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JSON2RDF

Streaming generic JSON to RDF converter

Reads JSON data and streams N-Triples output. The conversion algorithm is similar to that of JSON-LD but accepts arbitrary JSON and does not require a @context.

The resulting RDF representation is lossless with the exception of array ordering and some datatype round-tripping. The lost ordering should not be a problem in the majority of cases, as RDF applications tend to impose their own value-based ordering using SPARQL ORDER BY.

A common use case is feeding the JSON2RDF output into a triplestore or SPARQL processor and using a SPARQL CONSTRUCT query to map the generic RDF to more specific RDF that uses terms from some vocabulary. SPARQL is an inherently more flexible RDF mapping mechanism than JSON-LD @context.

Build

mvn clean install

That should produce an executable JAR file target/json2rdf-1.0.1-jar-with-dependencies.jar in which dependency libraries will be included.

Usage

The JSON data is read from stdin, the resulting RDF data is written to stdout.

JSON2RDF is available as a .jar as well as a Docker image atomgraph/json2rdf (recommended).

Parameters:

  • base - the base URI for the data. Property namespace is constructed by adding # to the base URI.

Options:

  • --input-charset - JSON input encoding, by default UTF-8
  • --output-charset - RDF output encoding, by default UTF-8

Examples

JSON2RDF output is streaming and produces N-Triples, therefore we pipe it through riot to get a more readable Turtle output.


Bob DuCharme's blog post on using JSON2RDF: Converting JSON to RDF.


JSON data in ordinary-json-document.json

{
  "name": "Markus Lanthaler",
  "homepage": "http://www.markus-lanthaler.com/",
  "image": "http://twitter.com/account/profile_image/markuslanthaler"
}

Java execution from shell:

cat ordinary-json-document.json | java -jar json2rdf-1.0.1-jar-with-dependencies.jar https://localhost/ | riot --formatted=TURTLE

Alternatively, Docker execution from shell:

cat ordinary-json-document.json | docker run -i -a stdin -a stdout -a stderr atomgraph/json2rdf https://localhost/ | riot --formatted=TURTLE

Note that using Docker you need to bind stdin/stdout/stderr streams.

Turtle output

[ <https://localhost/#homepage>  "http://www.markus-lanthaler.com/" ;
  <https://localhost/#image>     "http://twitter.com/account/profile_image/markuslanthaler" ;
  <https://localhost/#name>      "Markus Lanthaler"
] .

The following SPARQL query can be used to map this generic RDF to the desired target RDF, e.g. a structure that uses schema.org vocabulary.

BASE <https://localhost/>
PREFIX : <#>
PREFIX schema: <http://schema.org/>

CONSTRUCT
{
  ?person schema:homepage ?homepage ;
    schema:image ?image ;
    schema:name ?name .
}
{
  ?person :homepage ?homepageStr ;
    :image ?imageStr ;
    :name ?name .
  BIND (URI(?homepageStr) AS ?homepage)
  BIND (URI(?imageStr) AS ?image)
}

Turtle output after the mapping

[ <http://schema.org/homepage>  <http://www.markus-lanthaler.com/> ;
  <http://schema.org/image>     <http://twitter.com/account/profile_image/markuslanthaler> ;
  <http://schema.org/name>      "Markus Lanthaler"
] .

JSON data in city-distances.json

{
  "desc"    : "Distances between several cities, in kilometers.",
  "updated" : "2014-02-04T18:50:45",
  "uptodate": true,
  "author"  : null,
  "cities"  : {
    "Brussels": [
      {"to": "London",    "distance": 322},
      {"to": "Paris",     "distance": 265},
      {"to": "Amsterdam", "distance": 173}
    ],
    "London": [
      {"to": "Brussels",  "distance": 322},
      {"to": "Paris",     "distance": 344},
      {"to": "Amsterdam", "distance": 358}
    ],
    "Paris": [
      {"to": "Brussels",  "distance": 265},
      {"to": "London",    "distance": 344},
      {"to": "Amsterdam", "distance": 431}
    ],
    "Amsterdam": [
      {"to": "Brussels",  "distance": 173},
      {"to": "London",    "distance": 358},
      {"to": "Paris",     "distance": 431}
    ]
  }
}

Java execution from shell:

cat city-distances.json | java -jar json2rdf-1.0.1-jar-with-dependencies.jar https://localhost/ | riot --formatted=TURTLE

Alternatively, Docker execution from shell:

cat city-distances.json | docker run -i -a stdin -a stdout -a stderr atomgraph/json2rdf https://localhost/ | riot --formatted=TURTLE

Turtle output

[ <https://localhost/#cities>    [ <https://localhost/#Amsterdam>  [ <https://localhost/#distance>  "431"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "Paris"
                                                                   ] ;
                                   <https://localhost/#Amsterdam>  [ <https://localhost/#distance>  "358"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "London"
                                                                   ] ;
                                   <https://localhost/#Amsterdam>  [ <https://localhost/#distance>  "173"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "Brussels"
                                                                   ] ;
                                   <https://localhost/#Brussels>   [ <https://localhost/#distance>  "322"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "London"
                                                                   ] ;
                                   <https://localhost/#Brussels>   [ <https://localhost/#distance>  "265"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "Paris"
                                                                   ] ;
                                   <https://localhost/#Brussels>   [ <https://localhost/#distance>  "173"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "Amsterdam"
                                                                   ] ;
                                   <https://localhost/#London>     [ <https://localhost/#distance>  "358"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "Amsterdam"
                                                                   ] ;
                                   <https://localhost/#London>     [ <https://localhost/#distance>  "322"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "Brussels"
                                                                   ] ;
                                   <https://localhost/#London>     [ <https://localhost/#distance>  "344"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "Paris"
                                                                   ] ;
                                   <https://localhost/#Paris>      [ <https://localhost/#distance>  "431"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "Amsterdam"
                                                                   ] ;
                                   <https://localhost/#Paris>      [ <https://localhost/#distance>  "344"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "London"
                                                                   ] ;
                                   <https://localhost/#Paris>      [ <https://localhost/#distance>  "265"^^<http://www.w3.org/2001/XMLSchema#int> ;
                                                                     <https://localhost/#to>        "Brussels"
                                                                   ]
                                 ] ;
  <https://localhost/#desc>      "Distances between several cities, in kilometers." ;
  <https://localhost/#updated>   "2014-02-04T18:50:45" ;
  <https://localhost/#uptodate>  true
] .

Performance

Largest dataset tested so far: 2.95 GB / 30459482 lines of JSON to 4.5 GB / 21964039 triples in 2m10s. Hardware: x64 Windows 10 PC with Intel Core i5-7200U 2.5 GHz CPU and 16 GB RAM.

Dependencies