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JSON [RFC4627] has proven to be a highly useful object serialization and messaging format. In an attempt to harmonize the representation of Linked Data in JSON, this specification outlines a common JSON representation format for expressing directed graphs; mixing both Linked Data and non-Linked Data in a single document.
This document is merely a public working draft of a potential specification. It has no official standing of any kind and does not represent the support or consensus of any standards organisation.
This document is an experimental work in progress.
JSON, as specified in [RFC4627], is a simple language for representing data on the Web. Linked Data is a technique for creating a graph of interlinked data across different documents or Web sites. Data entities are described using IRIs, which are typically dereferencable and thus may be used to find more information about an entity, creating a "Web of Knowledge". JSON-LD is intended to be a simple publishing method for expressing not only Linked Data in JSON, but also for adding semantics to existing JSON.
JSON-LD is designed as a light-weight syntax that can be used to express Linked Data. It is primarily intended to be a way to use Linked Data in Javascript and other Web-based programming environments. It is also useful when building interoperable Web services and when storing Linked Data in JSON-based document storage engines. It is practical and designed to be as simple as possible, utilizing the large number of JSON parsers and libraries available today. It is designed to be able to express key-value pairs, RDF data, RDFa [RDFA-CORE] data, Microformats [MICROFORMATS] data, and Microdata [MICRODATA]. That is, it supports every major Web-based structured data model in use today.
The syntax does not necessarily require applications to change their JSON, but allows to easily add meaning by adding context in a way that is either in-band or out-of-band. The syntax is designed to not disturb already deployed systems running on JSON, but provide a smooth upgrade path from JSON to JSON with added semantics. Finally, the format is intended to be easy to parse, efficient to generate, convertible to RDF in one pass, and require a very small memory footprint in order to operate.
This document is a detailed specification for a serialization of Linked Data in JSON. 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]. 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 [RDF-CONCEPTS].
Examples may contain references to existing vocabularies and use prefixes to refer to Web Vocabularies. The following is a list of all vocabularies and their prefix abbreviations, as used in this document:
dc, e.g., dc:title)foaf, e.g., foaf:knows)rdf, e.g., rdf:type)xsd, e.g., xsd:integer)JSON [RFC4627] defines several terms which are used throughout this document:
There are a number of ways that one may participate in the development of this specification:
The following section outlines the design goals and rationale behind the JSON-LD markup language.
A number of design considerations were explored during the creation of this markup language:
The following definition for Linked Data is the one that will be used for this specification.
Note that the definition for Linked Data above is silent on the topic of unlabeled nodes. Unlabeled nodes are not considered Linked Data. However, this specification allows for the expression of unlabled nodes, as most graph-based data sets on the Web contain a number of associated nodes that are not named and thus are not directly de-referenceable.
An Internationalized Resource Identifier (IRI), as described in [RFC3987], is a mechanism for representing unique identifiers on the web. In Linked Data, an IRI is commonly used for expressing a subject, a property or an object.
JSON-LD defines a mechanism to map JSON terms, i.e., keys and values, to IRIs. This does not mean that JSON-LD requires every key or value to be an IRI, but rather ensures that keys and values can be mapped to IRIs if the developer desires to transform their data into Linked Data. There are a few techniques that can ensure that developers will generate good Linked Data for the Web. JSON-LD formalizes those techniques.
We will be using the following JSON markup as the example for the rest of this section:
{
"name": "Manu Sporny",
"homepage": "http://manu.sporny.org/",
"avatar": "http://twitter.com/account/profile_image/manusporny"
}
In JSON-LD, a context is used to map terms, i.e., keys and values
in an JSON document, to
IRIs. A term is a short word that may be expanded
to an IRI. The Web uses IRIs for unambiguous identification. The
idea is that these terms mean something that may be of use to
other developers and that it is useful to give them an unambiguous identifier.
That is, it is useful for terms to expand to IRIs so that
developers don't accidentally step on each other's Web Vocabulary terms.
For example, the term name may map directly to the IRI
http://xmlns.com/foaf/0.1/name. This allows JSON-LD documents to
be constructed using the common JSON practice of simple name/value pairs while
ensuring that the data is useful outside of the page, API or database in which it
resides.
These Linked Data terms are typically collected in a context document that would look something like this:
{
"name": "http://xmlns.com/foaf/0.1/name",
"homepage": "http://xmlns.com/foaf/0.1/homepage",
"avatar": "http://xmlns.com/foaf/0.1/avatar"
}
This context document can then be used in an JSON-LD document by adding a single line. The JSON markup as shown in the previous section could be changed as follows to link to the context document:
{
"@context": "http://example.org/json-ld-contexts/person",
"name": "Manu Sporny",
"homepage": "http://manu.sporny.org/",
"avatar": "http://twitter.com/account/profile_image/manusporny"
}
The additions above transform the previous JSON document into a JSON document
with added semantics because the @context specifies how the
name, homepage, and avatar
terms map to IRIs.
