JSON is a useful data serialization and messaging format. This specification defines JSON-LD, a JSON-based format to serialize Linked Data. The syntax is designed to easily integrate into deployed systems that already use JSON, and provides a smooth upgrade path from JSON to JSON-LD. It is primarily intended to be a way to use Linked Data in Web-based programming environments, to build interoperable Web services, and to store Linked Data in JSON-based storage engines.

This document has been developed by the JSON-LD Working Group and was derived from the JSON-LD Community Group's Final Report.

There is a live JSON-LD playground that is capable of demonstrating the features described in this document.

Set of Documents

This document is one of three JSON-LD 1.1 Recommendations produced by the JSON-LD Working Group:

Introduction

Linked Data [[LINKED-DATA]] is a way to create a network of standards-based machine interpretable data across different documents and Web sites. It allows an application to start at one piece of Linked Data, and follow embedded links to other pieces of Linked Data that are hosted on different sites across the Web.

JSON-LD is a lightweight syntax to serialize Linked Data in JSON [[!RFC8259]]. Its design allows existing JSON to be interpreted as Linked Data with minimal changes. JSON-LD is primarily intended to be a way to use Linked Data in Web-based programming environments, to build interoperable Web services, and to store Linked Data in JSON-based storage engines. Since JSON-LD is 100% compatible with JSON, the large number of JSON parsers and libraries available today can be reused. In addition to all the features JSON provides, JSON-LD introduces:

JSON-LD is designed to be usable directly as JSON, with no knowledge of RDF [[RDF11-CONCEPTS]]. It is also designed to be usable as RDF, if desired, for use with other Linked Data technologies like SPARQL. Developers who require any of the facilities listed above or need to serialize an RDF Graph or Dataset in a JSON-based syntax will find JSON-LD of interest. People intending to use JSON-LD with RDF tools will find it can be used as another RDF syntax, as with [[Turtle]] and [[TriG]]. Complete details of how JSON-LD relates to RDF are in section .

The syntax is designed to not disturb already deployed systems running on JSON, but provide a smooth upgrade path from JSON to JSON-LD. Since the shape of such data varies wildly, JSON-LD features mechanisms to reshape documents into a deterministic structure which simplifies their processing.

How to Read this Document

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

A companion document, the JSON-LD 1.1 Processing Algorithms and API specification [[JSON-LD11-API]], specifies how to work with JSON-LD at a higher level by providing a standard library interface for common JSON-LD operations.

To understand the basics in this specification you must first be familiar with JSON, which is detailed in [[!RFC8259]].

This document almost exclusively uses the term IRI (Internationalized Resource Indicator) when discussing hyperlinks. Many Web developers are more familiar with the URL (Uniform Resource Locator) terminology. The document also uses, albeit rarely, the URI (Uniform Resource Indicator) terminology. While these terms are often used interchangeably among technical communities, they do have important distinctions from one another and the specification goes to great lengths to try and use the proper terminology at all times.

Contributing

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

Typographical conventions

Terminology

This document uses the following terms as defined in JSON [[!RFC8259]]. Refer to the JSON Grammar section in [[!RFC8259]] for formal definitions.

Design Goals and Rationale

JSON-LD satisfies the following design goals:

Simplicity
No extra processors or software libraries are necessary to use JSON-LD in its most basic form. The language provides developers with a very easy learning curve. Developers only need to know JSON and two keywords (@context and @id) to use the basic functionality in JSON-LD.
Compatibility
A JSON-LD document is always a valid JSON document. This ensures that all of the standard JSON libraries work seamlessly with JSON-LD documents.
Expressiveness
The syntax serializes directed graphs. This ensures that almost every real world data model can be expressed.
Terseness
The JSON-LD syntax is very terse and human readable, requiring as little effort as possible from the developer.
Zero Edits, most of the time
JSON-LD ensures a smooth and simple transition from existing JSON-based systems. In many cases, zero edits to the JSON document and the addition of one line to the HTTP response should suffice (see ). This allows organizations that have already deployed large JSON-based infrastructure to use JSON-LD's features in a way that is not disruptive to their day-to-day operations and is transparent to their current customers. However, there are times where mapping JSON to a graph representation is a complex undertaking. In these instances, rather than extending JSON-LD to support esoteric use cases, we chose not to support the use case. While Zero Edits is a design goal, it is not always possible without adding great complexity to the language. JSON-LD focuses on simplicity when possible.
Usable as RDF
JSON-LD is usable by developers as idiomatic JSON, with no need to understand RDF [[RDF11-CONCEPTS]]. JSON-LD is also usable as RDF, so people intending to use JSON-LD with RDF tools will find it can be used like any other RDF syntax. Complete details of how JSON-LD relates to RDF are in section .

Data Model Overview

Generally speaking, the data model described by a JSON-LD document is a labeled, directed graph. The graph contains nodes, which are connected by edges. A node is typically data such as a string, number, typed values (like dates and times) or an IRI.

Within a directed graph, nodes with may be unnamed, i.e., not identified by an IRI or representing data such as strings or numbers. Such nodes are called blank nodes, and may be identified using a blank node identifier. These identifiers may be required to represent a fully connected graph using a tree structure, such as JSON, but otherwise have no intrinsic meaning.

This simple data model is incredibly flexible and powerful, capable of modeling almost any kind of data. For a deeper explanation of the data model, see section .

Developers who are familiar with Linked Data technologies will recognize the data model as the RDF Data Model. To dive deeper into how JSON-LD and RDF are related, see section .

At the surface level, a JSON-LD document is simply JSON, detailed in [[!RFC8259]]. For the purpose of describing the core data structures, this is limited to arrays, dictionaries (the parsed version of a JSON Object), strings, numbers, booleans, and null, called the JSON-LD internal representation. This allows surface syntaxes other than JSON to be manipulated using the same algorithms, when the syntax maps to equivalent core data structures.

Although not discussed in this specification, parallel work using YAML [[YAML]] and binary representations such as CBOR [[RFC7049]] could be used to map into the internal representation, allowing the JSON-LD 1.1 API [[JSON-LD11-API]] to operate as if the source was a JSON document.

Syntax Tokens and Keywords

JSON-LD specifies a number of syntax tokens and keywords that are a core part of the language:

@context
Used to define the short-hand names that are used throughout a JSON-LD document. These short-hand names are called terms and help developers to express specific identifiers in a compact manner. The @context keyword is described in detail in .
@id
Used to uniquely identify node objects that are being described in the document with IRIs or blank node identifiers. This keyword is described in .
@value
Used to specify the data that is associated with a particular property in the graph. This keyword is described in and .
@language
Used to specify the language for a particular string value or the default language of a JSON-LD document. This keyword is described in .
@type
Used to set the data type of a node or typed value. This keyword is described in .
@container
Used to set the default container type for a term. This keyword is described in the following sections:
  • ,
  • ,
  • ,
  • ,
  • ,
  • , and
@list
Used to express an ordered set of data. This keyword is described in .
@set
Used to express an unordered set of data and to ensure that values are always represented as arrays. This keyword is described in .
@reverse
Used to express reverse properties. This keyword is described in .
@index
Used to specify that a container is used to index information and that processing should continue deeper into a JSON data structure. This keyword is described in .
@base
Used to set the base IRI against which to resolve those relative IRIs interpreted relative to the document. This keyword is described in .
@vocab
Used to expand properties and values in @type with a common prefix IRI. This keyword is described in .
@graph
Used to express a graph. This keyword is described in .
@nest
Collects a set of nested properties within a node object.
@none
Used as an index value in an id map, language map, type map, or elsewhere where a dictionary is used to index into other values.
@prefix
With the value true, allows this term to be used to construct a compact IRI when compacting.
@version
Used in a context definition to set the processing mode. New features since JSON-LD 1.0 [[!JSON-LD]] described in this specification are only available when processing mode has been explicitly set to json-ld-1.1.
:
The separator for JSON keys and values that use compact IRIs.

All keys, keywords, and values in JSON-LD are case-sensitive.

Conformance criteria are relevant to authors and authoring tool implementers. As well as sections marked as non-normative, all authoring guidelines, diagrams, examples, and notes in this specification are non-normative. Everything else in this specification is normative.

A JSON-LD document complies with this specification if it follows the normative statements in appendix . JSON documents can be interpreted as JSON-LD by following the normative statements in . For convenience, normative statements for documents are often phrased as statements on the properties of the document.

This specification makes use of the following namespace prefixes:

Prefix IRI
dc http://purl.org/dc/terms/
cred https://w3id.org/credentials#
foaf http://xmlns.com/foaf/0.1/
geojson https://purl.org/geojson/vocab#
prov http://www.w3.org/ns/prov#
rdf http://www.w3.org/1999/02/22-rdf-syntax-ns#
schema http://schema.org/
skos http://www.w3.org/2004/02/skos/core#
xsd http://www.w3.org/2001/XMLSchema#

These are used within this document as part of a compact IRI as a shorthand for the resulting absolute IRI, such as dc:title used to represent http://purl.org/dc/terms/title.

Basic Concepts

JSON [[RFC8259]] is a lightweight, language-independent data interchange format. It is easy to parse and easy to generate. However, it is difficult to integrate JSON from different sources as the data may contain keys that conflict with other data sources. Furthermore, JSON has no built-in support for hyperlinks, which are a fundamental building block on the Web. Let's start by looking at an example that we will be using for the rest of this section:

  
  

It's obvious to humans that the data is about a person whose name is "Manu Sporny" and that the homepage property contains the URL of that person's homepage. A machine doesn't have such an intuitive understanding and sometimes, even for humans, it is difficult to resolve ambiguities in such representations. This problem can be solved by using unambiguous identifiers to denote the different concepts instead of tokens such as "name", "homepage", etc.

Linked Data, and the Web in general, uses IRIs (Internationalized Resource Identifiers as described in [[!RFC3987]]) for unambiguous identification. The idea is to use IRIs to assign unambiguous identifiers to data that may be of use to other developers. It is useful for terms, like name and homepage, to expand to IRIs so that developers don't accidentally step on each other's terms. Furthermore, developers and machines are able to use this IRI (by using a web browser, for instance) to go to the term and get a definition of what the term means. This process is known as IRI dereferencing.

