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Copyright © 2010-2013 the Contributors to the JSON-LD 1.0 Processing Algorithms and API Specification, published by the RDF Working Group under the W3C Community Final Specification Agreement (FSA). A human-readable summary is available.
This specification defines an Application Programming Interface (API) and a set of algorithms for programmatic transformations of JSON-LD documents. By expressing the data in a way that is specifically tailored to a particular use case, the processing typically becomes much simpler.
This specification was published by the RDF Working Group. It is not a W3C Standard nor is it on the W3C Standards Track. Please note that under the W3C Community Final Specification Agreement (FSA) other conditions apply. Learn more about W3C Community and Business Groups.
This document has been under development for over 25 months in the JSON for Linking Data Community Group. The document has recently been transferred to the RDF Working Group for review, improvement, and publication along the Recommendation track. The specification has undergone significant development, review, and changes during the course of the last 25 months.
There are several independent interoperable implementations of this specification. There is a fairly complete test suite and a live JSON-LD editor that is capable of demonstrating the features described in this document. While there will be continuous development on implementations, the test suite, and the live editor, they are believed to be mature enough to be integrated into a non-production system at this point in time. There is an expectation that they could be used in a production system within the next six months.
It is important for readers to understand that the scope of this document is currently under debate and new features may be added to the specification. Existing features may be modified heavily or removed entirely from the specification upon further review and feedback from the broader community. This is a work in progress and publication as a Working Draft does not require that all Working Group members agree on the content of the document.
There are a number of ways that one may participate in the development of this specification:
This section is non-normative.
This document is a detailed specification for an Application Programming Interface for the JSON-LD syntax. The document is primarily intended for the following audiences:
To understand the basics in this specification you must first be familiar with JSON, which is detailed in [RFC4627]. You must also understand the JSON-LD Syntax [JSON-LD], which is the base syntax used by all of the algorithms in this document. To understand the API and how it is intended to operate in a programming environment, it is useful to have working knowledge of the JavaScript programming language [ECMA-262] and WebIDL [WEBIDL]. To understand how JSON-LD maps to RDF, it is helpful to be familiar with the basic RDF concepts [RDF11-CONCEPTS].
This section is non-normative.
The JSON-LD Syntax specification [JSON-LD] outlines a syntax that may be used to express Linked Data in JSON. Because there is more than one way to express Linked Data using this syntax, it is often useful to be able to transform JSON-LD documents so that they may be more easily consumed by specific applications.
The way JSON-LD allows Linked Data to be expressed in a way that is specifically tailored to a particular person or application is by providing a context. By providing a context, JSON data can be expressed in a way that is a natural fit for a particular person or application whilst also indicating how the data should be understood at a global scale. In order for people or applications to share data that was created using a context that is different from their own, a JSON-LD processor must be able to transform a document from one context to another. Instead of requiring JSON-LD processors to write specific code for every imaginable context switching scenario, it is much easier to specify a single algorithm that can remove any context. Similarly, another algorithm can be specified to subsequently apply any context. These two algorithms represent the most basic transformations of JSON-LD documents. They are referred to as expansion and compaction, respectively.
There are four major types of transformation that are discussed in this document: expansion, compaction, flattening, and RDF conversion.
This section is non-normative.
The algorithm that removes context is called expansion. Before performing any other transformations on a JSON-LD document, it is easiest to remove any context from it, localizing all information, and to make data structures more regular.
To get an idea of how context and data structuring affects the same data, here is an example of JSON-LD that uses only terms and is fairly compact:
{ "@context": { "name": "http://xmlns.com/foaf/0.1/name", "homepage": { "@id": "http://xmlns.com/foaf/0.1/homepage", "@type": "@id" } }, "@id": "http://me.markus-lanthaler.com/", "name": "Markus Lanthaler", "homepage": "http://www.markus-lanthaler.com/" }
The next input example uses one IRI to express a property and array to encapsulate another, but leaves the rest of the information untouched.
{ "@context": { "website": "http://xmlns.com/foaf/0.1/homepage" }, "@id": "http://me.markus-lanthaler.com/", "http://xmlns.com/foaf/0.1/name": "Markus Lanthaler", "website": { "@id": "http://www.markus-lanthaler.com/" } }
Note that both inputs are valid JSON-LD and both represent the same information. The difference is in their context information and in the data structures used. A JSON-LD processor can remove context and ensure that the data is more regular by employing expansion.
Expansion has two important goals: removing any contextual
information from the document, and ensuring all values are represented
in a regular form. These goals are accomplished by expanding all properties
to absolute IRIs and by expressing all
values in arrays in
expanded form. Expanded form is the most verbose
and regular way of expressing of values in JSON-LD; all contextual
information from the document is instead stored locally with each value.
Running the Expansion algorithm
(expand
operation) against the examples provided above results in the following output:
[ { "@id": "http://me.markus-lanthaler.com/", "http://xmlns.com/foaf/0.1/name": [ { "@value": "Markus Lanthaler" } ], "http://xmlns.com/foaf/0.1/homepage": [ { "@id": "http://www.markus-lanthaler.com/" } ] } ]
Note that in the output above all context definitions have been removed, all terms and compact IRIs have been expanded to absolute IRIs, and all JSON-LD values are expressed in arrays in expanded form. While the output is more verbose and difficult for a human to read, it establishes a baseline that makes JSON-LD processing easier because of its very regular structure.
This section is non-normative.
While expansion removes context from a given input, compaction's primary function is to perform the opposite operation: to express a given input according to a particular context. Compaction applies a context that specifically tailors the way information is expressed for a particular person or application. This simplifies applications that consume JSON or JSON-LD by expressing the data in application-specific terms, and it makes the data easier to read by humans.
Compaction uses 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.
For example, assume the following expanded JSON-LD input document:
[ { "@id": "http://me.markus-lanthaler.com/", "http://xmlns.com/foaf/0.1/name": [ { "@value": "Markus Lanthaler" } ], "http://xmlns.com/foaf/0.1/homepage": [ { "@id": "http://www.markus-lanthaler.com/" } ] } ]
Additionally, assume the following developer-supplied JSON-LD context:
{ "@context": { "name": "http://xmlns.com/foaf/0.1/name", "homepage": { "@id": "http://xmlns.com/foaf/0.1/homepage", "@type": "@id" } } }
Running the Compaction Algorithm
(compact
operation) given the context supplied above against the JSON-LD input
document provided above would result in the following output:
{ "@context": { "name": "http://xmlns.com/foaf/0.1/name", "homepage": { "@id": "http://xmlns.com/foaf/0.1/homepage", "@type": "@id" } }, "@id": "http://me.markus-lanthaler.com/", "name": "Markus Lanthaler", "homepage": "http://www.markus-lanthaler.com/" }
Note that all IRIs have been compacted to
terms as specified in the context,
which has been injected into the output. While compacted output is
useful to humans, it is also used to generate structures that are easy to
program against. Compaction enables developers to map any expanded document
into an application-specific compacted document. While the context provided
above mapped http://xmlns.com/foaf/0.1/nam
to name
, it
could also have been mapped to any other term provided by the developer.
This section is non-normative.
While expansion ensures that a document is in a uniform structure, flattening goes a step further to ensure that the shape of the data is deterministic. In expanded documents, the properties of a single node may be spread across a number of different JSON objects. By flattening a document, all properties of a node are collected in a single JSON object and all blank nodes are labeled with a blank node identifier. This may drastically simplify the code required to process JSON-LD data in certain applications.