Mapping those keys to IRIs gives the data global context. If two
developers use the same IRI to describe a property, they are more than likely
expressing the same concept. This allows both developers to re-use each others
data without having to agree to how their data will inter-operate on a
site-by-site basis. Contexts may also contain datatype information
for certain terms as well as other processing instructions for
the JSON-LD processor.
Contexts may be specified in-line. This ensures that JSON-LD documents can be processed when a JSON-LD processor does not have access to the Web.
{
"@context": {
"name": "http://xmlns.com/foaf/0.1/name",
"homepage": "http://xmlns.com/foaf/0.1/homepage",
"avatar": "http://xmlns.com/foaf/0.1/avatar"
},
"name": "Manu Sporny",
"homepage": "http://manu.sporny.org/",
"avatar": "http://twitter.com/account/profile_image/manusporny"
}
JSON-LD strives to ensure that developers don't have to change the JSON that is going into and being returned from their Web APIs. This means that developers can also specify a context for JSON data in an out-of-band fashion. This is described later in this document.
JSON-LD uses a special type of machine-readable document called a Web Vocabulary to define terms that are then used to describe concepts and "things" in the world. Typically, these Web Vocabulary documents have prefixes associated with them and contain a number of term declarations. A prefix, like a term, is a short word that expands to a Web Vocabulary base IRI. Prefixes are helpful when a developer wants to mix multiple vocabularies together in a context, but does not want to go to the trouble of defining every single term in every single vocabulary. Some Web Vocabularies may have dozens of terms defined. If a developer wants to use 3-4 different vocabularies, the number of terms that would have to be declared in a single context could become quite large. To reduce the number of different terms that must be defined, JSON-LD also allows prefixes to be used to compact IRIs.
For example, the IRI http://xmlns.com/foaf/0.1/
specifies a Web Vocabulary which may be represented using the
foaf prefix. The foaf Web Vocabulary
contains a term called name. If you join the
foaf prefix with the name suffix,
you can build a compact IRI that will expand out into an absolute IRI for the
http://xmlns.com/foaf/0.1/name vocabulary term.
That is, the compact IRI, or short-form, is foaf:name and the
expanded-form is http://xmlns.com/foaf/0.1/name. This vocabulary
term is used to specify a person's name.
Developers, and machines, are able to use this IRI (plugging it directly into a web browser, for instance) to go to the term and get a definition of what the term means. Much like we can use WordNet today to see the definition of words in the English language. Developers and machines need the same sort of definition of terms. IRIs provide a way to ensure that these terms are unambiguous.
The context provides a collection of vocabulary terms and prefixes that can be used to expand JSON keys and values into IRIs.
To ensure the best possible performance, it is a best practice to put the context definition at the top of the JSON-LD document. If it isn't listed first, processors have to save each key-value pair until the context is processed. This creates a memory and complexity burden for one-pass processors.
If a set of terms such as, name, homepage, and avatar, are defined in a context, and that context is used to resolve the names in JSON objects, machines are able to automatically expand the terms to something meaningful and unambiguous, like this:
{
"http://xmlns.com/foaf/0.1/name": "Manu Sporny",
"http://xmlns.com/foaf/0.1/homepage": "http://manu.sporny.org"
"http://rdfs.org/sioc/ns#avatar": "http://twitter.com/account/profile_image/manusporny"
}
Doing this allows JSON to be unambiguously machine-readable without requiring developers to drastically change their workflow.
Please note that this JSON-LD document doesn't define the subject and will thus result in an unlabeled or blank node.
JSON-LD is designed to ensure that Linked Data concepts can be marked up in a way that is simple to understand and author by Web developers. In many cases, regular JSON markup can become Linked Data with the simple addition of a context. As more JSON-LD features are used, more semantics are added to the JSON markup.
Expressing IRIs are fundamental to Linked Data as that is how most subjects and many object are named. IRIs can be expressed in a variety of different ways in JSON-LD.
@context and when dealing with keys that
start with the @subject character.@subject,
if it is a string.@type.@iri
keyword.@coerce rules in
effect for a key named @iri.IRIs can be expressed directly in the key position like so:
{
...
"http://xmlns.com/foaf/0.1/name": "Manu Sporny",
...
}
In the example above, the key
http://xmlns.com/foaf/0.1/name is interpreted as an IRI, as
opposed to being interpreted as a string.
Term expansion occurs for IRIs if a term is defined within the active context:
{
"@context": {"name": "http://xmlns.com/foaf/0.1/name"},
...
"name": "Manu Sporny",
...
}
Prefixes are expanded when used in keys:
{
"@context": {"foaf": "http://xmlns.com/foaf/0.1/"},
...