Leveraging the popular schema.org vocabulary, the example above could be unambiguously expressed as follows:

In the example above, every property is unambiguously identified by an IRI and all values representing IRIs are explicitly marked as such by the @id keyword. While this is a valid JSON-LD document that is very specific about its data, the document is also overly verbose and difficult to work with for human developers. To address this issue, JSON-LD introduces the notion of a context as described in the next section.

The Context

When two people communicate with one another, the conversation takes place in a shared environment, typically called "the context of the conversation". This shared context allows the individuals to use shortcut terms, like the first name of a mutual friend, to communicate more quickly but without losing accuracy. A context in JSON-LD works in the same way. It allows two applications to use shortcut terms to communicate with one another more efficiently, but without losing accuracy.

Simply speaking, a context is used to map terms to IRIs. Terms are case sensitive and any valid string that is not a reserved JSON-LD keyword can be used as a term.

For the sample document in the previous section, a context would look something like this:

    
    

As the context above shows, the value of a term definition can either be a simple string, mapping the term to an IRI, or a dictionary.

When a when a member with a term key has a dictionary value, the dictionary is called an expanded term definition. The example above specifies that the values of image and homepage, if they are strings, are to be interpreted as IRIs. Expanded term definitions also allow terms to be used for index maps and to specify whether array values are to be interpreted as sets or lists. Expanded term definitions may be defined using absolute or compact IRIs as keys, which is mainly used to associate type or language information with an absolute or compact IRI.

Contexts can either be directly embedded into the document or be referenced. Assuming the context document in the previous example can be retrieved at https://json-ld.org/contexts/person.jsonld, it can be referenced by adding a single line and allows a JSON-LD document to be expressed much more concisely as shown in the example below:

The referenced context not only specifies how the terms map to IRIs in the Schema.org vocabulary but also specifies that string values associated with the homepage and image property can be interpreted as an IRI ("@type": "@id", see for more details). This information allows developers to re-use each other's data without having to agree to how their data will interoperate on a site-by-site basis. External JSON-LD context documents may contain extra information located outside of the @context key, such as documentation about the terms declared in the document. Information contained outside of the @context value is ignored when the document is used as an external JSON-LD context document.

JSON documents can be interpreted as JSON-LD without having to be modified by referencing a context via an HTTP Link Header as described in . It is also possible to apply a custom context using the JSON-LD 1.1 API [[JSON-LD11-API]].

In JSON-LD documents, contexts may also be specified inline. This has the advantage that documents can be processed even in the absence of a connection to the Web. Ultimately, this is a modeling decision and different use cases may require different handling.

This section only covers the most basic features of the JSON-LD Context. The Context can also be used to help interpret other more complex JSON data structures, such as indexed values, ordered values, and nested properties. More advanced features related to the JSON-LD Context are covered in section .

IRIs

IRIs (Internationalized Resource Identifiers [[!RFC3987]]) are fundamental to Linked Data as that is how most nodes and properties are identified. In JSON-LD, IRIs may be represented as an absolute IRI or a relative IRI. An absolute IRI is defined in [[!RFC3987]] as containing a scheme along with path and optional query and fragment segments. A relative IRI is an IRI that is relative to some other absolute IRI. In JSON-LD, with exceptions are as described below, all relative IRIs are resolved relative to the base IRI.

Properties, values of @type, and values of properties with a term definition that defines them as being relative to the vocabulary mapping, may have the form of a relative IRI, but are resolved using the vocabulary mapping, and not the base IRI.

A string is interpreted as an IRI when it is the value of an dictionary member with the key@id:

  
  

Values that are interpreted as IRIs, can also be expressed as relative IRIs. For example, assuming that the following document is located at http://example.com/about/, the relative IRI ../ would expand to http://example.com/ (for more information on where relative IRIs can be used, please refer to section ).

  
  

Absolute IRIs can be expressed directly in the key position like so:

  
  

In the example above, the key http://schema.org/name is interpreted as an absolute IRI.

Term-to-IRI expansion occurs if the key matches a term defined within the active context:

JSON keys that do not expand to an IRI, such as status in the example above, are not Linked Data and thus ignored when processed.

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

In the example above, since the value http://manu.sporny.org/ is expressed as a JSON string, the type coercion rules will transform the value into an IRI when processing the data. See for more details about this feature.

In summary, IRIs can be expressed in a variety of different ways in JSON-LD:

  1. Dictionary members that have a key mapping to a term in the active context expand to an IRI (only applies outside of the context definition).
  2. An IRI is generated for the string value specified using @id or @type.
  3. An IRI is generated for the string value of any key for which there are coercion rules that contain an @type key that is set to a value of @id or @vocab.

This section only covers the most basic features associated with IRIs in JSON-LD. More advanced features related to IRIs are covered in section .

Node Identifiers

To be able to externally reference nodes in a graph, it is important that nodes have an identifier. IRIs are a fundamental concept of Linked Data, for nodes to be truly linked, dereferencing the identifier should result in a representation of that node. This may allow an application to retrieve further information about a node.

In JSON-LD, a node is identified using the @id keyword:

The example above contains a node object identified by the IRI http://me.markus-lanthaler.com/.

This section only covers the most basic features associated with node identifiers in JSON-LD. More advanced features related to node identifiers are covered in section .

Specifying the Type

In Linked Data, it is common to specify the type of a graph node; in many cases, this can be inferred based on the properties used within a given node object, or the property for which a node is a value. For example, in the schema.org vocabulary, the givenName property is associated with a Person. Therefore, one may reason that if a node object contains the property firstName, that the type is a Person; making this explicit with @type helps to clarify the association.

The type of a particular node can be specified using the @type keyword. In Linked Data, types are uniquely identified with an IRI.

A node can be assigned more than one type by using an array:

The value of an @type key may also be a term defined in the active context:

This section only covers the most basic features associated with types in JSON-LD. It is worth noting that the @type keyword is not only used to specify the type of a node but also to express typed values (as described in ) and to type coerce values (as described in ). Specifically, @type cannot be used in a context to define a node's type. For a detailed description of the differences, please refer to .

Advanced Concepts

JSON-LD has a number of features that provide functionality above and beyond the core functionality described above. JSON can be used to express data using such structures, and the features described in this section can be used to interpret a variety of different JSON structures as Linked Data. A JSON-LD processor will make use of provided and embedded contexts to interpret property values in a number of different idiomatic ways.

Describing values

One pattern in JSON is for the value of a property to be a string. Often times, this string actually represents some other typed value, for example an IRI, a date, or a string in some specific language. See for details on how to describe such value typing.

Value ordering

In JSON, a property with an array value implies an implicit order; arrays in JSON-LD do not provide an ordering of the contained elements by default, unless defined using embedded structures or through a context definition. See for a further discussion.

Property nesting

Another JSON idiom often found in APIs is to use an intermediate object to represent the properties of an object; in JSON-LD these are refered to as nested properties and are described in .

Referencing objects

Linked Data is all about describing the relationships between different resources. Sometimes these relationships are between resources defined in different documents described on the web, sometimes the resources are described within the same document.

In this case, a document residing at http://manu.sporny.org/about may contain the example above, and reference another document at http://greggkellogg.net/foaf which could include a similar representation.

A common idiom found in JSON usage is objects being specified as the value of other objects, called object embedding in JSON-LD; for example, a friend specified as an object value of a Person:

See details these relationships.

Indexed values

Another common idiom in JSON is to use an intermediate object to represent property values via indexing. JSON-LD allows data to be indexed in a number of different ways, as detailed in .

Reverse Properties

JSON-LD serializes directed graphs. That means that every property points from a node to another node or value. However, in some cases, it is desirable to serialize in the reverse direction, as detailed in .

The following sections describe such advanced functionality in more detail.

Advanced Context Usage

Section introduced the basics of what makes JSON-LD work. This section expands on the basic principles of the context and demonstrates how more advanced use cases can be achieved using JSON-LD.

In general, contexts may be used any time a dictionary is defined. The only time that one cannot express a context is as a direct child of another context definition (other than as part of an expanded term definition). For example, a JSON-LD document may use more than one context at different points in a document:

Duplicate context terms are overridden using a most-recently-defined-wins mechanism.

In the example above, the name term is overridden in the more deeply nested details structure. Note that this is rarely a good authoring practice and is typically used when working with legacy applications that depend on a specific structure of the dictionary. If a term is redefined within a context, all previous rules associated with the previous definition are removed. If a term is redefined to null, the term is effectively removed from the list of terms defined in the active context.

Multiple contexts may be combined using an array, which is processed in order. The set of contexts defined within a specific dictionary are referred to as local contexts. The active context refers to the accumulation of local contexts that are in scope at a specific point within the document. Setting a local context to null effectively resets the active context to an empty context, without term definitions, default language, or other things defined within previous contexts. The following example specifies an external context and then layers an embedded context on top of the external context:

When possible, the context definition should be put at the top of a JSON-LD document. This makes the document easier to read and might make streaming parsers more efficient. Documents that do not have the context at the top are still conformant JSON-LD.

To avoid forward-compatibility issues, terms starting with an @ character are to be avoided as they might be used as keyword in future versions of JSON-LD. Terms starting with an @ character that are not JSON-LD 1.1 keywords are treated as any other term, i.e., they are ignored unless mapped to an IRI. Furthermore, the use of empty terms ("") is not allowed as not all programming languages are able to handle empty JSON keys.

JSON-LD 1.1 Processing Mode

New features defined in JSON-LD 1.1 are available when the processing mode is set to json-ld-1.1. This may be set using the @version member in a context set to the value 1.1 as a number, or through an API option.

  
  

The first context encountered when processing a document which contains @version determines the processing mode, unless it is defined explicitly through an API option.