For example, assume the following JSON-LD input document:
{ "@context": { "name": "http://xmlns.com/foaf/0.1/name", "knows": "http://xmlns.com/foaf/0.1/knows" }, "@id": "http://me.markus-lanthaler.com/", "name": "Markus Lanthaler", "knows": [ { "name": "Dave Longley" } ] }
Running the Flattening algorithm
(flatten
operation) with a context set to null to prevent compaction
returns the following document:
[ { "@id": "_:t0", "http://xmlns.com/foaf/0.1/name": [ { "@value": "Dave Longley" } ] }, { "@id": "http://me.markus-lanthaler.com/", "http://xmlns.com/foaf/0.1/name": [ { "@value": "Markus Lanthaler" } ], "http://xmlns.com/foaf/0.1/knows": [ { "@id": "_:t0" } ] } ]
Note how in the output above all properties of a node are collected in a
single JSON object and how the blank node representing
"Dave Longley" has been assigned the blank node identifier
_:t0
.
To make it easier for humans to read or for certain applications to process it, a flattened document can be compacted by passing a context. Using the same context as the input document, the flattened and compacted document looks as follows:
{ "@context": { "name": "http://xmlns.com/foaf/0.1/name", "knows": "http://xmlns.com/foaf/0.1/knows" }, "@graph": [ { "@id": "_:t0", "name": "Dave Longley" }, { "@id": "http://me.markus-lanthaler.com/", "name": "Markus Lanthaler", "knows": { "@id": "_:t0" } } ] }
Please note that the flattened and compacted result always explicitly
designates the default graph by the @graph
member in the
top-level JSON object.
This section is non-normative.
JSON-LD can be used to serialize data expressed in RDF as described in [RDF11-CONCEPTS]. This ensures that data can be round-tripped to and from any RDF syntax without any loss in fidelity.
For example, assume the following RDF input serialized in Turtle [TURTLE]:
<http://me.markus-lanthaler.com/> <http://xmlns.com/foaf/0.1/name> "Markus Lanthaler" . <http://me.markus-lanthaler.com/> <http://xmlns.com/foaf/0.1/homepage> <http://www.markus-lanthaler.com/> .
Using the Convert from RDF algorithm a developer could transform this document into expanded JSON-LD:
[ { "@id": "http://me.markus-lanthaler.com/", "http://xmlns.com/foaf/0.1/name": [ { "@value": "Markus Lanthaler" } ], "http://xmlns.com/foaf/0.1/homepage": [ { "@id": "http://www.markus-lanthaler.com/" } ] } ]
Note that the output above could easily be compacted using the technique outlined in the previous section. It is also possible to transform the JSON-LD document back to RDF using the Convert to RDF algorithm.
All examples and notes as well as sections marked as non-normative in this specification are non-normative. Everything else in this specification is normative.
The keywords MUST, MUST NOT, REQUIRED, SHOULD, SHOULD NOT, RECOMMENDED, MAY, and OPTIONAL in this specification are to be interpreted as described in [RFC2119].
There are two classes of products that can claim conformance to this specification: JSON-LD Implementations and JSON-LD Processors.
A conforming JSON-LD Implementation is a system capable of transforming JSON-LD documents according the algorithms defined in this specification.
A conforming JSON-LD Processor is a conforming JSON-LD Implementation
that exposes the Application Programming Interface (API) defined in this specification.
It MUST implement the json-ld-1.0
processing mode (for further details, see the
processingMode
option of JsonLdOptions
).
The algorithms in this specification are generally written with more concern for clarity than efficiency. Thus, JSON-LD Implementations and Processors may implement the algorithms given in this specification in any way desired, so long as the end result is indistinguishable from the result that would be obtained by the specification's algorithms.
This specification does not define how JSON-LD Implementations or Processors handle non-conforming input documents. This implies that JSON-LD Implementations or Processors MUST NOT attempt to correct malformed IRIs or language tags; however, they MAY issue validation warnings. IRIs are not modified other than converted between relative and absolute IRIs.
Implementers can partially check their level of conformance to this specification by successfully passing the test cases of the JSON-LD test suite [JSON-LD-TESTS]. Note, however, that passing all the tests in the test suite does not imply complete conformance to this specification. It only implies that the implementation conforms to aspects tested by the test suite.
This document uses the following terms as defined in JSON [RFC4627]. Refer to the JSON Grammar section in [RFC4627] for formal definitions.
@context
where the value, or the @id
of the
value, is null explicitly decouples a term's association
with an IRI. A key-value pair in the body of a JSON-LD document whose
value is null has the same meaning as if the key-value pair
was not defined. If @value
, @list
, or
@set
is set to null in expanded form, then
the entire JSON object is ignored.Furthermore, the following terminology is used throughout this document:
_:
.@context
keyword.@value
, @list
,
or @set
keywords, or@graph
and @context
.@value
member.@list
member.@set
member.When processing a JSON-LD data structure, each processing rule is applied using information provided by the active context. This section describes how to produce an active context.
The active context contains the active term definitions which specify how properties and values have to be interpreted as well as the current base IRI, the vocabulary mapping and the default language. Each term definition consists of an IRI mapping, a boolean flag reverse property, an optional type mapping or language mapping, and an optional container mapping. A term definition can not only be used to map a term to an IRI, but also to map a term to a keyword, in which case it is referred to as a keyword alias.
When processing, the active context is initialized without any term definitions, vocabulary mapping, or default language. If a local context is encountered during processing, a new active context is created by cloning the existing active context. Then the information from the local context is merged into the new active context. Given that local contexts may contain references to remote contexts, this includes their retrieval.
This section is non-normative.
First we prepare a new active context result by cloning the current active context. Then we normalize the form the passed local context to an array. Local contexts may be in the form of a JSON object, a string, or an array containing a combination of the two. Finally we process each context contained in the local context array as follows.
If context is a string, it represents a reference to
a remote context. We dereference the remote context and replace context
with the value of the @context
key of the top-level object in the
retrieved JSON-LD document. If there's no such key, an invalid remote context has
been detected. Otherwise, we process context by recursively using
this algorithm ensuring that there is no cyclical reference.
If context is a JSON object, we first update the
base IRI, the vocabulary mapping, and the
default language by processing three specific keywords:
@base
, @vocab
, and @language
.
These are handled before any other keys in the local context because
they affect how the other keys are processed.
Then, for every other key in local context, we update the term definition in result. Since term definitions in a local context may themselves contain terms or compact IRIs, we may need to recurse. When doing so, we must ensure that there is no cyclical dependency, which is an error. After we have processed any term definition dependencies, we update the current term definition, which may be a keyword alias.
Finally, we return result as the new active context.
This algorithm specifies how a new active context is updated with a local context. The algorithm takes three input variables: an active context, a local context, and an array remote contexts which is used to detect cyclical context inclusions. If remote contexts is not passed, it is initialized to an empty array.
recursive context inclusion
error has been detected and processing is aborted;
otherwise, add context to remote contexts.@context
member, an
invalid remote context
has been detected and processing is aborted; otherwise,
set context to the value of that member.invalid local context
error has been detected and processing is aborted.@base
key:
This feature is
at risk as the fact that a document may have multiple base IRIs
is potentially confusing for developers. It is also being discussed whether
relative IRIs are allowed as values of @base
or whether
the empty string should be used to explicitly specify that there isn't
a base IRI, which could be used to ensure that relative IRIs remain
relative when expanding.
@base
key.invalid base IRI
error has been detected and processing is aborted.@vocab
key:
@vocab
key.invalid vocab mapping
error has been detected and processing is aborted.@language
key:
@language
key.invalid default language
error has been detected and processing is aborted.@base
, @vocab
, or
@language
, invoke the
Create Term Definition algorithm,
passing result for active context,
context for local context, key,
and defined.This algorithm is called from the Context Processing algorithm to create a term definition in the active context for a term being processed in a local context.