"foaf:name": "Manu Sporny",
...
}
foaf:name above will automatically expand out to the IRI
http://xmlns.com/foaf/0.1/name.
An IRI is generated when a value is associated with a key using
the @iri keyword:
{
...
"homepage": { "@iri": "http://manu.sporny.org" }
...
}
If type coercion rules are specified in the @context for
a particular vocabulary term, an IRI is generated:
{
"@context":
{
...
"@coerce":
{
"@iri": "homepage"
}
}
...
"homepage": "http://manu.sporny.org/",
...
}
Even though the value http://manu.sporny.org/ is a string,
the type coercion rules will transform the value into an IRI when processed
by a JSON-LD Processor
To be able to externally reference nodes, it is important that each node has an unambiguous identifier. IRIs are a fundamental concept of Linked Data, and nodes should have a de-referencable identifier used to name and locate them. For nodes to be truely linked, de-referencing the identifier should result in a representation of that node. Associating an IRI with a node tells an application that the returned document contains a description of the node requested.
JSON-LD documents may also contain descriptions of other nodes, so it is necessary to be able to uniquely identify each node which may be externally referenced.
A subject
of an object in JSON is declared using the @subject key. The subject is the
first piece of information needed by the JSON-LD processor in order to
create the (subject, property, object) tuple, also known as a triple.
{
...
"@subject": "http://example.org/people#joebob",
...
}
The example above would set the subject to the IRI
http://example.org/people#joebob.
To ensure the best possible performance, it is a best practice to
put the @subject key before other key-value pairs in an object. If
it isn't listed first, processors have to save each key-value pair until
@subject is processed before they can create valid triples. This
creates a memory and complexity burden for one-pass processors.
The type of a particular subject can be specified using the
@type key. Specifying the type in this way will generate a
triple of the form (subject, type, type-iri).
To be Linked Data, types must be uniquely identified by an IRI.
{
...
"@subject": "http://example.org/people#joebob",
"@type": "http://xmlns.com/foaf/0.1/Person",
...
}
The example above would generate the following triple if the JSON-LD document is mapped to RDF (in N-Triples notation):
<http://example.org/people#joebob>
<http://www.w3.org/1999/02/22-rdf-syntax-ns#type>
<http://xmlns.com/foaf/0.1/Person> .
Regular text strings, also referred to as plain literals, are easily expressed using regular JSON strings.
{
...
"name": "Mark Birbeck",
...
}
JSON-LD makes an assumption that strings with associated language encoding information are not very common when used in JavaScript and Web Services. Thus, it takes a little more effort to express strings with associated language information.
{
...
"name":
{
"@literal": "花澄",
"@language": "ja"
}
...
}
The example above would generate a plain literal for
花澄 and associate the ja language code with the triple
that is generated. Languages must be expressed in [BCP47] format.
A value with an associated datatype, also known as a typed literal, is indicated by associating a literal with an IRI which indicates the literal's datatype. Typed literals may be expressed in JSON-LD in three ways:
@coerce keyword.The first example uses the @coerce keyword to express a
typed literal:
{
"@context":
{
"modified": "http://purl.org/dc/terms/modified",
"dateTime": "http://www.w3.org/2001/XMLSchema#dateTime"
"@coerce":
{
"dateTime": "modified"
}
}
...
"modified": "2010-05-29T14:17:39+02:00",
...
}
The second example uses the expanded form for specifying objects:
{
...
"modified":
{
"@literal": "2010-05-29T14:17:39+02:00",
"@datatype": "dateTime"
}
...
}
Both examples above would generate an object with the literal value of
2010-05-29T14:17:39+02:00 and the datatype of
http://www.w3.org/2001/XMLSchema#dateTime.
The third example uses a built-in native JSON type, a number, to express a datatype:
{
...
"@subject": "http://example.org/people#joebob",
"age": 31
...
}
The example above would generate the following triple:
<http://example.org/people#joebob>
<http://xmlns.com/foaf/0.1/age>
"31"^^<http://www.w3.org/2001/XMLSchema#integer> .
A JSON-LD author can express multiple triples in a compact way by using arrays. If a subject has multiple values for the same property, the author may express each property as an array.
In JSON-LD, multiple objects on a property are not ordered. This is because typically graphs are not inherently ordered data structures. To see more on creating ordered collections in JSON-LD, see Lists.
{
...
"@subject": "http://example.org/people#joebob",
"nick": ["joe", "bob", "jaybee"],
...
}
The markup shown above would generate the following triples:
<http://example.org/people#joebob>
<http://xmlns.com/foaf/0.1/nick>
"joe" .
<http://example.org/people#joebob>
<http://xmlns.com/foaf/0.1/nick>
"bob" .
<http://example.org/people#joebob>
<http://xmlns.com/foaf/0.1/nick>
"jaybee" .