Setting the processing mode explicitly for JSON-LD 1.1 is necessary so that a JSON-LD 1.0 processor does not attempt to process a JSON-LD 1.1 document and silently produce different results.

Default Vocabulary

At times, all properties and types may come from the same vocabulary. JSON-LD's @vocab keyword allows an author to set a common prefix which is used as the vocabulary mapping and is used for all properties and types that do not match a term and are neither a compact IRI nor an absolute IRI (i.e., they do not contain a colon).

If @vocab is used but certain keys in an dictionary should not be expanded using the vocabulary IRI, a term can be explicitly set to null in the context. For instance, in the example below the databaseId member would not expand to an IRI causing the property to be dropped when expanding.

Using the Document Base as the Default Vocabulary

In some cases, vocabulary terms are defined directly within the document itself, rather than in an external vocabulary. Since json-ld-1.1, the vocabulary mapping in the active context can be set to the empty string "", which causes terms which are expanded relative to the vocabulary, such as the keys of node objects, to use the base IRI to create absolute IRIs.

  
  

If this document were located at http://example/document, it would expand as follows:

Base IRI

JSON-LD allows IRIs to be specified in a relative form which is resolved against the document base according section 5.1 Establishing a Base URI of [[RFC3986]]. The base IRI may be explicitly set with a context using the @base keyword.

For example, if a JSON-LD document was retrieved from http://example.com/document.jsonld, relative IRIs would resolve against that IRI:

    
  

This document uses an empty @id, which resolves to the document base. However, if the document is moved to a different location, the IRI would change. To prevent this without having to use an absolute IRI, a context may define an @base mapping, to overwrite the base IRI for the document.

Setting @base to null will prevent relative IRIs from being expanded to absolute IRIs.

Please note that the @base will be ignored if used in external contexts.

Compact IRIs

A compact IRI is a way of expressing an IRI using a prefix and suffix separated by a colon (:). The prefix is a term taken from the active context and is a short string identifying a particular IRI in a JSON-LD document. For example, the prefix foaf may be used as a short hand for the Friend-of-a-Friend vocabulary, which is identified using the IRI http://xmlns.com/foaf/0.1/. A developer may append any of the FOAF vocabulary terms to the end of the prefix to specify a short-hand version of the absolute IRI for the vocabulary term. For example, foaf:name would be expanded to the IRI http://xmlns.com/foaf/0.1/name.

In the example above, foaf:name expands to the IRI http://xmlns.com/foaf/0.1/name and foaf:Person expands to http://xmlns.com/foaf/0.1/Person.

Prefixes are expanded when the form of the value is a compact IRI represented as a prefix:suffix combination, the prefix matches a term defined within the active context, and the suffix does not begin with two slashes (//). The compact IRI is expanded by concatenating the IRI mapped to the prefix to the (possibly empty) suffix. If the prefix is not defined in the active context, or the suffix begins with two slashes (such as in http://example.com), the value is interpreted as absolute IRI instead. If the prefix is an underscore (_), the value is interpreted as blank node identifier instead.

It's also possible to use compact IRIs within the context as shown in the following example:

In JSON-LD 1.0, terms may be chosen as compact IRI prefixes when compacting only if a simple term definition is used where the value ends with a URI gen-delim character (e.g, /, # and others, see [[!RFC3986]]). The previous specification allows any term to be chosen as a compact IRI prefix, which led to a poor experience.

In JSON-LD 1.1, terms may be chosen as compact IRI prefixes when compacting only if a simple term definition is used where the value ends with a URI gen-delim character, or if their expanded term definition contains a @prefix member with the value true.

This represents a small change to the 1.0 algorithm to prevent IRIs that are not really intended to be used as prefixes from being used for creating compact IRIs.

When processing mode is set to json-ld-1.1, terms will be used as compact IRI prefixes when compacting only if their expanded term definition contains a @prefix member with the value true, or if it has a a simple term definition where the value ends with a URI gen-delim character (e.g, /, # and others, see [[!RFC3986]]).

In this case, the compact-iris term would not normally be usable as a prefix, both because it is defined with an expanded term definition, and because it's @id does not end in a gen-delim character. Adding "@prefix": true allows it to be used as the prefix portion of the compact IRI compact-iris:are-considered.

Aliasing Keywords

Each of the JSON-LD keywords, except for @context, may be aliased to application-specific keywords. This feature allows legacy JSON content to be utilized by JSON-LD by re-using JSON keys that already exist in legacy documents. This feature also allows developers to design domain-specific implementations using only the JSON-LD context.

In the example above, the @id and @type keywords have been given the aliases url and a, respectively.

Since keywords cannot be redefined, they can also not be aliased to other keywords.

Aliased keywords may not be used within a context, itself.

IRI Expansion within a Context

In general, normal IRI expansion rules apply anywhere an IRI is expected (see ). Within a context definition, this can mean that terms defined within the context may also be used within that context as long as there are no circular dependencies. For example, it is common to use the xsd namespace when defining typed values:


In this example, the xsd term is defined and used as a prefix for the @type coercion of the age property.

Terms may also be used when defining the IRI of another term:


Compact IRIs and IRIs may be used on the left-hand side of a term definition.


In this example, the compact IRI form is used in two different ways. In the first approach, foaf:age declares both the IRI for the term (using short-form) as well as the @type associated with the term. In the second approach, only the @type associated with the term is specified. The full IRI for foaf:homepage is determined by looking up the foaf prefix in the context.

Absolute IRIs may also be used in the key position in a context:


In order for the absolute IRI to match above, the absolute IRI needs to be used in the JSON-LD document. Also note that foaf:homepage will not use the { "@type": "@id" } declaration because foaf:homepage is not the same as http://xmlns.com/foaf/0.1/homepage. That is, terms are looked up in a context using direct string comparison before the prefix lookup mechanism is applied.

While it is possible to define a compact IRI, or an absolute IRI to expand to some other unrelated IRI (for example, foaf:name expanding to http://example.org/unrelated#species), such usage is strongly discouraged.

The only exception for using terms in the context is that circular definitions are not allowed. That is, a definition of term1 cannot depend on the definition of term2 if term2 also depends on term1. For example, the following context definition is illegal:


Scoped Contexts

An expanded term definition can include a @context property, which defines a context (an embedded context) for values of properties defined using that term. This allows values to use term definitions, base IRI, vocabulary mapping or default language which is different from the node object they are contained in, as if the context was specified within the value itself.

In this case, the social profile is defined using the schema.org vocabulary, but interest is imported from FOAF, and is used to define a node describing one of Manu's interests where those properties now come from the FOAF vocabulary.

Expanding this document, uses a combination of terms defined in the outer context, and those defined specifically for that term in an embedded context.

Scoping can also be performed using a term used as a value of @type:

Scoping on @type is useful when common properties are used to relate things of different types, where the vocabularies in use within different entities calls for different context scoping. For example, hasPart/partOf may be common terms used in a document, but mean different things depending on the context.

When expanding, each value of @type is considered (ordering them lexographically) where that value is also a term in the active context having its own embedded context. If so, that embedded context is applied to the active context. When compacting, if a term is chosen to represent an IRI used as a value of @type where that term definition also has an embedded context, it is then applied to the active context to affect further compaction.

The values of @type are unordered, so if multiple types are listed, the order that scoped contexts are applied is based on lexicographical ordering.

If a term defines a scoped context, and then that term is later re-defined, the association of the context defined in the earlier expanded term definition is lost within the scope of that re-definition. This is consistent with term definitions of a term overriding previous term definitions from earlier less deeply nested definitions, as discussed in .

Scoped Contexts are a new feature in JSON-LD 1.1, requiring processing mode set to json-ld-1.1.

Describing Values

Values are leaf nodes in a graph associated with scalar values such as strings, dates, times, and other such atomic values.

Typed Values

A value with an associated type, also known as a typed value, is indicated by associating a value with an IRI which indicates the value's type. Typed values may be expressed in JSON-LD in three ways:

  1. By utilizing the @type keyword when defining a term within an @context section.
  2. By utilizing a value object.
  3. By using a native JSON type such as number, true, or false.

The first example uses the @type keyword to associate a type with a particular term in the @context:

The modified key's value above is automatically type coerced to a dateTime value because of the information specified in the @context. The example tabs show how a JSON-LD processor will interpret the data.

The second example uses the expanded form of setting the type information in the body of a JSON-LD document:

Both examples above would generate the value 2010-05-29T14:17:39+02:00 with the type http://www.w3.org/2001/XMLSchema#dateTime. Note that it is also possible to use a term or a compact IRI to express the value of a type.

The @type keyword is also used to associate a type with a node. The concept of a node type and a value type are different.

A node type specifies the type of thing that is being described, like a person, place, event, or web page. A value type specifies the data type of a particular value, such as an integer, a floating point number, or a date.


The first use of @type associates a node type (http://schema.org/BlogPosting) with the node, which is expressed using the @id keyword. The second use of @type associates a value type (http://www.w3.org/2001/XMLSchema#dateTime) with the value expressed using the @value keyword. As a general rule, when @value and @type are used in the same dictionary, the @type keyword is expressing a value type. Otherwise, the @type keyword is expressing a node type. The example above expresses the following data:

Type Coercion

JSON-LD supports the coercion of string values to particular data types. Type coercion allows someone deploying JSON-LD to use string property values and have those values be interpreted as typed values by associating an IRI with the value in the expanded value object representation. Using type coercion, string value representation can be used without requiring the data type to be specified explicitly with each piece of data.

Type coercion is specified within an expanded term definition using the @type key. The value of this key expands to an IRI. Alternatively, the keyword @id or @vocab may be used as value to indicate that within the body of a JSON-LD document, a string value of a term coerced to @id or @vocab is to be interpreted as an IRI. The difference between @id and @vocab is how values are expanded to absolute IRIs. @vocab first tries to expand the value by interpreting it as term. If no matching term is found in the active context, it tries to expand it as compact IRI or absolute IRI if there's a colon in the value; otherwise, it will expand the value using the active context's vocabulary mapping, if present. Values coerced to @id in contrast are expanded as compact IRI or absolute IRI if a colon is present; otherwise, they are interpreted as relative IRI.