This section is non-normative.
Term definitions are created by parsing the information in the given local context for the given term. If the given term is a compact IRI, it may omit an IRI mapping by depending on its prefix having its own term definition. If the prefix is a key in the local context, then its term definition must first be created, through recursion, before continuing. Because a term definition can depend on other term definitions, a mechanism must be used to detect cyclical dependencies. The solution employed here uses a map, defined, that keeps track of whether or not a term has been defined or is currently in the process of being defined. This map is checked before any recursion is attempted.
After all dependencies for a term have been defined, the rest of the information in the local context for the given term is taken into account, creating the appropriate IRI mapping, container mapping, and type mapping or language mapping for the term.
The algorithm has four required inputs which are: an active context, a local context, a term, and a map defined.
cyclic IRI mapping
error has been detected and processing is aborted.keyword redefinition
error has been detected and processing is aborted.@id
-null, set the
term definition in active context to
null, set the value associated with defined's
key term to true, and return.@context
, an
invalid keyword alias
error has been detected and processing is aborted.invalid term definition
error has been detected and processing is aborted.@reverse
:
@id
, an
@type
, or an @language
, member, an
invalid reverse property
error has been detected and processing is aborted.@reverse
key
is not a string, an
invalid IRI mapping
error has been detected and processing is aborted.@reverse
key for value, true
for vocab, true for document relative,
local context, and defined. If the result
is not an absolute IRI, i.e., it contains no
colon (:
), an
invalid IRI mapping
error has been detected and processing is aborted.@id
.@container
member,
set the container mapping of definition
to @index
if that is the value of the
@container
member; otherwise an
invalid reverse property
error has been detected (reverse properties only support
index-containers) and processing is aborted.@id
:
@id
key is not a string, an
invalid IRI mapping
error has been detected and processing is aborted.@id
key for
value, true for vocab,
true for document relative,
local context, and defined.:
):
invalid IRI mapping
error been detected and processing is aborted.@type
:
@type
key, which must be a string. Otherwise, an
invalid type mapping
error has been detected and processing is aborted.@id
, nor @vocab
, nor an absolute IRI, an
invalid type mapping
error has been detected and processing is aborted.@container
:
@container
key, which must be either
@list
, @set
, @index
,
or @language
. Otherwise, an
invalid container mapping
error
has been detected and processing is aborted.@language
and
does not contain the key @type
:
@language
key, which must be either null
or a string. Otherwise, an
invalid language mapping
error has been detected and processing is aborted.In JSON-LD documents, some keys and values may represent IRIs. This section defines an algorithm for transforming a string that represents an IRI into an absolute IRI or blank node identifier. It also covers transforming keyword aliases into keywords.
IRI expansion may occur during context processing or during any of the other JSON-LD algorithms. If IRI expansion occurs during context processing, then the local context and its related defined map from the Context Processing algorithm are passed to this algorithm. This allows for term definition dependencies to be processed via the Create Term Definition algorithm.
This section is non-normative.
In order to expand value to an absolute IRI, we must first determine if it is null, a term, a keyword alias, or some form of IRI. Based on what we find, we handle the specific kind of expansion; for example, we expand a keyword alias to a keyword and a term to an absolute IRI according to its IRI mapping in the active context. While inspecting value we may also find that we need to create term definition dependencies because we're running this algorithm during context processing. We can tell whether or not we're running during context processing by checking local context against null. We know we need to create a term definition in the active context when value is a key in the local context and the defined map does not have a key for value with an associated value of true. The defined map is used during Context Processing to keep track of which terms have already been defined or are in the process of being defined. We create a term definition by using the Create Term Definition algorithm.
The algorithm takes two required and four optional input variables. The
required inputs are an active context and a value
to be expanded. The optional inputs are two flags,
document relative and vocab, that specifying
whether value can be interpreted as a relative IRI
against the document's base IRI or the
active context's
vocabulary mapping, respectively, and
a local context and a map defined to be used when
this algorithm is used during Context Processing.
If not passed, the two flags are set to false
and
local context and defined are initialized to null.
:
), it is either
an absolute IRI or a compact IRI:
:
)._
)
and suffix does not begin with double-forward-slash
(//
), it may be a compact IRI:
invalid IRI mapping
error has been detected and processing is aborted.This algorithm expands a JSON-LD document, such that all context definitions are removed, all terms and compact IRIs are expanded to absolute IRIs, blank node identifiers, or keywords and all JSON-LD values are expressed in arrays in expanded form.
This section is non-normative.
Starting with its root element, we can process the JSON-LD document recursively, until we have a fully expanded result. When expanding an element, we can treat each one differently according to its type, in order to break down the problem:
Finally, after ensuring result is in an array, we return result.
The algorithm takes three input variables: an active context,
an active property, and an element to be expanded.
To begin, the active context is set to the result of performing,
Context Processing on the passed
expandContext
,
or empty if expandContext
is null, active property is set to null,
and element is set to the JSON-LD input.
@graph
,
drop the free-floating scalar by returning null.@list
or its
container mapping is set to @list
, the
expanded item must not be an array or a
list object, otherwise a
list of lists
error has been detected and processing is aborted.@context
, set
active context to the result of the
Context Processing algorithm,
passing active context and the value of the
@context
key as local context.@context
, continue to
the next key.:
) nor it is a keyword,
drop key by continuing to the next key.@reverse
, an
invalid reverse property map
error has been detected and processing is aborted.colliding keywords
error has been detected and processing is aborted.@id
and
value is not a string, an
invalid @id value
error has been detected and processing is aborted. Otherwise,
set expanded value to the result of using the
IRI Expansion algorithm,
passing active context, value, and true
for document relative.@type
and value
is neither a string nor an array of
strings, an
invalid type value
error has been detected and processing is aborted. Otherwise,
set expanded value to the result of using the
IRI Expansion algorithm, passing
active context, true for vocab,
and true for document relative to expand the value
or each of its items.@graph
, set
expanded value to the result of using this algorithm
recursively passing active context, @graph
for active property, and value for element.@value
and
value is not a scalar or null, an
invalid value object value
error has been detected and processing is aborted. Otherwise,
set expanded value to value. If expanded value
is null, set the @value
member of result to null and continue with the
next key from element. Null values need to be preserved
in this case as the meaning of an @type
member depends
on the existence of an @value
member.@language
and
value is not a string, an
invalid language-tagged string
error has been detected and processing is aborted. Otherwise,
set expanded value to lowercased value.@index
and
value is not a string, an
invalid @index value
error has been detected and processing is aborted. Otherwise,
set expanded value to value.@list
:
@graph
, continue with the next key
from element to remove the free-floating list..list of lists
error has been detected and processing is aborted.@set
, set
expanded value to the result of using this algorithm
recursively, passing active context,
active property, and value for
element.@reverse
and
value is not a JSON object, an
invalid @reverse value
error has been detected and processing is aborted. Otherwise
@reverse
as active property, and
value as element.@reverse
member,
i.e., properties that are reversed twice, execute for each of its
property and item the following steps:
@reverse
:
@reverse
member, create
one and set its value to an empty JSON object.@reverse
member in result
using the variable reverse map.@reverse
:
invalid reverse property value
has been detected and processing is aborted.@language
and
value is a JSON object then value
is expanded from a language map
as follows:
invalid language map value
error has been detected and processing is aborted.@value
-item)
and (@language
-lowercased
language).@index
and
value is a JSON object then value
is expanded from an index map as follows:
@index
, add the key-value pair
(@index
-index) to
item.@list
and
expanded value is not already a list object,
convert expanded value to a list object
by first setting it to an array containing only
expanded value if it is not already an array,
and then by setting it to a JSON object containing
the key-value pair @list
-expanded value.@reverse
member, create
one and initialize its value to an empty JSON object.@reverse
member in result
using the variable reverse map.
invalid reverse property value
has been detected and processing is aborted.@value
:
@value
, @language
, @type
,
and @index
. It must not contain both the
@language
key and the @type
key.
