Data Model Overview

Generally speaking, the data model used for JSON-LD 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. There is also a special class of node called a blank node, which is typically used to express data that does not have a global identifier like an IRI. Blank nodes are identified using a blank node identifier. 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 .

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 to be expanded to absolute IRIs.

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

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 to be 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 object 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.

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:

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. A JSON-LD processor will interpret the example above as follows:

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 JSON object, 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 values to particular data types. Type coercion allows someone deploying JSON-LD to coerce the incoming or outgoing values to the proper data type based on a mapping of data type IRIs to terms. Using type coercion, value representation is preserved without requiring the data type to be specified 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 keywords @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, or by interpreting it as relative IRI. 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.

The example shown above would generate the following data.

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.

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.

The example shows two nodes related by a property from the first node:

A node object, like the one used above, may be used in any value position in the body of a JSON-LD document.

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 at any time a JSON object is defined. The only time that one cannot express a context is inside a context definition itself. 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 JSON object. 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 JSON object 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. 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 keywords in future versions of JSON-LD. Terms starting with an @ character that are not JSON-LD 1.0 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.

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:

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:

Sets and Lists

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:

The example shown above would result in the following data being generated, each relating the node to an individual value, with no inherent order:

Multiple values may also be expressed using the expanded form:

The example shown above would generate the following data, again with no inherent order:

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:

List of lists in the form of list objects are not allowed in this version of JSON-LD. This decision was made due to the extreme amount of added complexity when processing lists of lists.

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 or @list 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.

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/graphs/73. 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. An alternative view of the information above is represented in table form below:

When a JSON-LD document's top-level structure is an object that contains no other properties 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:

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 nothing 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.

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.

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 above is expressed in the table below. Note how the index keys do not appear in the Linked Data below, but would continue to exist if the document were compacted or expanded (see and ) using a JSON-LD processor:

Expanded Document Form

The JSON-LD Processing Algorithms and API specification [[JSON-LD-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 Processing Algorithms and API specification [[JSON-LD-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 Processing Algorithms and API specification [[JSON-LD-API]] defines a method for flattening a JSON-LD document. Flattening collects all properties of a node in a single JSON object 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.

Embedding JSON-LD in HTML Documents

HTML script tags can be used to embed blocks of data in documents. This way, JSON-LD content can be easily embedded in HTML 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-LD-API]].

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 Processing Algorithms and API specification [[JSON-LD-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.