Terms or compact IRIs used as the value of a @type key may be defined within the same context. This means that one may specify a term like xsd and then use xsd:integer within the same context definition.

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

Terms may also be defined using absolute IRIs or compact IRIs. This allows coercion rules to be applied to keys which are not represented as a simple term. For example:

In this case the @id definition in the term definition is optional. If it does exist, the compact IRI or IRI representing the term will always be expanded to IRI defined by the @id key—regardless of whether a prefix is defined or not.

Type coercion is always performed using the unexpanded value of the key. In the example above, that means that type coercion is done looking for foaf:age in the active context and not for the corresponding, expanded IRI http://xmlns.com/foaf/0.1/age.

Keys in the context are treated as terms for the purpose of expansion and value coercion. At times, this may result in multiple representations for the same expanded IRI. For example, one could specify that dog and cat both expanded to http://example.com/vocab#animal. Doing this could be useful for establishing different type coercion or language specification rules. It also allows a compact IRI (or even an absolute IRI) to be defined as something else entirely. For example, one could specify that the term http://example.org/zoo should expand to http://example.org/river, but this usage is discouraged because it would lead to a great deal of confusion among developers attempting to understand the JSON-LD document.

String Internationalization

At times, it is important to annotate a string with its language. In JSON-LD this is possible in a variety of ways. First, it is possible to define a default language for a JSON-LD document by setting the @language key in the context:

The example above would associate the ja language code with the two strings 花澄 and 科学者. Languages codes are defined in [[!BCP47]]. The default language applies to all string values that are not type coerced.

To clear the default language for a subtree, @language can be set to null in a local context as follows:

  
  

Second, it is possible to associate a language with a specific term using an expanded term definition:

  
  

The example above would associate 忍者 with the specified default language code ja, Ninja with the language code en, and Nindža with the language code cs. The value of name, Yagyū Muneyoshi wouldn't be associated with any language code since @language was reset to null in the expanded term definition.

Language associations are only applied to plain strings. Typed values or values that are subject to type coercion are not language tagged.

Just as in the example above, systems often need to express the value of a property in multiple languages. Typically, such systems also try to ensure that developers have a programmatically easy way to navigate the data structures for the language-specific data. In this case, language maps may be utilized.

  
  

The example above expresses exactly the same information as the previous example but consolidates all values in a single property. To access the value in a specific language in a programming language supporting dot-notation accessors for object properties, a developer may use the property.language pattern. For example, to access the occupation in English, a developer would use the following code snippet: obj.occupation.en.

Third, it is possible to override the default language by using a value object:

  
  

This makes it possible to specify a plain string by omitting the @language tag or setting it to null when expressing it using a value object:

  
  

See for a description of using language maps to set the language of mapped values.

Value Ordering

A JSON-LD author can express multiple values in a compact way by using arrays. Since graphs do not describe ordering for links between nodes, arrays in JSON-LD do not provide an ordering of the contained elements by default. This is exactly the opposite from regular JSON arrays, which are ordered by default. For example, consider the following simple document:

Multiple values may also be expressed using the expanded form:

The example shown above would generates statement, again with no inherent order.

Although multiple values of a property are typically of the same type, JSON-LD places no restriction on this, and a property may have values of different types:

When viewed as statements, the values have no inherent order.

Lists

As the notion of ordered collections is rather important in data modeling, it is useful to have specific language support. In JSON-LD, a list may be represented using the @list keyword as follows:

This describes the use of this array as being ordered, and order is maintained when processing a document. If every use of a given multi-valued property is a list, this may be abbreviated by setting @container to @list in the context:

The implementation of lists in RDF depends on linking anonymous nodes together using the properties rdf:first and rdf:rest, with the end of the list defined as the resource rdf:nil. This can be represented as statments, as the "statements" tab illustrates.

Both JSON-LD and Turtle provide shortcuts for representing ordered lists.

In JSON-LD 1.1, lists of lists, where the value of a list object, may itself be a list object, are fully supported. For example, in GeoJSON (see [[RFC7946]]), coordinates are an ordered list of positions, which are represented as an array of two or more numbers:

{
  "type": "Feature",
  "bbox": [-10.0, -10.0, 10.0, 10.0],
  "geometry": {
    "type": "Polygon",
    "coordinates": [
        [
            [-10.0, -10.0],
            [10.0, -10.0],
            [10.0, 10.0],
            [-10.0, -10.0]
        ]
    ]
  }
  ####//...####
}

For these examples, it's important that values expressed within bbox and coordinates maintain their order, which requires the use of embedded list structures. In JSON-LD 1.1, we can express this using recursive lists, by simply adding the appropriate context definion:

Note that coordinates includes three levels of lists.

Values of terms associated with an @list container are always represented in the form of an array, even if there is just a single value or no value at all.

Sets

While @list is used to describe ordered lists, the @set keyword is used to describe unordered sets. The use of @set in the body of a JSON-LD document is optimized away when processing the document, as it is just syntactic sugar. However, @set is helpful when used within the context of a document. Values of terms associated with an @set container are always represented in the form of an array, even if there is just a single value that would otherwise be optimized to a non-array form in compact form (see ). This makes post-processing of JSON-LD documents easier as the data is always in array form, even if the array only contains a single value.

This describes the use of this array as being unordered, and order is maintained when processing a document. By default, arrays of values are unordered, but this may be made explicit by setting @container to @set in the context:

Since JSON-LD 1.1, the @set keyword may be combined with other container specifications within an expanded term definition to similarly cause compacted values of indexes to be consistently represented using arrays. See for a further discussion.

Nested Properties

Many JSON APIs separate properties from their entities using an intermediate object; in JSON-LD these are called nested properties. For example, a set of possible labels may be grouped under a common property:

By defining labels using the keyword @nest, a JSON-LD processor will ignore the nesting created by using the labels property and process the contents as if it were declared directly within containing object. In this case, the labels property is semantically meaningless. Defining it as equivalent to @nest causes it to be ignored when expanding, making it equivalent to the following:

Similarly, node objects may contain a @nest property to reference a term aliased to @nest which causes such values to be nested under that aliased term.

Nested properties are a new feature in JSON-LD 1.1, requiring processing mode set to json-ld-1.1.

Embedding

Embedding is a JSON-LD feature that allows an author to use node objects as property values. This is a commonly used mechanism for creating a parent-child relationship between two nodes.

Without embedding, node objects can be linked by referencing the identifier of another node object. For example:

The previous example describes two node objects, for Manu and Gregg, with the knows property defined to treat string values as identifiers. Embedding allows the node object for Gregg to be embedded as a value of the knows property:

A node object, like the one used above, may be used in any value position in the body of a JSON-LD document. Note that type coercion of the knows property is not required, as the value is not a string.

While it is considered a best practice to identify nodes in a graph, at times this is impractical. In the data model, nodes without an explicit identifier are called blank nodes, which can be represented in a serialization such as JSON-LD using a blank node identifier. In the previous example, the top-level node for Manu does not have an identifier, and does not need one to describe it within the data model. However, if we were to want to describe a knows relationship from Gregg to Manu, we would need to introduce a blank node identifier (here _:b0).

Blank node identifiers may be automatically introduced by algorithms such as flattening, but they are also useful for authors to describe such relationships directly.

Identifying Blank Nodes

At times, it becomes necessary to be able to express information without being able to uniquely identify the node with an IRI. This type of node is called a blank node. JSON-LD does not require all nodes to be identified using @id. However, some graph topologies may require identifiers to be serializable. Graphs containing loops, e.g., cannot be serialized using embedding alone, @id must be used to connect the nodes. In these situations, one can use blank node identifiers, which look like IRIs using an underscore (_) as scheme. This allows one to reference the node locally within the document, but makes it impossible to reference the node from an external document. The blank node identifier is scoped to the document in which it is used.

The example above contains information about two secret agents that cannot be identified with an IRI. While expressing that agent 1 knows agent 2 is possible without using blank node identifiers, it is necessary to assign agent 1 an identifier so that it can be referenced from agent 2.

It is worth noting that blank node identifiers may be relabeled during processing. If a developer finds that they refer to the blank node more than once, they should consider naming the node using a dereferenceable IRI so that it can also be referenced from other documents.

Indexed Values

Sometimes multiple property values need to be accessed in a more direct fashion than iterating though multiple array values. JSON-LD provides an indexing mechanism to allow the use of an intermediate dictionary to associate specific indexes with associated values.

Data Indexing
As described in , data indexing allows an arbitrary to reference a node or value.
Language Indexing
As described in , language indexing allows a language to reference a string and be interpreted as the language associated with that string.
Node Identifier Indexing
As described in , node indentifier indexing allows an IRI to reference a node and be interpreted as the identifier of that node.
Node Type Indexing
As described in , node type indexing allows an IRI to reference a node and be interpreted as a type of that node.

See for other uses of indexing in JSON-LD.

Data Indexing

Databases are typically used to make access to data more efficient. Developers often extend this sort of functionality into their application data to deliver similar performance gains. Often this data does not have any meaning from a Linked Data standpoint, but is still useful for an application.

JSON-LD introduces the notion of index maps that can be used to structure data into a form that is more efficient to access. The data indexing feature allows an author to structure data using a simple key-value map where the keys do not map to IRIs. This enables direct access to data instead of having to scan an array in search of a specific item. In JSON-LD such data can be specified by associating the @index keyword with a @container declaration in the context:

In the example above, the post term has been marked as an index map. The en and de keys will be ignored semantically, but preserved syntactically, by the JSON-LD Processor. This allows a developer to access the German version of the post using the following code snippet: obj.post.de.

The interpretation of the data is expressed in the statements table. Note how the index keys do not appear in the statements, but would continue to exist if the document were compacted or expanded (see and ) using a JSON-LD processor.

