RDF

Dgrpah natively supports Resource Description Framework (RDF) when creating, importing and exporting data. Dgraph Client libraries can be used to query RDF as well.

RDF 1.1 is a Semantic Web Standard for data interchange defined by the W3C. It expresses statements about resources. The format of these statements is simple and in the form of triples.

A triple has the form

<subject> <predicate> <object> .

In RDF terminology, each triple represents one fact about a node.

In Dgraph, the <subject> of a triple is always a node, and must be a numeric UID. The <object> of a triple may be another node or a literal value:

<0x01> <name> "Alice" .
<0x01> <knows> <0x02> .

The first triple specifies that a node has a name property of “Alice”. The subject is the UID of the first node, the predicate is name, and the object is the literal value string: "Alice". The second triple specifies that Alice knows Bob. The subject is again the UID of a node (the “alice” node), the predicate is knows, and the object of this triple is the uid of the other node (the “bob” node). When the object is a UID, the triple represents a relationship in Dgraph.

Each triple representation in RDF ends with a period.

Blank nodes in mutations

When creating nodes in Dgraph, you often let Dgraph assign the node UID by specifing a blank node starting with “_:”. All references to the same blank node, such as _:identifier123, will identify the same node within a mutation. Dgraph creates a UID identifying each blank node.

Language for string values

Languages are written using @lang. For example

<0x01> <name> "Adelaide"@en .
<0x01> <name> "Аделаида"@ru .
<0x01> <name> "Adélaïde"@fr .
<0x01> <dgraph.type> "Person" .

See also how language strings are handled in queries.

Types

Dgraph understands standard RDF types specified in RDF using the ^^ separator. For example

<0x01> <age> "32"^^<xs:int> .
<0x01> <birthdate> "1985-06-08"^^<xs:dateTime> .

The supported RDF datatypes and the corresponding internal Dgraph type are as follows.

Facets

Dgraph is more expressive than RDF in that it allows properties to be stored on every relation. These properties are called Facets in Dgraph, and dgraph allows an extension to RDF where facet values are incuded in any triple.

Creating a list with facets

The following set operation uses a sequence of RDF statements with additional facet information:

{
  set {
    _:Julian <name> "Julian" .
    _:Julian <nickname> "Jay-Jay" (kind="first") .
    _:Julian <nickname> "Jules" (kind="official") .
    _:Julian <nickname> "JB" (kind="CS-GO") .
  }
}

{
  q(func: eq(name,"Julian")){
    name
    nickname @facets
  }
}

Result:

{
  "data": {
    "q": [
      {
        "name": "Julian",
        "nickname|kind": {
          "0": "first",
          "1": "official",
          "2": "CS-GO"
        },
        "nickname": [
          "Jay-Jay",
          "Jules",
          "JB"
        ]
      }
    ]
  }
}