlns.com/foaf/0.1/Person> .
<http://example.org/people#jane> 
   <http://www.w3.org/1999/02/22-rdf-syntax-ns#type>
<http://xmlns.com/foaf/0.1/Person>
.

Since the two subjects are entirely disjoint with one another, it is impossible to express the RDF graph above using a single JSON-LD associative array.

In JSON-LD, one can use the subject to express disjoint graphs as a single graph:

{
  "@": 

  "@coerce": {
    "foaf": "http://xmlns.com/foaf/0.1/"
  },
  "@subject": 

  [
    {
      "@": "http://example.org/people#john",
      "a": "foaf:Person"

      "@subject": "http://example.org/people#john",
      "@type": "foaf:Person"

    },
    {
      "@": "http://example.org/people#jane",
      "a": "foaf:Person"

      "@subject": "http://example.org/people#jane",
      "@type": "foaf:Person"

    }
  ]
}

A disjoint graph could also be expressed like so:

[
  {
    "@": "http://example.org/people#john",
    "a": "foaf:Person"

    "@subject": "http://example.org/people#john",
    "@type": "http://xmlns.com/foaf/0.1/Person"

  },
  {
    "@": "http://example.org/people#jane",
    "a": "foaf:Person"

    "@subject": "http://example.org/people#jane",
    "@type": "http://xmlns.com/foaf/0.1/Person"

  }
]

9.3 6.2 The JSON-LD API Lists

This API provides a clean mechanism that enables developers to convert JSON-LD data into a format that is easier to work with Because graphs do not describe ordering for links between nodes, multi-valued properties in various programming languages. JSON do not provide an ordering of the listed objects. For example, consider the following simple document:

{
...
  "@subject": "http://example.org/people#joebob",
  "foaf:nick": ["joe", "bob", "jaybee"],
...
}

This results in three triples being generated, each relating the data into subject to an Graph, which is compatible individual object, with the RDF Interfaces API specification no inherent order. To address this issue, RDF-based languages, such as [ RDF-INTERFACES TURTLE ]. This method will return null if there are any errors, or if ] use the RDF Interfaces API is not available for use. Parameter Type Nullable Optional Description jsonld concept of an DOMString rdf:List (as described in [ ✘ ✘ The JSON-LD string to parse into the RDFGraph. callback JSONLDParserCallback RDF-SCHEMA ✔ ✔ A callback that is called whenever ]). This uses a processing error occurs on the given JSON-LD string. No exceptions. Return type: Graph toProjection Parses sequence of unlabeled nodes with properties describing a value, a null-terminated next property. Without specific syntactical support, this could be represented in JSON-LD text into an RDF API Projection object as specified by follows:

{
...
  "@subject": "http://example.org/people#joebob",
  "foaf:nick": {,
    "@first": "joe",    "@rest": {      "@first": "bob",      "@rest": {        "@first": "jaybee",        "@rest": "@nil"        }      }    }  },
...
}

As this notation is rather unwieldy and the RDF API specification [ RDF-API ]. If there are any errors, null notion of ordered collections is returned. Parameter Type Nullable Optional Description jsonld DOMString ✘ ✘ The JSON-LD string rather important in data modeling, it is useful to parse into have specific language support. In JSON-LD, a list may be represented using the Projection. template object @list ✔ ✘ The Projection template to use when building keyword as follows:

{
...
  "@subject": "http://example.org/people#joebob",
  "foaf:nick": {"@list": ["joe", "bob", "jaybee"]},
...
}

This describes the Projection. subject DOMString ✔ ✘ The subject to use when building the Projection. callback JSONLDParserCallback ✔ ✔ A callback that of this array as being ordered, and order is called whenever maintained through normalization and RDF conversion. If every use of a processing error occurs on the given JSON-LD string. No exceptions. Return type: object The JSONLDParserCallback multi-valued property is called whenever a processing error occurs on input data. list, this may be abbreviated by adding an @coerce term:

{
  "@context": {
    ...
    "@context": {      "@list": ["foaf:nick"]    }  },
...
  "@subject": "http://example.org/people#joebob",
  "foaf:nick": ["joe", "bob", "jaybee"],
...
}