The value of @container can also be an array containing both @index and @set. When compacting, this ensures that a JSON-LD Processor will use the array form for all values of indexes.

If the processing mode is set to json-ld-1.1, the special index @none is used for indexing data which does not have an associated index, which is useful to maintain a normalized representation.

Language Indexing

JSON which includes string values in multiple languages may be represented using a language map to allow for easily indexing property values by language tag. This enables direct access to language values instead of having to scan an array in search of a specific item. In JSON-LD such data can be specified by associating the @language keyword with a @container declaration in the context:

In the example above, the label term has been marked as an language map. The en and de keys are implicitly associated with their respective values by the JSON-LD Processor. This allows a developer to access the German version of the label using the following code snippet: obj.label.de.

The value of @container can also be an array containing both @language and @set. When compacting, this ensures that a JSON-LD Processor will use the array form for all values of language tags.

If the processing mode is set to json-ld-1.1, the special index @none is used for indexing data which does not have a language, which is useful to maintain a normalized representation.

Node Identifier Indexing

In addition to index maps, JSON-LD introduces the notion of id maps for structuring data. The id indexing feature allows an author to structure data using a simple key-value map where the keys map to IRIs. This enables direct access to associated node objects instead of having to scan an array in search of a specific item. In JSON-LD such data can be specified by associating the @id keyword with a @container declaration in the context:

In the example above, the post term has been marked as an id map. The http://example.com/posts/1/en and http://example.com/posts/1/de keys will be interpreted as the @id property of the node object value.

The interpretation of the data above is exactly the same as that in using a JSON-LD processor.

The value of @container can also be an array containing both @id and @set. When compacting, this ensures that a JSON-LD processor will use the array form for all values of node identifiers.

The special index @none is used for indexing node objects which do not have an @id, which is useful to maintain a normalized representation. The @none index may also be a term which expands to @none, such as the term none used in the example below.

Id maps are a new feature in JSON-LD 1.1, requiring processing mode set to json-ld-1.1.

Node Type Indexing

In addition to id and index maps, JSON-LD introduces the notion of type maps for structuring data. The type indexing feature allows an author to structure data using a simple key-value map where the keys map to IRIs. This enables data to be structured based on the @type of specific node objects. In JSON-LD such data can be specified by associating the @type keyword with a @container declaration in the context:

In the example above, the affiliation term has been marked as an type map. The schema:Corporation and schema:ProfessionalService keys will be interpreted as the @type property of the node object value.

The value of @container can also be an array containing both @type and @set. When compacting, this ensures that a JSON-LD processor will use the array form for all values of types.

The special index @none is used for indexing node objects which do not have an @type, which is useful to maintain a normalized representation. The @none index may also be a term which expands to @none, such as the term none used in the example below.

As with id maps, when used with @type, a container may also include @set to ensure that key values are always contained in an array.

Type maps are a new feature in JSON-LD 1.1, requiring processing mode set to json-ld-1.1.

Reverse Properties

JSON-LD serializes directed graphs. That means that every property points from a node to another node or value. However, in some cases, it is desirable to serialize in the reverse direction. Consider for example the case where a person and its children should be described in a document. If the used vocabulary does not provide a children property but just a parent property, every node representing a child would have to be expressed with a property pointing to the parent as in the following example.

Expressing such data is much simpler by using JSON-LD's @reverse keyword:

The @reverse keyword can also be used in expanded term definitions to create reverse properties as shown in the following example:

Named Graphs

At times, it is necessary to make statements about a graph itself, rather than just a single node. This can be done by grouping a set of nodes using the @graph keyword. A developer may also name data expressed using the @graph keyword by pairing it with an @id keyword as shown in the following example:

The example above expresses a named graph that is identified by the IRI http://example.org/foaf-graph. That graph is composed of the statements about Manu and Gregg. Metadata about the graph itself is expressed via the generatedAt property, which specifies when the graph was generated.

When a JSON-LD document's top-level structure is an dictionary that contains no other keys than @graph and optionally @context (properties that are not mapped to an IRI or a keyword are ignored), @graph is considered to express the otherwise implicit default graph. This mechanism can be useful when a number of nodes exist at the document's top level that share the same context, which is, e.g., the case when a document is flattened. The @graph keyword collects such nodes in an array and allows the use of a shared context.

In this case, embedding doesn't work as each node object references the other. This is equivalent to using multiple node objects in array and defining the @context within each node object:

Graph Containers

In some cases, it is useful to logically partition data into separate graphs, without making this explicit within the JSON expression. For example, a JSON document may contain data against which other metadata is asserted and it is useful to separate this data in the data model using the notion of named graphs, without the syntactic overhead associated with the @graph keyword.

An expanded term definition can use @graph as the value of @container. This indicates that values of this term should be considered to be named graphs, where the graph name is an automatically assigned blank node identifier creating an implicitly named graph. When expanded, these become simple graph objects.

An alternative to our example above could use an anonymously named graph as follows:

The example above expresses a named graph that is identified by the blank node identifier _:b0. That graph is composed of the statements about Manu and Gregg. Metadata about the graph itself is expressed via the generatedAt property, which specifies when the graph was generated.

The blank node identifier _:b0 is automatically created to allow the default graph to reference the named graph as the definition of the claim. These are necessary for serialization, where nodes without explicit identifiers, such as the named graph in this case, can be represented.

Strictly speaking, the value of such a term is not a named graph, rather it is the graph name associated with the named graph, which exists separately within the dataset.

Graph Containers are a new feature in JSON-LD 1.1, requiring processing mode set to json-ld-1.1.

Named Graph Data Indexing

In addition to indexing node objects by index, graph objects may also be indexed by an index. By using the @graph container type, introduced in in addition to @index, an object value of such a property is treated as a key-value map where the keys do not map to IRIs, but are taken from an @index property associated with named graphs which are their values. When expanded, these must be simple graph objects

The following example describes a default graph referencing multiple named graphs using an index map.

As with index maps, when used with @graph, a container may also include @set to ensure that key values are always contained in an array.

If the processing mode is set to json-ld-1.1, the special index @none is used for indexing graphs which does not have an @index key, which is useful to maintain a normalized representation. Note, however, that compacting a document where multiple unidentified named graphs are compacted using the @none index will result in the content of those graphs being merged. To prevent this, give each graph a distinct @index key.

Named Graph Indexing

In addition to indexing node objects by identifier, graph objects may also be indexed by their graph name. By using the @graph container type, introduced in in addition to @id, an object value of such a property is treated as a key-value map where the keys represent the identifiers of named graphs which are their values.

The following example describes a default graph referencing multiple named graphs using an id map.

As with id maps, when used with @graph, a container may also include @set to ensure that key values are always contained in an array.

As with id maps, the special index @none is used for indexing named graphs which do not have an @id, which is useful to maintain a normalized representation. The @none index may also be a term which expands to @none. Note, however, that if multiple graphs are represented without an @id, they will be merged on expansion. To prevent this, use @none judiciously, and consider giving graphs their own distinct identifier.

Graph Containers are a new feature in JSON-LD 1.1, requiring processing mode set to json-ld-1.1.

Forms of JSON-LD

As with many data formats, there is no single correct way to describe data in JSON-LD. However, as JSON-LD is used for describing graphs, certain transformations can be used to change the shape of the data, without changing its meaning as Linked Data.

Expanded Document Form
Expansion is the process of taking a JSON-LD document and applying a context so that the @context is no longer necessary. This process is described further in .
Compacted Document Form
Compaction is the process of applying a provided context to an existing JSON-LD document. This process is described further in .
Flattened Document Form
Flattening is the process of extracting embedded nodes to the top level of the JSON tree, and replacing the embedded node with a reference, creating blank node identifiers as necessary. This process is described further in .
Framed Document Form
Framing is used to shape the data in a JSON-LD document, using an example frame document which is used to both match the flattened data and show an example of how the resulting data should be shaped. This process is described further in .

Expanded Document Form

The JSON-LD 1.1 Processing Algorithms and API specification [[JSON-LD11-API]] defines a method for expanding a JSON-LD document. Expansion is the process of taking a JSON-LD document and applying a context such that all IRIs, types, and values are expanded so that the @context is no longer necessary.

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

  
  

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

JSON-LD's media type defines a profile parameter which can be used to signal or request expanded document form. The profile URI identifying expanded document form is http://www.w3.org/ns/json-ld#expanded.

Compacted Document Form

The JSON-LD 1.1 Processing Algorithms and API specification [[JSON-LD11-API]] defines a method for compacting a JSON-LD document. Compaction is the process of applying a developer-supplied context to shorten IRIs to terms or compact IRIs and JSON-LD values expressed in expanded form to simple values such as strings or numbers. Often this makes it simpler to work with document as the data is expressed in application-specific terms. Compacted documents are also typically easier to read for humans.

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

  
  

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

  
  

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

JSON-LD's media type defines a profile parameter which can be used to signal or request compacted document form. The profile URI identifying compacted document form is http://www.w3.org/ns/json-ld#compacted.

Flattened Document Form

The JSON-LD 1.1 Processing Algorithms and API specification [[JSON-LD11-API]] defines a method for flattening a JSON-LD document. Flattening collects all properties of a node in a single dictionary and labels all blank nodes with blank node identifiers. This ensures a shape of the data and consequently may drastically simplify the code required to process JSON-LD in certain applications.

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

  
  

Running the JSON-LD Flattening algorithm against the JSON-LD input document in the example above and using the same context would result in the following output:

JSON-LD's media type defines a profile parameter which can be used to signal or request flattened document form. The profile URI identifying flattened document form is http://www.w3.org/ns/json-ld#flattened. It can be combined with the profile URI identifying expanded document form or compacted document from.

Framed Document Form

The JSON-LD 1.1 Framing specification [[JSON-LD11-FRAMING]] defines a method for framing a JSON-LD document. Framing is used to shape the data in a JSON-LD document, using an example frame document which is used to both match the flattened data and show an example of how the resulting data should be shaped.