Otherwise, an
invalid value object
error has been detected and processing is aborted.@value
key is
null, then set result to null.@value
member
is not a string and result contains the key
@language
, an
invalid language-tagged value
error has been detected (only strings
can be language-tagged) and processing is aborted.@type
member
and its value is not a string, an
invalid typed value
error has been detected and processing is aborted.@type
and its associated value is not an array, set it to
an array containing only the associated value.@set
or @list
:
@index
. Otherwise, an
invalid set or list object
error has been detected and processing is aborted.@set
, then
set result to the key's associated value.@language
, set result to null.@graph
,
drop free-floating values as follows:
@value
or @list
, set result to
null.@id
, set result to null.If, after the above algorithm is run, the result is a
JSON object that contains only an @graph
key, set the
result to the value of @graph
's value. Otherwise, if the result
is null, set it to an empty array. Finally, if
the result is not an array, then set the result to an
array containing only the result.
Some values in JSON-LD can be expressed in a compact form. These values are required to be expanded at times when processing JSON-LD documents. A value is said to be in expanded form after the application of this algorithm.
This section is non-normative.
If active property has a type mapping in the
active context set to @id
or @vocab
,
a JSON object with a single member @id
whose
values is the result of using the
IRI Expansion algorithm on value
is returned.
Otherwise, the result will be a JSON object containing
an @value
member whose value is the passed value.
Additionally, an @type
member will be included if there is a
type mapping associated with the active property
or an @language
member if value is a
string and there is language mapping associated
with the active property.
The algorithm takes three required inputs: an active context, an active property, and a value to expand.
@id
, return a new
JSON object containing a single key-value pair where the
key is @id
and the value is the result of using the
IRI Expansion algorithm, passing
active context, value, and true for
document relative.@vocab
, return
a new JSON object containing a single key-value pair
where the key is @id
and the value is the result of
using the IRI Expansion algorithm, passing
active context, value, true for
vocab, and true for
document relative.@value
member whose value is set to
value.@type
member to
result and set its value to the value associated with the
type mapping.@language
to result and set its
value to the language code associated with the
language mapping; unless the
language mapping is set to null in
which case no member is added.@language
to result and set its value to the
default language.This algorithm compacts a JSON-LD document, such that the given context is applied. This must result in shortening any applicable IRIs to terms or compact IRIs, any applicable keywords to keyword aliases, and any applicable JSON-LD values expressed in expanded form to simple values such as strings or numbers.
This section is non-normative.
Starting with its root element, we can process the JSON-LD document recursively, until we have a fully compacted result. When compacting an element, we can treat each one differently according to its type, in order to break down the problem:
@index
or @language
maps.The final output is a JSON object with a @context
key, if a context was given, where the JSON object
is either result or a wrapper for it where result appears
as the value of an (aliased) @graph
key because result
contained two or more items in an array.
The algorithm takes five required input variables: an active context,
an inverse context, an active property, an
element to be compacted, and a flag
compactArrays
.
To begin, the active context is set to the result of
performing Context Processing
on the passed context, the inverse context is
set to the result of performing the
Inverse Context Creation algorithm
on active context, the active property is
set to null, element is set to the result of
performing the Expansion algorithm
on the JSON-LD input, and, if not passed,
compactArrays
is set to true.
1
), active property has no
container mapping in active context, and
compactArrays
is true, set result to its only item.@value
or @id
member and the result of using the
Value Compaction algorithm,
passing active context, inverse context,
active property,and element as value is
a scalar, return that result.@reverse
,
otherwise to false.@id
or
@type
:
@type
,
false otherwise.@type
array:
1
), then
set compacted value to its only item.@reverse
:
@reverse
for
active property, and expanded value
for element.compactArrays
is false and value is not an
array, set value to a new
array containing only value.@reverse
for iri.@index
and
active property has a container mapping
in active context that is @index
,
then the compacted result will be inside of an @index
container, drop the @index
property by continuing
to the next expanded property.@index
,
@value
, or @language
:
@list
, otherwise pass
the key's associated value for element.@list
:
@list
for iri, and compacted item
for value.@index
, then add a key-value pair
to compacted item where the key is the
result of the IRI Compaction algorithm,
passing active context, inverse context,
@index
as iri, and the associated with the
@index
key in expanded item as value.compaction to list of lists
error has been detected and processing is aborted.@language
or
@index
:
@language
and
compacted item contains the key
@value
, then set compacted item
to the value associated with its @value
key.compactArrays
is false, container is @set
or
@list
, or expanded property is
@list
or @graph
and
compacted item is not an array,
set it to a new array
containing only compacted item.If, after the algorithm outlined above is run, the result result
is an array, replace it with a new
JSON object with a single member whose key is the result
of using the IRI Compaction algorithm,
passing active context, inverse context, and
@graph
as iri and whose value is the array
result. Finally, if a context has been passed, add an
@context
member to result and set its value to
the passed context.
When there is more than one term that could be chosen to compact an IRI, it has to be ensured that the term selection is both deterministic and represents the most context-appropriate choice whilst taking into consideration algorithmic complexity.
In order to make term selections, the concept of an inverse context is introduced. An inverse context is essentially a reverse lookup table that maps container mappings, type mappings, and language mappings to a simple term for a given active context. A inverse context only needs to be generated for an active context if it is being used for compaction.
To make use of an inverse context, a list of preferred container mappings and the type mapping or language mapping are gathered for a particular value associated with an IRI. These parameters are then fed to the Term Selection algorithm, which will find the term that most appropriately matches the value's mappings.
This section is non-normative.
To create an inverse context for a given
active context, each term in the
active context is visited, ordered by length, shortest
first (ties are broken by choosing the lexicographically least
term). For each term, an entry is added to
the inverse context for each possible combination of
container mapping and type mapping
or language mapping that would legally match the
term. Illegal matches include differences between a
value's type mapping or language mapping and
that of the term. If a term has no
container mapping, type mapping, or
language mapping (or some combination of these), then it
will have an entry in the inverse context using the special
key @none
. This allows the
Term Selection algorithm to fall back
to choosing more generic terms when a more
specifically-matching term is not available for a particular
IRI and value combination.
The algorithm takes one required input: the active context that the inverse context is being created for.
@none
. If the
active context has a default language,
set default language to it.@none
. If there
is a container mapping in
term definition, set container to
its associated value.@language
and its value is a new empty
JSON object, the second member is @type
and its value is a new empty JSON object.@type
member in type/language map using the variable
type map.@reverse
member, create one and set its value to the term
being processed.@type
member in type/language map using the variable
type map.@language
member in type/language map using the variable
language map.@null
; otherwise set it
to the language code in language mapping.@language
member in type/language map using the variable
language map.@none
member, create one and set its value to the term
being processed.@type
member in type/language map using the variable
type map.@none
member, create one and set its value to the term
being processed.This algorithm compacts an IRI to a term or compact IRI, or a keyword to a keyword alias. A value that is associated with the IRI may be passed in order to assist in selecting the most context-appropriate term.
This section is non-normative.