Multiple typed literals may also be expressed using the expanded form for objects:
{
...
"@subject": "http://example.org/articles/8",
"modified":
[
{
"@literal": "2010-05-29T14:17:39+02:00",
"@datatype": "dateTime"
},
{
"@literal": "2010-05-30T09:21:28-04:00",
"@datatype": "dateTime"
}
]
...
}
The markup shown above would generate the following triples:
<http://example.org/articles/8>
<http://purl.org/dc/terms/modified>
"2010-05-29T14:17:39+02:00"^^http://www.w3.org/2001/XMLSchema#dateTime .
<http://example.org/articles/8>
<http://purl.org/dc/terms/modified>
"2010-05-30T09:21:28-04:00"^^http://www.w3.org/2001/XMLSchema#dateTime .
Expansion is the process of taking a JSON-LD document and applying a context such that all IRI, datatypes, and literal values are expanded so that the context is no longer necessary. JSON-LD document expansion is typically used as a part of Framing or Normalization.
For example, assume the following JSON-LD input document:
{
"@context":
{
"name": "http://xmlns.com/foaf/0.1/name",
"homepage": "http://xmlns.com/foaf/0.1/homepage",
"@coerce":
{
"@iri": "homepage"
}
},
"name": "Manu Sporny",
"homepage": "http://manu.sporny.org/"
}
Running the JSON-LD Expansion algorithm against the JSON-LD input document provided above would result in the following output:
{
"http://xmlns.com/foaf/0.1/name": "Manu Sporny",
"http://xmlns.com/foaf/0.1/homepage":
{
"@iri": "http://manu.sporny.org/"
}
}
Compaction is the process of taking a JSON-LD document and applying a context such that the most compact form of the document is generated. JSON is typically expressed in a very compact, key-value format. That is, full IRIs are rarely used as keys. At times, a JSON-LD document may be received that is not in its most compact form. JSON-LD, via the API, provides a way to compact a JSON-LD document.
For example, assume the following JSON-LD input document:
{
"http://xmlns.com/foaf/0.1/name": "Manu Sporny",
"http://xmlns.com/foaf/0.1/homepage":
{
"@iri": "http://manu.sporny.org/"
}
}
Additionally, assume the following developer-supplied JSON-LD context:
{
"name": "http://xmlns.com/foaf/0.1/name",
"homepage": "http://xmlns.com/foaf/0.1/homepage",
"@coerce":
{
"@iri": "homepage"
}
}
Running the JSON-LD Compaction algorithm given the context supplied above against the JSON-LD input document provided above would result in the following output:
{
"@context":
{
"name": "http://xmlns.com/foaf/0.1/name",
"homepage": "http://xmlns.com/foaf/0.1/homepage",
"@coerce":
{
"@iri": "homepage"
}
},
"name": "Manu Sporny",
"homepage": "http://manu.sporny.org/"
}
The compaction algorithm also enables the developer to map any expanded
format into an application-specific compacted format. While the context
provided above mapped http://xmlns.com/foaf/0.1/name to
name, it could have also mapped it to any arbitrary string
provided by the developer.
A JSON-LD document is a representation of a directed graph. A single directed graph can have many different serializations, each expressing exactly the same information. Developers typically work with trees, represented as JSON objects. While mapping a graph to a tree can be done, the layout of the end result must be specified in advance. A Frame can be used by a developer on a JSON-LD document to specify a deterministic layout for a graph.
Framing is the process of taking a JSON-LD document, which expresses a graph of information, and applying a specific graph layout (called a Frame).