For example, assume the following JSON-LD frame:

  
  

This frame document describes an embedding structure that would place objects with type Library at the top, with objects of type Book that were linked to the library object using the contains property embedded as property values. It also places objects of type Chapter within the referencing Book object as embedded values of the Book object.

When using a flattened set of objects that match the frame components:

  
  

The Frame Algorithm can create a new document which follows the structure of the frame:

Interpreting JSON as JSON-LD

Ordinary JSON documents can be interpreted as JSON-LD by providing an explicit JSON-LD context document. One way to provide this is by using referencing a JSON-LD context document in an HTTP Link Header. Doing so allows JSON to be unambiguously machine-readable without requiring developers to drastically change their documents and provides an upgrade path for existing infrastructure without breaking existing clients that rely on the application/json media type or a media type with a +json suffix as defined in [[!RFC6839]].

In order to use an external context with an ordinary JSON document, when retrieving an ordinary JSON document via HTTP, processors MUST retrieve any JSON-LD document referenced by a Link Header with:

The referenced document MUST have a top-level JSON object. The @context member within that object is added to the top-level JSON object of the referencing document. If an array is at the top-level of the referencing document and its items are JSON objects, the @context subtree is added to all array items. All extra information located outside of the @context subtree in the referenced document MUST be discarded. Effectively this means that the active context is initialized with the referenced external context. A response MUST NOT contain more than one HTTP Link Header [[!RFC8288]] using the http://www.w3.org/ns/json-ld#context link relation.

Other mechanisms for providing a JSON-LD Context MAY be described for other URI schemes.

The JSON-LD 1.1 Processing Algorithms and API specification [[JSON-LD11-API]] provides for an expandContext option for specifying a context to use when expanding JSON documents programatically.

The following example demonstrates the use of an external context with an ordinary JSON document over HTTP:

  
  

Please note that JSON-LD documents served with the application/ld+json media type MUST have all context information, including references to external contexts, within the body of the document. Contexts linked via a http://www.w3.org/ns/json-ld#context HTTP Link Header MUST be ignored for such documents.

Embedding JSON-LD in HTML Documents

HTML script elements can be used to embed blocks of data in documents. This way, JSON-LD content can be easily embedded in HTML [[HTML52]] by placing it in a script element with the type attribute set to application/ld+json.

  
  

Depending on how the HTML document is served, certain strings may need to be escaped.

Defining how such data may be used is beyond the scope of this specification. The embedded JSON-LD document might be extracted as is or, e.g., be interpreted as RDF.

If JSON-LD content is extracted as RDF [[RDF11-CONCEPTS]], it should be expanded into an RDF Dataset using the Deserialize JSON-LD to RDF Algorithm [[JSON-LD11-API]].

Data Model

JSON-LD is a serialization format for Linked Data based on JSON. It is therefore important to distinguish between the syntax, which is defined by JSON in [[!RFC8259]], and the data model which is an extension of the RDF data model [[!RDF11-CONCEPTS]]. The precise details of how JSON-LD relates to the RDF data model are given in .

To ease understanding for developers unfamiliar with the RDF model, the following summary is provided:

JSON-LD documents MAY contain data that cannot be represented by the data model defined above. Unless otherwise specified, such data is ignored when a JSON-LD document is being processed. One result of this rule is that properties which are not mapped to an IRI, a blank node, or keyword will be ignored.

Additionally, the JSON serialization format is internally represented using the JSON-LD internal representation, which uses the generic concepts of arrays, dictionaries, strings, numbers, booleans, and null to describe the data represented by a JSON document.

The image depicts a linked data dataset with a default graph and two named graphs.

An illustration of a linked data dataset.
A description of the linked data dataset diagram is available in the Appendix. Image available in SVG and PNG formats.

The dataset described in this figure can be represented as follows:

Note the use of @graph at the outer-most level to describe three top-level resources (two of them named graphs). The named graphs use @graph in addition to @id to provide the name for each graph.

JSON-LD Grammar

This appendix restates the syntactic conventions described in the previous sections more formally.

A JSON-LD document MUST be valid JSON text as described in [[!RFC8259]], or some format that can be represented in the JSON-LD internal representation that is equivalent to valid JSON text.

A JSON-LD document MUST be a single node object, a dictionary consisting of only the members @context and/or @graph, or an array or zero or more node objects.

In contrast to JSON, in JSON-LD the keys in objects MUST be unique.

Whenever a keyword is discussed in this grammar, the statements also apply to an alias for that keyword.

JSON-LD allows keywords to be aliased (see for details). For example, if the active context defines the term id as an alias for @id, that alias may be legitimately used as a substitution for @id. Note that keyword aliases are not expanded during context processing.

Terms

A term is a short-hand string that expands to an IRI or a blank node identifier.

A term MUST NOT equal any of the JSON-LD keywords.

When used as the prefix in a Compact IRI, to avoid the potential ambiguity of a prefix being confused with an IRI scheme, terms SHOULD NOT come from the list of URI schemes as defined in [[!IANA-URI-SCHEMES]]. Similarly, to avoid confusion between a Compact IRI and a term, terms SHOULD NOT include a colon (:) and SHOULD be restricted to the form of isegment-nz-nc as defined in [[!RFC3987]].

To avoid forward-compatibility issues, a term SHOULD NOT start with an @ character as future versions of JSON-LD may introduce additional keywords. Furthermore, the term MUST NOT be an empty string ("") as not all programming languages are able to handle empty JSON keys.

See and for further discussion on mapping terms to IRIs.

Node Objects

A node object represents zero or more properties of a node in the graph serialized by the JSON-LD document. A dictionary is a node object if it exists outside of a JSON-LD context and:

The properties of a node in a graph may be spread among different node objects within a document. When that happens, the keys of the different node objects need to be merged to create the properties of the resulting node.

A node object MUST be a dictionary. All keys which are not IRIs, compact IRIs, terms valid in the active context, or one of the following keywords (or alias of such a keyword) MUST be ignored when processed:

If the node object contains the @context key, its value MUST be null, an absolute IRI, a relative IRI, a context definition, or an array composed of any of these.

If the node object contains the @id key, its value MUST be an absolute IRI, a relative IRI, or a compact IRI (including blank node identifiers). See , , and for further discussion on @id values.

If the node object contains the @graph key, its value MUST be a node object or an array of zero or more node objects. If the node object contains an @id keyword, its value is used as the graph name of a named graph. See for further discussion on @graph values. As a special case, if a dictionary contains no keys other than @graph and @context, and the dictionary is the root of the JSON-LD document, the dictionary is not treated as a node object; this is used as a way of defining node objects that may not form a connected graph. This allows a context to be defined which is shared by all of the constituent node objects.

If the node object contains the @type key, its value MUST be either an absolute IRI, a relative IRI, a compact IRI (including blank node identifiers), a term defined in the active context expanding into an absolute IRI, or an array of any of these. See for further discussion on @type values.

If the node object contains the @reverse key, its value MUST be a dictionary containing members representing reverse properties. Each value of such a reverse property MUST be an absolute IRI, a relative IRI, a compact IRI, a blank node identifier, a node object or an array containing a combination of these.

If the node object contains the @index key, its value MUST be a string. See for further discussion on @index values.

If the node object contains the @nest key, its value MUST be an dictionary or an array of dictionaries which MUST NOT include a value object. See for further discussion on @nest values.

Keys in a node object that are not keywords MAY expand to an absolute IRI using the active context. The values associated with keys that expand to an absolute IRI MUST be one of the following:

Graph Objects

A graph object represents a named graph, which MAY include include an explicit graph name. A dictionary is a graph object if it exists outside of a JSON-LD context, it is not a node object, it is not the top-most dictionary in the JSON-LD document, and it consists of no members other than @graph, @index, @id and @context, or an alias of one of these keywords.

If the graph object contains the @context key, its value MUST be null, an absolute IRI, a relative IRI, a context definition, or an array composed of any of these.

If the graph object contains the @id key, its value is used as the identifier (graph name) of a named graph, and MUST be an absolute IRI, a relative IRI, or a compact IRI (including blank node identifiers). See , , and for further discussion on @id values.

A graph object without an @id member is also a simple graph object and represents a named graph without an explicit identifier, although in the data model it still has a graph name, which is an implicitly allocated blank node identifier.

The value of the @graph key MUST be a node object or an array of zero or more node objects. See for further discussion on @graph values..

Value Objects

A value object is used to explicitly associate a type or a language with a value to create a typed value or a language-tagged string.

A value object MUST be a dictionary containing the @value key. It MAY also contain an @type, an @language, an @index, or an @context key but MUST NOT contain both an @type and an @language key at the same time. A value object MUST NOT contain any other keys that expand to an absolute IRI or keyword.

The value associated with the @value key MUST be either a string, a number, true, false or null.

The value associated with the @type key MUST be a term, a compact IRI, an absolute IRI, a string which can be turned into an absolute IRI using the vocabulary mapping, or null.

The value associated with the @language key MUST have the lexical form described in [[!BCP47]], or be null.

The value associated with the @index key MUST be a string.

See and for more information on value objects.

Lists and Sets

A list represents an ordered set of values. A set represents an unordered set of values. Unless otherwise specified, arrays are unordered in JSON-LD. As such, the @set keyword, when used in the body of a JSON-LD document, represents just syntactic sugar which is optimized away when processing the document. However, it is very helpful when used within the context of a document. Values of terms associated with an @set or @list container will always be represented in the form of an array when a document is processed—even if there is just a single value that would otherwise be optimized to a non-array form in compact document form. This simplifies post-processing of the data as the data is always in a deterministic form.

A list object MUST be a dictionary that contains no keys that expand to an absolute IRI or keyword other than @list, @context, and @index.

A set object MUST be a dictionary that contains no keys that expand to an absolute IRI or keyword other than @set, @context, and @index. Please note that the @index key will be ignored when being processed.

In both cases, the value associated with the keys @list and @set MUST be one of the following types:

See for further discussion on sets and lists.