If the passed IRI is null, we simply return null. Otherwise, we first try to find a term that the IRI or keyword can be compacted to if it is relative to active context's vocabulary mapping. In order to select the most appropriate term, we may have to collect information about the passed value. This information includes whic container mappings would be preferred for expressing the value, and what its type mapping or language mapping is. For JSON-LD lists, the type mapping or language mapping will be chosen based on the most specific values that work for all items in the list. Once this information is gathered, it is passed to the Term Selection algorithm, which will return the most appropriate term to use.
If no term was found that could be used to compact the IRI, then an attempt is made to find a compact IRI to use. If there is no appropriate compact IRI, then, if the IRI is relative to active context's vocabulary mapping, then it is used. Otherwise, it is transformed to a relative IRI using the document's base IRI. Finally, if the IRI or keyword still could not be compacted, it is returned as is.
This algorithm takes three required inputs and three optional inputs.
The required inputs an active context, an inverse context,
and the iri to be compacted. The optional inputs are a value associated
with the iri, a vocab flag which specifies whether the
passed iri should be compacted using the
active context's
vocabulary mapping, and a reverse flag which specifies whether
a reverse property is being compacted. If not passed, value is set to
null and vocab and reverse are both set to
false
.
@none
.@language
,
and type/language value to @null
. These two
variables will keep track of the preferred
type mapping or language mapping for
a term, based on what is compatible with value.@index
, then append the value @index
to containers.@type
, type/language value to
@reverse
, and append @set
to containers.@index
is a not key in value, then
append @list
to containers.@list
in value.@none
and
item type to @none
.@value
:
@language
,
then set item language to its associated
value.@type
, set item type to its
associated value.@null
.@id
.@value
, then set common language
to @none
because list items have conflicting
languages.@none
because list items have conflicting
types.@none
and
common type is @none
, then
stop processing items in the list because it has been
detected that there is no common language or type amongst
the items.@none
.@none
.@none
then set
type/language to @type
and
type/language value to common type.@language
and does not contain the key @index
,
then set type/language value to its associated
value and append @language
to
containers.@type
, then set type/language value to
its associated value and set type/language to
@type
.@type
and set type/language value to @id
.@set
to containers.@none
to containers. This represents
the non-existence of a container mapping, and it will
be the last container mapping value to be checked as it
is the most generic.@null
. This is the key under which null values
are stored in the inverse context entry.@reverse
, append
@reverse
to preferred values.@id
or @reverse
and value has an @id
member:
@id
key in value for
iri, true for vocab, and
true for document relative has a
term definition in the active context
with an IRI mapping that equals the value associated
with the @id
key in value,
then append @vocab
, @id
, and
@none
, in that order, to preferred values.@id
, @vocab
, and
@none
, in that order, to preferred values.@none
, in
that order, to preferred values.:
),
then continue to the next term because
terms with colons can't be
used as prefixes.:
), and the substring of iri
that follows after the value of the
term definition's
IRI mapping.This algorithm, invoked via the IRI Compaction algorithm, makes use of an active context's inverse context to find the term that is best used to compact an IRI. Other information about a value associated with the IRI is given, including which container mappings and which type mapping or language mapping would be best used to express the value.
This section is non-normative.
The inverse context's entry for the IRI will be first searched according to the preferred container mappings, in the order that they are given. Amongst terms with a matching container mapping, preference will be given to those with a matching type mapping or language mapping, over those without a type mapping or language mapping. If there is no term with a matching container mapping then the term without a container mapping that matches the given type mapping or language mapping is selected. If there is still no selected term, then a term with no type mapping or language mapping will be selected if available. No term will be selected that has a conflicting type mapping or language mapping. Ties between terms that have the same mappings are resolved by first choosing the shortest terms, and then by choosing the lexicographically least term. Note that these ties are resolved automatically because they were previously resolved when the Inverse Context Creation algorithm was used to create the inverse context.
This algorithm has five required inputs. They are: an inverse context, a keyword or IRI iri, an array containers that represents an ordered list of preferred container mappings, a string type/language that indicates whether to look for a term with a matching type mapping or language mapping, and an array representing an ordered list of preferred values for the type mapping or language mapping to look for.
Expansion transforms all values into expanded form in JSON-LD. This algorithm performs the opposite operation, transforming a value into compacted form. This algorithm compacts a value according to the term definition in the given active context that is associated with the value's associated active property.
This section is non-normative.
The value to compact has either an @id
or an
@value
member.
For the former case, if the type mapping of
active property is set to @id
or @vocab
and value consists of only of an @id
member and, if
if the container mapping of active property
is set to @index
, an @index
member, value
can be compacted to a string by returning the result of
using the IRI Compaction algorithm
to compact the value associated with the @id
member.
Otherwise, value cannot be compacted and is returned as is.
For the latter case, it might be possible to compact value
just into the value associated with the @value
member.
This can be done if the active property has a matching
type mapping or language mapping and there
is either no @index
member or the container mapping
of active property is set to @index
. It can
also be done if @value
is the only member in value
(apart an @index
member in case the container mapping
of active property is set to @index
) and
either its associated value is not a string, there is
no default language, or there is an explicit
null language mapping for the
active property.
This algorithm has four required inputs: an active context, an inverse context, an active property, and a value to be compacted.
@index
member and the
container mapping associated to active property
is set to @index
, decrease number members by
1
.2
, return
value as it cannot be compacted.@id
member:
1
and
the type mapping of active property
is set to @id
, return the result of using the
IRI compaction algorithm,
passing active context, inverse context,
and the value of the @id
member for iri.1
and
the type mapping of active property
is set to @vocab
, return the result of using the
IRI compaction algorithm,
passing active context, inverse context,
the value of the @id
member for iri, and
true for vocab.@type
member whose
value matches the type mapping of active property,
return the value associated with the @value
member
of value.@language
member whose
value matches the language mapping of
active property, return the value associated with the
@value
member of value.1
and either
the value of the @value
member is not a string,
or the active context has no default language,
or the language mapping of active property
is set to null,, return the value associated with the
@value
member.This algorithm flattens an expanded JSON-LD document by collecting all properties of a node in a single JSON object and labeling all blank nodes with blank node identifiers. This resulting uniform shape of the document, may drastically simplify the code required to process JSON-LD data in certain applications.
This section is non-normative.
First, a node map is generated using the Node Map Generation algorithm which collects all properties of a node in a single JSON object. In the next step, the node map is converted to a JSON-LD document in flattened document form. Finally, if a context has been passed, the flattened document is compacted using the Compaction algorithm before being returned.
The algorithm takes two input variables, an element to flatten and an optional context used to compact the flattened document. If not passed, context is set to null.
@default
and whose value is
an empty JSON object.@default
member of node map, which is a JSON object representing
the default graph.@default
, perform the following steps:
@id
member whose value is set to graph name.@graph
member to entry and set it to an
empty array.@graph
member of entry.@graph
keyword (or its alias)
at the top-level, even if the context is empty or if there is only one element to
put in the @graph
array. This ensures that the returned
document has a deterministic structure.This algorithm creates a JSON object node map holding an indexed
representation of the graphs and nodes
represented in the passed expanded document. All nodes that are not
uniquely identified by an IRI get assigned a (new) blank node identifier.
The resulting node map will have a member for every graph in the document whose
value is another object with a member for every node represented in the document.
The default graph is stored under the @default
member, all other graphs are
stored under their graph name.
This section is non-normative.
The algorithm recursively runs over an expanded JSON-LD document to
collect all properties of a node
in a single JSON object. The algorithm constructs a
JSON object node map whose keys represent the
graph names used in the document
(the default graph is stored under the key @default
)
and whose associated values are JSON objects
which index the nodes in the
graph. If a
property's value is a node object,
it is replace by a node object consisting of only an
@id
member. If a node object has no @id
member or it is identified by a blank node identifier,
a new blank node identifier is generated. This relabeling
of blank node identifiers is
also be done for properties and values of
@type
.