The JSON-LD document below expresses a library, a book and a chapter:
{
"@context": {
"Book": "http://example.org/vocab#Book",
"Chapter": "http://example.org/vocab#Chapter",
"contains": "http://example.org/vocab#contains",
"creator": "http://purl.org/dc/terms/creator"
"description": "http://purl.org/dc/terms/description"
"Library": "http://example.org/vocab#Library",
"title": "http://purl.org/dc/terms/title",
"@coerce":
{
"@iri": "contains"
},
},
"@subject":
[{
"@subject": "http://example.com/library",
"@type": "Library",
"contains": "http://example.org/library/the-republic"
},
{
"@subject": "http://example.org/library/the-republic",
"@type": "Book",
"creator": "Plato",
"title": "The Republic",
"contains": "http://example.org/library/the-republic#introduction"
},
{
"@subject": "http://example.org/library/the-republic#introduction",
"@type": "Chapter",
"description": "An introductory chapter on The Republic.",
"title": "The Introduction"
}]
}
Developers typically like to operate on items in a hierarchical, tree-based fashion. Ideally, a developer would want the data above sorted into top-level libraries, then the books that are contained in each library, and then the chapters contained in each book. To achieve that layout, the developer can define the following frame:
{
"@context": {
"Book": "http://example.org/vocab#Book",
"Chapter": "http://example.org/vocab#Chapter",
"contains": "http://example.org/vocab#contains",
"creator": "http://purl.org/dc/terms/creator"
"description": "http://purl.org/dc/terms/description"
"Library": "http://example.org/vocab#Library",
"title": "http://purl.org/dc/terms/title"
},
"@type": "Library",
"contains": {
"@type": "Book",
"contains": {
"@type": "Chapter"
}
}
}
When the framing algorithm is run against the previously defined JSON-LD document, paired with the frame above, the following JSON-LD document is the end result:
{
"@context": {
"Book": "http://example.org/vocab#Book",
"Chapter": "http://example.org/vocab#Chapter",
"contains": "http://example.org/vocab#contains",
"creator": "http://purl.org/dc/terms/creator"
"description": "http://purl.org/dc/terms/description"
"Library": "http://example.org/vocab#Library",
"title": "http://purl.org/dc/terms/title"
},
"@subject": "http://example.org/library",
"@type": "Library",
"contains": {
"@subject": "http://example.org/library/the-republic",
"@type": "Book",
"creator": "Plato",
"title": "The Republic",
"contains": {
"@subject": "http://example.org/library/the-republic#introduction",
"@type": "Chapter",
"description": "An introductory chapter on The Republic.",
"title": "The Introduction"
},
},
}
The JSON-LD framing algorithm allows developers to query by example and force a specific tree layout to a JSON-LD document.
JSON-LD has a number of features that provide functionality above and beyond the core functionality described above. The following sections outline the features that are specific to JSON-LD.
Authors may choose to declare JSON-LD contexts in external
documents to promote re-use of contexts as well as reduce the size of JSON-LD
documents.
In order to use an external context, an author may specify an IRI to a valid
JSON-LD document. If an IRI is specified, the external document must be
dereferenced and the top-level @context key in the
JSON Object must be overlayed on top of the current
active context.
The following example demonstrates the use of an external context:
{
"@context": "http://example.org/json-ld-contexts/person",
"name": "Manu Sporny",
"homepage": "http://manu.sporny.org/",
"avatar": "http://twitter.com/account/profile_image/manusporny"
}
Authors may also import multiple contexts by specifying a list of contexts to import:
{
"@context": ["http://example.org/json-ld-contexts/person", "http://example.org/json-ld-contexts/event"]
"name": "Manu Sporny",
"homepage": "http://manu.sporny.org/",
"avatar": "http://twitter.com/account/profile_image/manusporny"
"celebrates":
{
"@type": "Event",
"description": "International Talk Like a Pirate Day",
"date": "R/2011-09-19"
}
}
Each context in a list will be evaluated in-order. Duplicate values must be overwritten on a last-defined-overrides basis. The context list must contain either de-referenceable IRIs or JSON Objects that conform to the context syntax as described in this document.
External JSON-LD context documents may contain extra information located
outside of the @context key, such as
documentation about the prefixes declared in the document. It is
also recommended that a human-readable document encoded in HTML+RDFa
[HTML-RDFA] or other Linked Data compatible format is served as well to
explain the correct usage of the JSON-LD context document.
Vocabulary terms in Linked Data documents may draw from a number of different Web vocabularies. At times, declaring every single term that a document uses can require the developer to declare tens, if not hundreds of potential vocabulary terms that may be used across an application. This is a concern for at least three reasons; the first is the cognitive load on the developer, the second is the serialized size of the context, the third is future-proofing application contexts. In order to address these issues, the concept of a prefix mechanism is introduced.
A prefix is a compact way of expressing a base
IRI to a Web Vocabulary.
Generally, these prefixes are used by concatenating the prefix and
a term separated by a colon (:).
The prefix is a short string that identifies a particular Web vocabulary.
For example, the prefix foaf may be used as a short
hand for the Friend-of-a-Friend Web 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 full IRI for the vocabulary term. For example,
foaf:name would be expanded out to the IRI
http://xmlns.com/foaf/0.1/name. Instead of having to remember
and type out the entire IRI, the developer can instead use the prefix in
their JSON-LD markup.
The ability to use prefixes reduces the need for developers
to declare every vocabulary term that they intend to use in
the JSON-LD context. This reduces document serialization size because
every vocabulary term need not be declared in the context.
Prefix also
reduce the cognitive load on the developer. It is far easier to
remember foaf:name than it is to remember
http://xmlns.com/foaf/0.1/name. The use of prefixes also
ensures that a context document does not have to be updated in lock-step
with an externally defined Web Vocabulary. Without prefixes, a developer
would need to keep their application context terms in lock-step with an
externally defined Web Vocabulary. Rather, by just declaring the
Web Vocabulary prefix, one can use new terms as they're declared
without having to update the application's JSON-LD context.