Language Maps

A language map is used to associate a language with a value in a way that allows easy programmatic access. A language map may be used as a term value within a node object if the term is defined with @container set to @language, or an array containing both @language and @set . The keys of a language map MUST be strings representing [[BCP47]] language codes, the keyword @none, or a term which expands to @none, and the values MUST be any of the following types:

See for further discussion on language maps.

Index Maps

An index map allows keys that have no semantic meaning, but should be preserved regardless, to be used in JSON-LD documents. An index map may be used as a term value within a node object if the term is defined with @container set to @index, or an array containing both @index and @set . The values of the members of an index map MUST be one of the following types:

See for further information on this topic.

Index Maps may also be used to map indexes to associated named graphs, if the term is defined with @container set to an array containing both @graph and @index, and optionally including @set. The value consists of the node objects contained within the named graph which is named using the referencing key, which can be represented as a simple graph object.

Id Maps

An id map is used to associate an IRI with a value that allows easy programmatic access. An id map may be used as a term value within a node object if the term is defined with @container set to @id, or an array containing both @id and @set. The keys of an id map MUST be IRIs (relative IRI, compact IRI (including blank node identifiers), or absolute IRI), the keyword @none, or a term which expands to @none, and the values MUST be node objects.

If the value contains a property expanding to @id, it's value MUST be equivalent to the referencing key. Otherwise, the property from the value is used as the @id of the node object value when expanding.

Id Maps may also be used to map graph names to their named graphs, if the term is defined with @container set to an array containing both @graph and @id, and optionally including @set. The value consists of the node objects contained within the named graph which is named using the referencing key.

Type Maps

A type map is used to associate an IRI with a value that allows easy programmatic access. A type map may be used as a term value within a node object if the term is defined with @container set to @type, or an array containing both @type and @set. The keys of a type map MUST be IRIs (relative IRI, compact IRI (including blank node identifiers), or absolute IRI), the keyword @none, or a term which expands to @none, and the values MUST be node objects.

If the value contains a property expanding to @type, and it's value is contains the referencing key after suitable expansion of both the referencing key and the value, then the node object already contains the type. Otherwise, the property from the value is added as a @type of the node object value when expanding.

Property Nesting

A nested property is used to gather properties of a node object in a separate dictionary, or array of dictionaries which are not value objects. It is semantically transparent and is removed during the process of expansion. Property nesting is recursive, and collections of nested properties may contain further nesting.

Semantically, nesting is treated as if the properties and values were declared directly within the containing node object.

Context Definitions

A context definition defines a local context in a node object.

A context definition MUST be a dictionary whose keys MUST be either terms, compact IRIs, absolute IRIs, or one of the keywords @language, @base, @vocab, or @version.

If the context definition has an @language key, its value MUST have the lexical form described in [[!BCP47]] or be null.

If the context definition has an @base key, its value MUST be an absolute IRI, a relative IRI, or null.

If the context definition has an @vocab key, its value MUST be a absolute IRI, a compact IRI, a blank node identifier, an empty string (""), a term, or null.

If the context definition has an @version key, its value MUST be a number with the value 1.1.

The value of keys that are not keywords MUST be either an absolute IRI, a compact IRI, a term, a blank node identifier, a keyword, null, or an expanded term definition.

An expanded term definition is used to describe the mapping between a term and its expanded identifier, as well as other properties of the value associated with the term when it is used as key in a node object.

An expanded term definition MUST be a dictionary composed of zero or more keys from @id, @reverse, @type, @language, @context, @prefix, or @container. An expanded term definition SHOULD NOT contain any other keys.

If the term being defined is not a compact IRI or absolute IRI and the active context does not have an @vocab mapping, the expanded term definition MUST include the @id key.

If the expanded term definition contains the @id keyword, its value MUST be null, an absolute IRI, a blank node identifier, a compact IRI, a term, or a keyword.

If an expanded term definition has an @reverse member, it MUST NOT have @id or @nest members at the same time, its value MUST be an absolute IRI, a blank node identifier, a compact IRI, or a term. If an @container member exists, its value MUST be null, @set, or @index.

If the expanded term definition contains the @type keyword, its value MUST be an absolute IRI, a compact IRI, a term, null, or one of the keywords @id or @vocab.

If the expanded term definition contains the @language keyword, its value MUST have the lexical form described in [[!BCP47]] or be null.

If the expanded term definition contains the @container keyword, its value MUST be either @list, @set, @language, @index, @id, @graph, @type, or be null or an array containing exactly any one of those keywords, or a combination of @set and any of @index, @id, @graph, @type, @language in any order . @container may also be an array containing @graph along with either @id or @index and also optionally including @set. If the value is @language, when the term is used outside of the @context, the associated value MUST be a language map. If the value is @index, when the term is used outside of the @context, the associated value MUST be an index map.

If an expanded term definition has an @context member, it MUST be a valid context definition.

If the expanded term definition contains the @nest keyword, its value MUST be either @nest, or a term which expands to @nest.

If the expanded term definition contains the @prefix keyword, its value MUST be true or false.

Terms MUST NOT be used in a circular manner. That is, the definition of a term cannot depend on the definition of another term if that other term also depends on the first term.

See for further discussion on contexts.

Relationship to RDF

JSON-LD is a concrete RDF syntax as described in [[RDF11-CONCEPTS]]. Hence, a JSON-LD document is both an RDF document and a JSON document and correspondingly represents an instance of an RDF data model. However, JSON-LD also extends the RDF data model to optionally allow JSON-LD to serialize generalized RDF Datasets. The JSON-LD extensions to the RDF data model are:

Summarized, these differences mean that JSON-LD is capable of serializing any RDF graph or dataset and most, but not all, JSON-LD documents can be directly interpreted as RDF as described in RDF 1.1 Concepts [[RDF11-CONCEPTS]].

For authors and developers working with blank nodes as properties when deserializing to RDF, three potential approaches are suggested:

The normative algorithms for interpreting JSON-LD as RDF and serializing RDF as JSON-LD are specified in the JSON-LD 1.1 Processing Algorithms and API specification [[JSON-LD11-API]].

Even though JSON-LD serializes generalized RDF Datasets, it can also be used as a RDF graph source. In that case, a consumer MUST only use the default graph and ignore all named graphs. This allows servers to expose data in languages such as Turtle and JSON-LD using content negotiation.

Publishers supporting both dataset and graph syntaxes have to ensure that the primary data is stored in the default graph to enable consumers that do not support datasets to process the information.

Serializing/Deserializing RDF

The process of serializing RDF as JSON-LD and deserializing JSON-LD to RDF depends on executing the algorithms defined in RDF Serialization-Deserialization Algorithms in the JSON-LD 1.1 Processing Algorithms and API specification [[JSON-LD11-API]]. It is beyond the scope of this document to detail these algorithms any further, but a summary of the necessary operations is provided to illustrate the process.

The procedure to deserialize a JSON-LD document to RDF involves the following steps:

  1. Expand the JSON-LD document, removing any context; this ensures that properties, types, and values are given their full representation as IRIs and expanded values. Expansion is discussed further in .
  2. Flatten the document, which turns the document into an array of node objects. Flattening is discussed further in .
  3. Turn each node object into a series of RDF triples.

For example, consider the following JSON-LD document in compact form:

    
    

Running the JSON-LD Expansion and Flattening algorithms against the JSON-LD input document in the example above would result in the following output:

    
    

Deserializing this to RDF now is a straightforward process of turning each node object into one or more RDF triples. This can be expressed in Turtle as follows:

    
    

The process of serializing RDF as JSON-LD can be thought of as the inverse of this last step, creating an expanded JSON-LD document closely matching the triples from RDF, using a single node object for all triples having a common subject, and a single property for those triples also having a common predicate. The result may then be framed by using the Framing Algorithm described in [[JSON-LD11-FRAMING]] to create the desired object embedding.

Image Desciptions

Linked Data Dataset

Description of the Linked Data Dataset figure in

The image consists of three dashed boxes, each describing a different linked data graph. Each box consists of shapes linked with arrows describing the linked data relationships.

The first box is titled "default graph: <no name>" describes two resources: http://example.com/people/alice and http://example.com/people/bob (denoting "Alice" and "Bob" respectively), which are connected by an arrow labeled schema:knows which describes the knows relationship between the two resources. Additionally, the "Alice" resource is related to three different literals:

Alice
an RDF literal with no datatype or language.
weiblich | de
an language-tagged string with the value "weiblich" and language-tag "de".
female | en
an language-tagged string with the value "female" and language-tag "en".

The second and third boxes describe two named graphs, with the graph names "http://example.com/graphs/1" and "http://example.com/graphs/1", respectively.

The second box consists of two resources: http://example.com/people/alice and http://example.com/people/bob related by the schema:parent relationship, and names the http://example.com/people/bob "Bob".

The third box consists of two resources, one named http://example.com/people/bob and the other unnamed. The two resources related to each other using schema:sibling relationship with the second named "Mary".

Relationship to Other Linked Data Formats

The JSON-LD examples below demonstrate how JSON-LD can be used to express semantic data marked up in other linked data formats such as Turtle, RDFa, and Microdata. These sections are merely provided as evidence that JSON-LD is very flexible in what it can express across different Linked Data approaches.

Turtle

The following are examples of transforming RDF expressed in [[Turtle]] into JSON-LD.

Prefix definitions

The JSON-LD context has direct equivalents for the Turtle @prefix declaration:

      
      
      
      

Embedding

Both [[Turtle]] and JSON-LD allow embedding, although [[Turtle]] only allows embedding of blank nodes.

      
      
      
      

Conversion of native data types

In JSON-LD numbers and boolean values are native data types. While [[Turtle]] has a shorthand syntax to express such values, RDF's abstract syntax requires that numbers and boolean values are represented as typed literals. Thus, to allow full round-tripping, the JSON-LD 1.1 Processing Algorithms and API specification [[JSON-LD11-API]] defines conversion rules between JSON-LD's native data types and RDF's counterparts. Numbers without fractions are converted to xsd:integer-typed literals, numbers with fractions to xsd:double-typed literals and the two boolean values true and false to a xsd:boolean-typed literal. All typed literals are in canonical lexical form.