The algorithm takes as input an expanded JSON-LD document element and a reference to
a JSON object node map. Furthermore it has the optional parameters
active graph (which defaults to @default
), an active subject,
active property, and a reference to a JSON object list. If
not passed, active subject, active property, and list are
set to null.
@type
member, perform for each
item the following steps:
@id
whose value is item.@value
member, perform the following steps:
@list
member of list.@list
member, perform
the following steps:
@list
whose value is initialized to an empty array.@list
member for element, active graph,
active subject, active property, and
result for list.@id
member, set id
to its value and remove the member from element. If id
is a blank node identifier, replace it with a newly
generated blank node identifier
passing id for identifier.@id
whose
value is id.@id
whose value is id.@list
member of list.@type
member, merge each of its values into the
@type
member of node and finally remove the
@type
member from element; the resulting
array must not contain any duplicate values.@index
member, set the @index
member of node to its value. If node has already an
@index
member with a different value, a
conflicting indexes
error has been detected and processing is aborted. Otherwise, continue by
removing the @index
member from element.@reverse
member:
@id
whose
value is id.@reverse
member of
element.@reverse
member from element.@graph
member, recursively invoke this
algorithm passing the value of the @graph
member for element,
node map, and id for active graph before removing
the @graph
member from element.This algorithm is used to generate new blank node identifiers or to relabel an existing blank node identifier to avoid collision by the introduction of new ones.
This section is non-normative.
The simplest case is if there exists already a blank node identifier
in the identifier map for the passed identifier, in which
case it is simply returned. Otherwise, a new blank node identifier
is generated by concatenating the string _:b
and the
counter. If the passed identifier is not null,
an entry is created in the identifier map associating the
identifier with the blank node identifier. Finally,
the counter is increased by one and the new
blank node identifier is returned.
The algorithm takes a single input variable identifier which may
be null. Between its executions, the algorithm needs to
keep an identifier map to relabel existing
blank node identifiers
consistently and a counter to generate new
blank node identifiers. The
counter is initialized to 0
by default.
_:b
and counter.1
.This section describes algorithms to transform a JSON-LD document to an RDF dataset and vice versa. The algorithms are designed for in-memory implementations with random access to JSON object elements.
Throughout this section, the following vocabulary prefixes are used in compact IRIs:
Prefix | IRI |
---|---|
rdf | http://www.w3.org/1999/02/22-rdf-syntax-ns# |
rdfs | http://www.w3.org/2000/01/rdf-schema# |
xsd | http://www.w3.org/2001/XMLSchema# |
This algorithms converts a JSON-LD document to an RDF dataset.
RDF does not currently allow a blank node identifier to be used as a graph name.
This section is non-normative.
The JSON-LD document is expanded and converted to a node map using the
Node Map Generation algorithm.
This allows each graph represented within the document to be
extracted and flattened, making it easier to process each
node object. Each graph from the node map
is processed to extract RDF triples,
to which any (non-default) graph name is applied to create an
RDF dataset. Each node object in the
node map has an @id
member which corresponds to the
RDF subject, the other members
represent RDF predicates. Each
member value is either an IRI or
blank node identifier or can be transformed to an
RDF literal
to generate an RDF triple. Lists
are transformed into an
RDF Collection
using the List to RDF Conversion algorithm.
The algorithm takes a JSON-LD document element and returns an RDF dataset.
@type
, then for each
type in values, append a triple
composed of subject, rdf:type
,
and type to triples.@list
key from
item and list triples. Append first a
triple composed of subject,
property, and list head to triples and
finally append all triples from
list triples to triples.@default
, add
triples to the default graph in dataset.This algorithm takes a node object or value object and transforms it into an RDF resource to be used as the object of an RDF triple.
This section is non-normative.
Value objects are transformed to RDF literals as defined in the section Data Round Tripping whereas node objects are transformed to IRIs or blank node identifiers.
The algorithm takes as its sole argument item which must be either a value object or node object.
@id
member.@value
member in item.
@type
member of item or null
if
item does not have such a member.xsd:boolean
.xsd:integer
or xsd:double
, depending
on if the value contains a fractional and/or an exponential
component.xsd:string
or rdf:langString
, depending on if
item has an @language
member.@language
member and datatype is
rdf:langString
, then add the value associated with the
@language
key as the language of literal.List Conversion is the process of taking a list object and transforming it into an RDF Collection as defined in RDF Semantics [RDF-MT].
This section is non-normative.
For each element of the list a new blank node identifier
is allocated which is used to generate rdf:first
and
rdf:rest
triples. The
algorithm returns the list head, which is either the the first allocated
blank node identifier or rdf:nil
if the
list is empty.
The algorithm takes two inputs: an array list and an empty array list triples used for returning the generated triples.
rdf:nil
.rdf:first
, and the result of using th
Object to RDF Conversion algorithm
passing item to list triples.rdf:nil
. Append a
triple composed of subject,
rdf:rest
, and rest to list triples.rdf:nil
if bnodes is empty.This algorithm converts an RDF dataset consisting of a default graph and zero or more named graphs into a JSON-LD document.
In some cases, data exists natively in the form of triples or triples; for example, if the data was originally represented in an RDF dataset. This algorithm is designed to simply translate an array of triples into a JSON-LD document.
This algorithm does not support lists containing lists.
This section is non-normative.
Iterate through each graph in the dataset, converting RDF Collections into a list and generating a JSON-LD document in expanded form for all RDF literals, IRIs and blank node identifiers.
The algorithm takes a single parameter dataset in the form of an array of an RDF dataset.
nodeMap
and listMap
,
whose value is an an empty JSON object.@default
whose value is set to
reference default graph.nodeMap
member of default graph
using the variable default graph nodes.@default
, otherwise to the
graph name associated with graph.nodeMap
and listMap
, whose value
is an an empty JSON object.@id
whose value is name.nodeMap
member in
graph object using the variable node map and the
value of the listMap
member using the variable
list map.rdf:first
,
first
member of
the subject member of list map to the result of the
RDF to Object Conversion algorithm,
passing object.rdf:rest
:
rest
member of
the subject member of list map to
object, which is either an absolute IRI
or blank node identifier.@id
whose value is
set to subject.rdf:type
, and object
is an IRI or blank node identifier,
append object to the value of the @type
member of node. If no such member exists, create one
and initialize it to an array whose only item is
object. Finally, continue to the next
RDF triple.head
member of the object
member of list map to a reference of value.
This reference may be required later to replace the
value in the predicate member of node
with a list object.listMap
member in
graph object using the variable list map.listMap
member of
graph object:
head
and an
first
member it does not represent the head of
a list. Continue with the next key-value pair.head
member in entry
using the variable value.@id
member from value.@list
member to value and initialize
it to an array containing the value of the
first
member of entry.rest
member
of entry is not rdf:nil
:
rest
member of entry.first
member of entry to the @list
member
of value.@graph
member to node and initialize
its value to an empty array.nodeMap
member of the subject
member of graph map using the variable node map.@graph
member of node.This algorithm transforms an RDF literal to a JSON-LD value object and a RDF blank node or IRI to an JSON-LD node object.
This section is non-normative.
RDF literals are transformed to value objects as defined in the section Data Round Tripping whereas IRIs and blank node identifiers are transformed to node objects.