Consider the following example:
{
"@context": {
"dc": "http://purl.org/dc/elements/1.1/",
"ex": "http://example.org/vocab#"
},
"@subject": "http://example.org/library",
"@type": "ex:Library",
"ex:contains": {
"@subject": "http://example.org/library/the-republic",
"@type": "ex:Book",
"dc:creator": "Plato",
"dc:title": "The Republic",
"ex:contains": {
"@subject": "http://example.org/library/the-republic#introduction",
"@type": "ex:Chapter",
"dc:description": "An introductory chapter on The Republic.",
"dc:title": "The Introduction"
},
},
}
In this example, two different vocabularies are referred to using
prefixes. Those prefixes are then used as type and property values using
the prefix:term notation.
Prefixes, also known as CURIEs, are defined more formally in RDFa Core 1.1, Section 6 "CURIE Syntax Definition" [RDFA-CORE]. JSON-LD does not support the square-bracketed CURIE syntax as the mechanism is not required to disambiguate IRIs in a JSON-LD document like it is in HTML documents.
Since JSON is capable of expressing typed information such as doubles, integers, and boolean values. As demonstrated below, JSON-LD utilizes that information to create typed literals:
{
...
// The following two values are automatically converted to a type of xsd:double
// and both values are equivalent to each other.
"measure:cups": 5.3,
"measure:cups": 5.3e0,
// The following value is automatically converted to a type of xsd:double as well
"space:astronomicUnits": 6.5e73,
// The following value should never be converted to a language-native type
"measure:stones": { "@literal": "4.8", "@datatype": "xsd:decimal" },
// This value is automatically converted to having a type of xsd:integer
"chem:protons": 12,
// This value is automatically converted to having a type of xsd:boolean
"sensor:active": true,
...
}
When dealing with a number of modern programming languages,
including JavaScript ECMA-262, there is no distinction between
xsd:decimal and xsd:double values. That is,
the number 5.3 and the number
5.3e0 are treated as if they were the same. When converting from
JSON-LD to a language-native format and back, datatype information is lost in a
number of these languages. Thus, one could say that 5.3 is a
xsd:decimal and 5.3e0 is an
xsd:double in JSON-LD, but when both values are
converted to a language-native format the datatype difference between the two
is lost because the machine-level representation will almost always be a
double.
Implementers should be aware of this potential round-tripping issue between
xsd:decimal and xsd:double. Specifically
objects with a datatype of xsd:decimal must not be converted
to a language native type.
JSON-LD supports the coercion of values to particular data types. Type coercion allows someone deploying JSON-LD to coerce the incoming or outgoing types to the proper data type based on a mapping of data type IRIs to property types. Using type coercion, one may convert simple JSON data to properly typed RDF data.
The example below demonstrates how a JSON-LD author can coerce values to plain literals, typed literals and IRIs.
{
"@context":
{
"rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#",
"xsd": "http://www.w3.org/2001/XMLSchema#",
"name": "http://xmlns.com/foaf/0.1/name",
"age": "http://xmlns.com/foaf/0.1/age",
"homepage": "http://xmlns.com/foaf/0.1/homepage",
"@coerce":
{
"xsd:integer": "age",
"@iri": "homepage"
}
},
"name": "John Smith",
"age": "41",
"homepage": "http://example.org/home/"
}
The example above would generate the following triples:
_:bnode1
<http://xmlns.com/foaf/0.1/name>
"John Smith" .
_:bnode1
<http://xmlns.com/foaf/0.1/age>
"41"^^http://www.w3.org/2001/XMLSchema#integer .
_:bnode1
<http://xmlns.com/foaf/0.1/homepage>
<http://example.org/home/> .
Object chaining is a JSON-LD feature that allows an author to use the definition of JSON-LD objects as property values. This is a commonly used mechanism for creating a parent-child relationship between two subjects.
The example shows an two subjects related by a property from the first subject:
{
...
"name": "Manu Sporny",
"knows": {
"@type": "Person",
"name": "Gregg Kellogg",
}
...
}
An object definition, like the one used above, may be used as a JSON value at any point in JSON-LD.
At times, it becomes necessary to be able to express information without
being able to specify the subject. Typically, this type of node is called
an unlabeled node or a blank node. In JSON-LD, unlabeled node identifiers are
automatically created if a subject is not specified using the
@subject keyword. However, authors may provide identifiers for
unlabeled nodes by using the special _ (underscore)
prefix. This allows to reference the node locally within the
document but not in an external document.
{
...
"@subject": "_:foo",
...
}
The example above would set the subject to _:foo, which can
then be used later on in the JSON-LD markup to refer back to the
unlabeled node. This practice, however, is usually frowned upon when
generating Linked Data. If a developer finds that they refer to the unlabeled
node more than once, they should consider naming the node using a resolve-able
IRI.