      
      
      
      

Lists

Both JSON-LD and [[Turtle]] can represent sequential lists of values.

      
      
      
      

RDFa

The following example describes three people with their respective names and homepages in RDFa [[RDFA-CORE]].

    
    

An example JSON-LD implementation using a single context is described below.

    
    

Microdata

The HTML Microdata [[MICRODATA]] example below expresses book information as a Microdata Work item.

    
    

Note that the JSON-LD representation of the Microdata information stays true to the desires of the Microdata community to avoid contexts and instead refer to items by their full IRI.

    
    

IANA Considerations

This section has been submitted to the Internet Engineering Steering Group (IESG) for review, approval, and registration with IANA.

application/ld+json

Type name:
application
Subtype name:
ld+json
Required parameters:
None
Optional parameters:
profile

A non-empty list of space-separated URIs identifying specific constraints or conventions that apply to a JSON-LD document according to [[!RFC6906]]. A profile does not change the semantics of the resource representation when processed without profile knowledge, so that clients both with and without knowledge of a profiled resource can safely use the same representation. The profile parameter MAY be used by clients to express their preferences in the content negotiation process. If the profile parameter is given, a server SHOULD return a document that honors the profiles in the list which are recognized by the server. It is RECOMMENDED that profile URIs are dereferenceable and provide useful documentation at that URI. For more information and background please refer to [[!RFC6906]].

This specification defines three values for the profile parameter. To request or specify expanded JSON-LD document form, the URI http://www.w3.org/ns/json-ld#expanded SHOULD be used. To request or specify compacted JSON-LD document form, the URI http://www.w3.org/ns/json-ld#compacted SHOULD be used. To request or specify flattened JSON-LD document form, the URI http://www.w3.org/ns/json-ld#flattened SHOULD be used. Please note that, according [[HTTP11]], the value of the profile parameter has to be enclosed in quotes (") because it contains special characters and, if multiple profiles are combined, whitespace.

When processing the "profile" media type parameter, it is important to note that its value contains one or more URIs and not IRIs. In some cases it might therefore be necessary to convert between IRIs and URIs as specified in section 3 Relationship between IRIs and URIs of [[RFC3987]].

Encoding considerations:
See RFC 6839, section 3.1.
Security considerations:
See [[!RFC8259]]

Since JSON-LD is intended to be a pure data exchange format for directed graphs, the serialization SHOULD NOT be passed through a code execution mechanism such as JavaScript's eval() function to be parsed. An (invalid) document may contain code that, when executed, could lead to unexpected side effects compromising the security of a system.

When processing JSON-LD documents, links to remote contexts are typically followed automatically, resulting in the transfer of files without the explicit request of the user for each one. If remote contexts are served by third parties, it may allow them to gather usage patterns or similar information leading to privacy concerns. Specific implementations, such as the API defined in the JSON-LD 1.1 Processing Algorithms and API specification [[!JSON-LD11-API]], may provide fine-grained mechanisms to control this behavior.

JSON-LD contexts that are loaded from the Web over non-secure connections, such as HTTP, run the risk of being altered by an attacker such that they may modify the JSON-LD active context in a way that could compromise security. It is advised that any application that depends on a remote context for mission critical purposes vet and cache the remote context before allowing the system to use it.

Given that JSON-LD allows the substitution of long IRIs with short terms, JSON-LD documents may expand considerably when processed and, in the worst case, the resulting data might consume all of the recipient's resources. Applications should treat any data with due skepticism.

Interoperability considerations:
Not Applicable
Published specification:
http://www.w3.org/TR/json-ld
Applications that use this media type:
Any programming environment that requires the exchange of directed graphs. Implementations of JSON-LD have been created for JavaScript, Python, Ruby, PHP, and C++.
Additional information:
Magic number(s):
Not Applicable
File extension(s):
.jsonld
Macintosh file type code(s):
TEXT
Person & email address to contact for further information:
Manu Sporny <msporny@digitalbazaar.com>
Intended usage:
Common
Restrictions on usage:
None
Author(s):
Manu Sporny, Dave Longley, Gregg Kellogg, Markus Lanthaler, Niklas Lindström
Change controller:
W3C

Fragment identifiers used with application/ld+json are treated as in RDF syntaxes, as per RDF 1.1 Concepts and Abstract Syntax [[RDF11-CONCEPTS]].

Security Considerations

Consider requirements from Self-Review Questionnaire: Security and Privacy.

See,

Open Issues

The following is a list of issues open at the time of publication.

Consider using "@type": "@json" to describe native values in the compact form.

Allows a term definition to include an @values block to describe structured values, such as for GeoJSON.

When requesting JSON-LD from an HTTP endpoint, it would be useful to provide a reference to a context or frame which should be used by the server to put the results into the proper format.

Provide a means for refering to a remote context without without requiring it to be downloaded.

Consider a container type, similar to @list for encoding things like schema:ItemList serializations, when the values are schema:ListItem and order is set through schema:position.

Consider the opposite of "@container": "@set"; this would be when there is exactly one entry in an @list, instead of compacting to an array, compact to a single item.

It would be useful if JSON-LD recognized both value (rdf:nil) and list ([]).

Consider a mechanism such as Microdata's @itemref for including objects within another referencing node.

Mechinism to allow freezing terms so that additional contexts don't override them.

Should consider html>head>base@href and xml:base, as appropriate.

Update terminology in the spec from IRI to URL.

For every example, there should be an equivalent of the example in the expanded form, in a table with the triples, in [[Turtle]] (as close to the JSON-LD structure as possible) and, possibly, as graphs. Not all of them would appear on the screen at the same time but, rather, the reader could choose what to see with some tabs.

Proposal is to start from scratch, ie, deprecating @graph and replacing the functionality with something cleaner.

Ensure that the output is consistent in shape. Thus if there can ever be multiple values, the structure is always an array.

Consider issues surrounding confusion of differing expansion rules for @id, @type, and dictionary members.

Require JSON-LD processors to be able to identify and extract JSON-LD from a script tag with type application/ld+json within an HTML document.

Instead of normatively requiring an initial context, such as RDFa does, instead JSON-LD has the ability to import contexts. This approach means that the existing context rules are followed, and the best practice context can be updated over time as new norms emerge in the community. If the best practice context is not useful to a particular community, then they don't need to import it.

Changes since 1.0 Recommendation of 16 January 2014

Changes since JSON-LD Community Group Final Report

Acknowledgements

This 1.1 version of the specification is a product of deliberations by the members of the JSON-LD 1.1 Working Group chaired by Robert Sanderson and Benjamin Young along with members of the Working Group: Adam Soroka, Alejandra Gonzalez Beltran, Axel Polleres, Christopher Allen, Dan Brickley, Dave Longley, David Lehn, David Newbury, Harold Solbrig, Ivan Herman, Jeff Mixter, Leonard Rosenthol, Manu Sporny, Matthias Kovatsch, Sebastian Käbisch, Simon Steyskal, Steve Blackmon, Timothy Cole, Victor Charpenay, and Gregg Kellogg.

A large amount of thanks goes out to the JSON-LD Community Group participants who worked through many of the technical issues on the mailing list and the weekly telecons: Chris Webber, David Wood, Drummond Reed, Eleanor Joslin, Farbian Gandon, Herm Fisher, Jamie Pitts, Kim Hamilton Duffy, Niklas Lindström, Paolo Ciccarese, Paul Frazze, Paul Warren, Rego Gmür, Rob Trainer, Ted Thibodeau Jr., and Victor Charpenay.

For the 1.0 version of the specification

The authors would like to extend a deep appreciation and the most sincere thanks to Mark Birbeck, who contributed foundational concepts to JSON-LD via his work on RDFj. JSON-LD uses a number of core concepts introduced in RDFj, such as the context as a mechanism to provide an environment for interpreting JSON data. Mark had also been very involved in the work on RDFa as well. RDFj built upon that work. JSON-LD exists because of the work and ideas he started nearly a decade ago in 2004.

A large amount of thanks goes out to the JSON-LD Community Group participants who worked through many of the technical issues on the mailing list and the weekly telecons - of special mention are François Daoust, Stéphane Corlosquet, Lin Clark, and Zdenko 'Denny' Vrandečić.

The work of David I. Lehn and Mike Johnson are appreciated for reviewing, and performing several early implementations of the specification. Thanks also to Ian Davis for this work on RDF/JSON.

Thanks to the following individuals, in order of their first name, for their input on the specification: Adrian Walker, Alexandre Passant, Andy Seaborne, Ben Adida, Blaine Cook, Bradley Allen, Brian Peterson, Bryan Thompson, Conal Tuohy, Dan Brickley, Danny Ayers, Daniel Leja, Dave Reynolds, David Booth, David I. Lehn, David Wood, Dean Landolt, Ed Summers, elf Pavlik, Eric Prud'hommeaux, Erik Wilde, Fabian Christ, Jon A. Frost, Gavin Carothers, Glenn McDonald, Guus Schreiber, Henri Bergius, Jose María Alvarez Rodríguez, Ivan Herman, Jack Moffitt, Josh Mandel, KANZAKI Masahide, Kingsley Idehen, Kuno Woudt, Larry Garfield, Mark Baker, Mark MacGillivray, Marko Rodriguez, Marios Meimaris, Matt Wuerstl, Melvin Carvalho, Nathan Rixham, Olivier Grisel, Paolo Ciccarese, Pat Hayes, Patrick Logan, Paul Kuykendall, Pelle Braendgaard, Peter Patel-Schneider, Peter Williams, Pierre-Antoine Champin, Richard Cyganiak, Roy T. Fielding, Sandro Hawke, Simon Grant, Srecko Joksimovic, Stephane Fellah, Steve Harris, Ted Thibodeau Jr., Thomas Steiner, Tim Bray, Tom Morris, Tristan King, Sergio Fernández, Werner Wilms, and William Waites.