This algorithm takes as single input variable value that is converted to a JSON object.
rdf:nil
return a new
JSON object consisting of a single member
@list
whose value is set to an empty
array. This is behavior is required by the
Convert from RDF algorithm.@id
whose value is set to value.xsd:boolean
, set
converted value to true if the
lexical form
of value matches true
, or false
if
it matches false
.xsd:integer
or
xsd:double
, try to convert the literal to a
JSON number. If the conversion is
successful, store the result in converted value.@language
to result and set its value to the
language tag
of value.xsd:string
which is ignored.@value
to result whose value
is set to converted value.@type
to result whose value is set to type.When converting JSON-LD to RDF JSON-native types such as
numbers and booleans are automatically coerced to
xsd:integer
, xsd:double
, or xsd:boolean
.
Implementers MUST ensure that the result is in canonical lexical form. A
canonical lexical form is a set of literals from among the valid set of literals for
a datatype such that there is a one-to-one mapping between the canonical lexical form
and a value in the value space as defined in [XMLSCHEMA11-2]. In other words, every
value MUST be converted to a deterministic string representation.
The canonical lexical form of an integer, i.e., a number without fractions
or a number coerced to xsd:integer
, is a finite-length sequence of decimal
digits (0-9
) with an optional leading minus sign; leading zeros are prohibited.
To convert the number in JavaScript, implementers can use the following snippet of code:
(value).toFixed(0).toString()
The canonical lexical form of a double, i.e., a number with fractions
or a number coerced to xsd:double
, consists of a mantissa followed by the
character "E", followed by an exponent. The mantissa MUST be a decimal number. The exponent
MUST be an integer. Leading zeros and a preceding plus sign (+
) are prohibited
in the exponent. If the exponent is zero, it must be indicated by E0
.
For the mantissa, the preceding optional plus sign is prohibited and the decimal point is
required. Leading and trailing zeros are prohibited subject to the following: number
representations must be normalized such that there is a single digit which is non-zero to the
left of the decimal point and at least a single digit to the right of the decimal point unless
the value being represented is zero. The canonical representation for zero is 0.0E0
.
xsd:double
's value space is defined by the IEEE double-precision 64-bit
floating point type [IEEE-754-1985]; in JSON-LD the mantissa is rounded to 15 digits after the
decimal point.
To convert the number in JavaScript, implementers can use the following snippet of code:
(value).toExponential(15).replace(/(\d)0*e\+?/,'$1E')
When data such as decimals need to be normalized, JSON-LD authors should
not use values that are going to undergo automatic conversion. This is due to the lossy nature
of xsd:double
values. Authors should instead use the expanded object form to
set the canonical lexical form directly.
The canonical lexical form of the boolean values true and false
are the strings true
and false
.
When JSON-native numbers, are type coerced, lossless data round-tripping can not
be guaranteed as rounding errors might occur. Additionally, only literals typed as
xsd:integer
, xsd:double
, and xsd:boolean
are
automatically converted back to their JSON-native counterparts in when
converting from RDF.
Some JSON serializers, such as PHP's native implementation in some versions,
backslash-escape the forward slash character. For example, the value
http://example.com/
would be serialized as http:\/\/example.com\/
.
This is problematic as other JSON parsers might not understand those escaping characters.
There is no need to backslash-escape forward slashes in JSON-LD. To aid interoperability
between JSON-LD processors, a JSON-LD serializer MUST NOT backslash-escape forward slashes.
This API provides a clean mechanism that enables developers to convert JSON-LD data into a a variety of output formats that are often easier to work with. A conformant JSON-LD Processor MUST implement the entirety of the following API.
The JSON-LD Processor interface is the high-level programming structure that developers use to access the JSON-LD transformation methods.
It is important to highlight that conformant
JSON-LD processors MUST NOT modify
the input parameters. If an error is detected, the callback is
invoked passing a JsonLdError
with the corresponding error
code
and processing is stopped.
[Constructor]
interface JsonLdProcessor {
void expand ((object or object[] or DOMString) input, JsonLdCallback
callback, optional JsonLdOptions
? options);
void compact ((object or object[] or DOMString) input, (object or DOMString)? context, JsonLdCallback
callback, optional JsonLdOptions
? options);
void flatten ((object or object[] or DOMString) input, (object or DOMString)? context, JsonLdCallback
callback, optional JsonLdOptions
? options);
};
compact
Compacts the given input
using the
context
according to the steps in the
Compaction algorithm:
application/ld+json
or application/json
or
if the document cannot be parsed as JSON, invoke the callback passing an
loading document failed
error.expandContext
has been passed, update the active context using the
Context Processing algorithm, passing the
expandContext
as local context.application/json
and an HTTP Link Header [RFC5988] using the
http://www.w3.org/ns/json-ld#context
link relation, update the
active context using the
Context Processing algorithm, passing the
context referenced in the HTTP Link Header as local context.compactArrays
flag in options.Parameter | Type | Nullable | Optional | Description |
---|---|---|---|---|
input | (object or object[] or DOMString) | ✘ | ✘ | The JSON-LD object or array of JSON-LD objects to perform the compaction upon or an IRI referencing the JSON-LD document to compact. |
context | (object or DOMString) | ✔ | ✘ | The context to use when compacting the input ; either in the
form of a JSON object or as IRI. |
callback |
| ✘ | ✘ | A callback that is called when processing completed successfully
on the given input , or a fatal error prevented
processing from completing. |
options |
| ✔ | ✔ | A set of options to configure the algorithms. This allows, e.g., to set the input document's base IRI. |
void
expand
Expands the given input
according to
the steps in the Expansion algorithm:
application/ld+json
or application/json
or
if the document cannot be parsed as JSON, invoke the callback passing an
loading document failed
error.expandContext
has been passed, update the active context using the
Context Processing algorithm, passing the
expandContext
as local context.application/json
and an HTTP Link Header [RFC5988] using the
http://www.w3.org/ns/json-ld#context
link relation, update the
active context using the
Context Processing algorithm, passing the
context referenced in the HTTP Link Header as local context.Parameter | Type | Nullable | Optional | Description |
---|---|---|---|---|
input | (object or object[] or DOMString) | ✘ | ✘ | The JSON-LD object or array of JSON-LD objects to perform the expansion upon or an IRI referencing the JSON-LD document to expand. |
callback |
| ✘ | ✘ | A callback that is called when processing completed successfully
on the given input , or a fatal error prevented
processing from completing. |
options |
| ✔ | ✔ | A set of options to configure the used algorithms such. This allows, e.g., to set the input document's base IRI. |
void
flatten
Flattens the given input
and
compacts it using the passed context
according to the steps in the Flattening algorithm:
application/ld+json
or application/json
or
if the document cannot be parsed as JSON, invoke the callback passing an
loading document failed
error.expandContext
has been passed, update the active context using the
Context Processing algorithm, passing the
expandContext
as local context.application/json
and an HTTP Link Header [RFC5988] using the
http://www.w3.org/ns/json-ld#context
link relation, update the
active context using the
Context Processing algorithm, passing the
context referenced in the HTTP Link Header as local context.0
)
to be used by the
Generate Blank Node Identifier algorithm.compactArrays
flag in options (which is internally passed to the
Compaction algorithm).Parameter | Type | Nullable | Optional | Description |
---|---|---|---|---|
input | (object or object[] or DOMString) | ✘ | ✘ | The JSON-LD object or array of JSON-LD objects or an IRI referencing the JSON-LD document to flatten. |
context | (object or DOMString) | ✔ | ✘ | The context to use when compacting the flattened input ; either
in the form of a JSON object or as IRI. If
null is passed, the result will not be compacted but kept
in expanded form. |
callback |
| ✘ | ✘ | A callback that is called when processing completed successfully
on the given input , or a fatal error prevented
processing from completing. |
options |
| ✔ | ✔ | A set of options to configure the used algorithms such. This allows, e.g., to set the input document's base IRI. |
void
JSON-LD processors utilize callbacks in order to exchange information in an asynchronous manner with applications. This section details the parameters of those callbacks.