JSON-LD allows all of the syntax keywords, except for @context,
to be aliased. This feature allows more legacy JSON content to be supported
by JSON-LD. It also allows developers to design domain-specific implementations
using only the JSON-LD context.
{
"@context":
{
"url": "@subject",
"a": "@type",
"name": "http://schema.org/name"
},
"url": "http://example.com/about#gregg",
"a": "http://schema.org/Person",
"name": "Gregg Kellogg"
}
In the example above, the @subject and @type
keywords have been given the aliases url and
a, respectively.
Normalization is the process of taking JSON-LD input and performing a deterministic transformation on that input that results in a JSON-LD output that any conforming JSON-LD processor would have generated given the same input. The problem is a fairly difficult technical problem to solve because it requires a directed graph to be ordered into a set of nodes and edges in a deterministic way. This is easy to do when all of the nodes have unique names, but very difficult to do when some of the nodes are not labeled.
Normalization is useful when comparing two graphs against one another, when generating a detailed list of differences between two graphs, and when generating a cryptographic digital signature for information contained in a graph or when generating a hash of the information contained in a graph.
The example below is an un-normalized JSON-LD document:
{
"@context":
{
"name": "http://xmlns.com/foaf/0.1/name",
"homepage": "http://xmlns.com/foaf/0.1/homepage",
"xsd": "http://www.w3.org/2001/XMLSchema#",
"@coerce":
{
"@iri": ["homepage"]
}
},
"name": "Manu Sporny",
"homepage": "http://manu.sporny.org/"
}
The example below is the normalized form of the JSON-LD document above:
Whitespace is used below to aid readability. The normalization algorithm for JSON-LD removes all unnecessary whitespace in the fully normalized form.
[{
"@subject":
{
"@iri": "_:c14n0"
},
"http://xmlns.com/foaf/0.1/homepage":
{
"@iri": "http://manu.sporny.org/"
},
"http://xmlns.com/foaf/0.1/name": "Manu Sporny"
}]
Notice how all of the terms have been expanded and sorted in alphabetical order. Also, notice how the subject has been labeled with a blank node identifier. Normalization ensures that any arbitrary graph containing exactly the same information would be normalized to exactly the same form shown above.
The JSON-LD markup examples below demonstrate how JSON-LD can be used to express semantic data marked up in other languages such as RDFa, Microformats, and Microdata. These sections are merely provided as proof that JSON-LD is very flexible in what it can express across different Linked Data approaches.
The following example describes three people with their respective names and homepages.
<div prefix="foaf: http://xmlns.com/foaf/0.1/"> <ul> <li typeof="foaf:Person"> <a rel="foaf:homepage" href="http://example.com/bob/" property="foaf:name" >Bob</a> </li> <li typeof="foaf:Person"> <a rel="foaf:homepage" href="http://example.com/eve/" property="foaf:name" >Eve</a> </li> <li typeof="foaf:Person"> <a rel="foaf:homepage" href="http://example.com/manu/" property="foaf:name" >Manu</a> </li> </ul> </div>
An example JSON-LD implementation is described below, however, there are other ways to mark-up this information such that the context is not repeated.
{
"@context": { "foaf": "http://xmlns.com/foaf/0.1/"},
"@subject": [
{
"@subject": "_:bnode1",
"@type": "foaf:Person",
"foaf:homepage": "http://example.com/bob/",
"foaf:name": "Bob"
},
{
"@subject": "_:bnode2",
"@type": "foaf:Person",
"foaf:homepage": "http://example.com/eve/",
"foaf:name": "Eve"
},
{
"@subject": "_:bnode3",
"@type": "foaf:Person",
"foaf:homepage": "http://example.com/manu/",
"foaf:name": "Manu"
}
]
}
The following example uses a simple Microformats hCard example to express how the Microformat is represented in JSON-LD.
<div class="vcard"> <a class="url fn" href="http://tantek.com/">Tantek Çelik</a> </div>
The representation of the hCard expresses the Microformat terms in the
context and uses them directly for the url and fn
properties. Also note that the Microformat to JSON-LD processor has
generated the proper URL type for http://tantek.com.
{
"@context":
{
"vcard": "http://microformats.org/profile/hcard#vcard",
"url": "http://microformats.org/profile/hcard#url",
"fn": "http://microformats.org/profile/hcard#fn",
"@coerce": { "@iri": "url" }
},
"@subject": "_:bnode1",
"@type": "vcard",
"url": "http://tantek.com/",
"fn": "Tantek Çelik"
}
The Microdata example below expresses book information as a Microdata Work item.
<dl itemscope
itemtype="http://purl.org/vocab/frbr/core#Work"
itemid="http://purl.oreilly.com/works/45U8QJGZSQKDH8N">
<dt>Title</dt>
<dd><cite itemprop="http://purl.org/dc/terms/title">Just a Geek</cite></dd>
<dt>By</dt>
<dd><span itemprop="http://purl.org/dc/terms/creator">Wil Wheaton</span></dd>
<dt>Format</dt>
<dd itemprop="http://purl.org/vocab/frbr/core#realization"
itemscope
itemtype="http://purl.org/vocab/frbr/core#Expression"
itemid="http://purl.oreilly.com/products/9780596007683.BOOK">
<link itemprop="http://purl.org/dc/terms/type" href="http://purl.oreilly.com/product-types/BOOK">
Print
</dd>
<dd itemprop="http://purl.org/vocab/frbr/core#realization"
itemscope
itemtype="http://purl.org/vocab/frbr/core#Expression"
itemid="http://purl.oreilly.com/products/9780596802189.EBOOK">
<link itemprop="http://purl.org/dc/terms/type" href="http://purl.oreilly.com/product-types/EBOOK">
Ebook
</dd>
</dl>
Note that the JSON-LD representation of the Microdata information stays true to the desires of the Microdata community to avoid contexts and instead refer to items by their full IRI.
[
{
"@subject": "http://purl.oreilly.com/works/45U8QJGZSQKDH8N",
"@type": "http://purl.org/vocab/frbr/core#Work",
"http://purl.org/dc/terms/title": "Just a Geek",
"http://purl.org/dc/terms/creator": "Whil Wheaton",
"http://purl.org/vocab/frbr/core#realization":
["http://purl.oreilly.com/products/9780596007683.BOOK", "http://purl.oreilly.com/products/9780596802189.EBOOK"]
},
{
"@subject": "http://purl.oreilly.com/products/9780596007683.BOOK",
"@type": "http://purl.org/vocab/frbr/core#Expression",
"http://purl.org/dc/terms/type": "http://purl.oreilly.com/product-types/BOOK"
},
{
"@subject": "http://purl.oreilly.com/products/9780596802189.EBOOK",
"@type": "http://purl.org/vocab/frbr/core#Expression",
"http://purl.org/dc/terms/type": "http://purl.oreilly.com/product-types/EBOOK"
}
]
Developers would also benefit by allowing other vocabularies to be used automatically with their JSON API. There are over 200 Web Vocabulary Documents that are available for use on the Web today. Some of these vocabularies are:
You can use these vocabularies in combination, like so:
{
"@type": "foaf:Person",
"foaf:name": "Manu Sporny",
"foaf:homepage": "http://manu.sporny.org/",
"sioc:avatar": "http://twitter.com/account/profile_image/manusporny"
}
Developers can also specify their own Vocabulary documents by modifying the
active context in-line using the @context keyword,
like so:
{
"@context": { "myvocab": "http://example.org/myvocab#" },
"@type": "foaf:Person",
"foaf:name": "Manu Sporny",
"foaf:homepage": "http://manu.sporny.org/",
"sioc:avatar": "http://twitter.com/account/profile_image/manusporny",
"myvocab:personality": "friendly"
}
The @context keyword is used to change how the JSON-LD
processor evaluates key-value pairs. In this case, it was used to
map one string ('myvocab') to another string, which is interpreted as
a IRI. In the example above, the myvocab string is replaced
with "http://example.org/myvocab#" when it
is detected. In the example above, "myvocab:personality" would
expand to "http://example.org/myvocab#personality".
This mechanism is a short-hand, called a Web Vocabulary prefix, and provides developers an unambiguous way to map any JSON value to RDF.
This section is included merely for standards community review and will be submitted to the Internet Engineering Steering Group if this specification becomes a W3C Recommendation.
formcompacted, expanded,
framed, and normalized. Other values are
allowed, but must be pre-pended with a x- string until
they are clearly defined by a stable specification. If no form
is specified in an HTTP request header to a responding application,
such as a Web server, the application may choose any form. If no
form is specified for a receiving application, the form must not
be assumed to take any particular form.application/json MIME media type.eval()
function. It is recommended that a conforming parser does not attempt to
directly evaluate the JSON-LD serialization and instead purely parse the
input into a language-native data structure. 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, Dave Longley, Dave Lehn and Mike Johnson who reviewed, provided feedback, and performed several implementations of the specification, and Ian Davis, who created RDF/JSON. Thanks also to Nathan Rixham, Bradley P. Allen, Kingsley Idehen, Glenn McDonald, Alexandre Passant, Danny Ayers, Ted Thibodeau Jr., Olivier Grisel, Niklas Lindström, Markus Lanthaler, and Richard Cyganiak for their input on the specification. Another huge thank you goes out to Dave Longley who designed many of the algorithms used in this specification, including the normalization algorithm which was a monumentally difficult design challenge.