The JsonLdCallback
is called when an API method of
JsonLdProcessor
has been completed, either successfully or
by a fatal error.
callback JsonLdCallback = void (JsonLdError
error, object or object[] document);
JsonLdCallback
Parameterserror
of type JsonLdError
document
of type array of object or objectThe LoadContextCallback
defines the callback that custom context loaders
have to implement to be used to retrieve remote contexts.
callback LoadContextCallback = void (DOMString url, ContextLoadedCallback
callback);
LoadContextCallback
Parametersurl
of type DOMStringcallback
of type ContextLoadedCallback
The ContextLoadedCallback
is called in response to a call
of the LoadContextCallback
.
callback ContextLoadedCallback = void (JsonLdError
error, DOMString url, DOMString context);
ContextLoadedCallback
Parameterserror
of type JsonLdError
JsonLdErrorCode
of
loading remote context failed
.url
of type DOMStringcontext
of type DOMStringThis section describes datatype definitions used within the JSON-LD API.
The JsonLdOptions
type is used to pass various options to the
JsonLdProcessor
methods.
dictionary JsonLdOptions {
DOMString base;
boolean compactArrays = true;
LoadContextCallback
loadContext;
object or DOMString expandContext = null;
DOMString processingMode = "json-ld-1.0";
};
JsonLdOptions
Membersbase
of type DOMStringThe default value of this option
implies that all IRIs that cannot be compacted otherwise are transformed to relative IRIs
during compaction. To avoid that data is being lost, developers thus have to store the
base IRI along with the compacted document. This might be problematic in practice and
thus the default behavior might be changed in future. Furthermore, the relationship
of this option to the @base
keyword (which is at risk) should be further
investigated.
compactArrays
of type boolean, defaulting to true
true
, the JSON-LD processor replaces arrays with just
one element with that element during compaction. If set to false
,
all arrays will remain arrays even if they have just one element.
expandContext
of type object or DOMString, defaulting to null
loadContext
of type LoadContextCallback
processingMode
of type DOMString, defaulting to "json-ld-1.0"
json-ld-1.0
, the JSON-LD Processor MUST produce
exactly the same results as the algorithms defined in this specification.
If set to another value, the JSON-LD Processor is allowed to extend
or modify the algorithms defined in this specification to enable
application-specific optimizations. The definition of such
optimizations is beyond the scope of this specification and thus
not defined. Consequently, different implementations MAY implement
different optimizations. Developers MUST NOT define modes beginning
with json-ld
as they are reserved for future versions
of this specification.The JsonLdError
type is used to report processing errors
to a JsonLdCallback
.
dictionary JsonLdError {
JsonLdErrorCode
code;
DOMString? message;
};
JsonLdError
Memberscode
of type JsonLdErrorCode
message
of type DOMString, nullableThe JsonLdErrorCode
represents the collection of valid JSON-LD error
codes.
enum JsonLdErrorCode {
"loading document failed",
"list of lists",
"invalid @index value",
"conflicting indexes",
"invalid @id value",
"invalid local context",
"loading remote context failed",
"invalid remote context",
"recursive context inclusion",
"invalid base IRI",
"invalid vocab mapping",
"invalid default language",
"keyword redefinition",
"invalid term definition",
"invalid reverse property",
"invalid IRI mapping",
"cyclic IRI mapping",
"invalid keyword alias",
"invalid type mapping",
"invalid language mapping",
"colliding keywords",
"invalid container mapping",
"invalid type value",
"invalid value object",
"invalid value object value",
"invalid language-tagged string",
"invalid language-tagged value",
"invalid typed value",
"invalid set or list object",
"invalid language map value",
"compaction to list of lists",
"invalid reverse property map",
"invalid @reverse value",
"invalid reverse property value"
};
Enumeration description | |
---|---|
loading document failed | The document could not be loaded or parsed as JSON. |
list of lists | A list of lists was detected. List of lists are not supported in this version of JSON-LD due to the algorithmic complexity associated with conversion to RDF. |
invalid @index value | An @index member was encountered whose value was
not a string. |
conflicting indexes | Multiple conflicting indexes have been found for the same node. |
invalid @id value | An @id member was encountered whose value was not a
string. |
invalid local context | In invalid local context was detected. |
loading remote context failed | There was a problem encountered loading a remote context. |
invalid remote context | No valid context document has been found for a referenced, remote context. |
recursive context inclusion | A cycle in remote context inclusions has been detected. |
invalid base IRI | An invalid base IRI has been detected, i.e., it is neither an absolute IRI nor null. |
invalid vocab mapping | An invalid vocabulary mapping has been detected, i.e., it is neither an absolute IRI nor null. |
invalid default language | The value of the default language is not a string or null and thus invalid. |
keyword redefinition | A keyword redefinition has been detected. |
invalid term definition | An invalid term definition has been detected. |
invalid reverse property | An invalid reverse property definition has been detected. |
invalid IRI mapping | A local context contains a term that has an invalid or missing IRI mapping. |
cyclic IRI mapping | A cycle in IRI mappings has been detected. |
invalid keyword alias | An invalid keyword alias definition has been encountered. |
invalid type mapping | An @type member in a term definition
was encountered whose value could not be expanded to an
absolute IRI. |
invalid language mapping | An @language member in a term definition
was encountered whose value was neither a string nor
null and thus invalid. |
colliding keywords | Two properties which expand to the same keyword have been detected. This might occur if a keyword and an an alias thereof are used at the same time. |
invalid container mapping | An @container member was encountered whose value was
not one of the following strings:
@list , @set , or @index . |
invalid type value | An invalid value for an @type member has been detected,
i.e., the value was neither a string nor an array
of strings. |
invalid value object | A value object with disallowed members has been detected. |
invalid value object value | An invalid value for the @value member of a
value object has been detected, i.e., it is neither
a scalar nor null. |
invalid language-tagged string | A language-tagged string with an invalid language value was detected. |
invalid language-tagged value | A number, true, or false with an associated language tag was detected. |
invalid typed value | A typed value with an invalid type was detected. |
invalid set or list object | A set object or list object with disallowed members has been detected. |
invalid language map value | An invalid value in a language map has been detected. It has to be a string or an array of strings. |
compaction to list of lists | The compacted document contains a list of lists as multiple lists have been compacted to the same term. |
invalid reverse property map | An invalid reverse property map has been detected. No
keywords apart from @context
are allowed in reverse property maps. |
invalid @reverse value | An invalid value for an @reverse member has been detected,
i.e., the value was not a JSON object. |
invalid reverse property value | An invalid value for a reverse property has been detected. The value of an inverse property must be a node object. |
This section is non-normative.
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 Niklas Lindström, François Daoust, Lin Clark, and Zdenko 'Denny' Vrandečić. The editors would like to thank Mark Birbeck, who provided a great deal of the initial push behind the JSON-LD work via his work on RDFj. The work of Dave Lehn and Mike Johnson are appreciated for reviewing, and performing several implementations of the specification. Ian Davis is thanked for his work on RDF/JSON. Thanks also to Nathan Rixham, Bradley P. Allen, Kingsley Idehen, Glenn McDonald, Alexandre Passant, Danny Ayers, Ted Thibodeau Jr., Olivier Grisel, Josh Mandel, Eric Prud'hommeaux, David Wood, Guus Schreiber, Pat Hayes, Sandro Hawke, and Richard Cyganiak or their input on the specification.