[{"_1":2,"_176":-5,"_177":-5},"loaderData",{"_3":4,"_13":14,"_21":22,"_155":156},"root",{"_5":-5,"_6":-7,"_7":8,"_9":-7,"_10":11,"_12":-7},"currentUser","primaryEmail","siteVerification","6LeIxAcTAAAAAJcZVRqyHh71UMIEGNQ_MXjiZKhI","toast","enableDev",false,"incidentStatus","routes/_layout",{"_15":-5,"_16":17,"_18":17,"_19":11,"_20":11},"username","isAskGordonEnabled",true,"isUsingNewTemplate","showMinimalLanding","showHoneypotTrap","routes/_layout.r.$namespace.$reponame",{"_23":24,"_25":-5,"_26":11,"_27":11,"_28":29,"_30":31,"_32":-5,"_33":11,"_34":35,"_84":85,"_108":109,"_146":-5,"_147":11,"_148":17,"_149":11,"_150":-5,"_151":11,"_152":-5,"_153":154},"canonicalUrl","https://hub.docker.com/r/atomgraph/json2rdf/tags","mcpServer","canSeeDockerfile","canSeeAutobuilds","namespace","atomgraph","reponame","json2rdf","cloudBuildSource","isAutobuildsAvailable","repo",{"_36":37,"_38":39,"_41":42,"_43":44,"_45":11,"_46":47,"_48":49,"_50":51,"_53":31,"_28":29,"_54":55,"_56":40,"_57":58,"_59":58,"_60":61,"_62":-5,"_63":64,"_65":66,"_67":11,"_68":29,"_69":70,"_75":11,"_76":77,"_81":29,"_82":83},"categories",[],"content_types",[40],"image","date_registered","2019-08-14T22:58:52.75602Z","description","Streaming generic JSON to RDF converter","is_private","last_updated","2023-08-31T19:15:10.739734Z","last_modified","2024-10-16T13:48:34.145251Z","media_types",[52],"application/vnd.docker.container.image.v1+json","name","pull_count",1448,"repository_type","star_count",1,"status","status_description","active","source","collaborator_count",0,"full_description","# JSON2RDF\nStreaming generic JSON to RDF converter\n\nReads JSON data and streams N-Triples output. The conversion algorithm is similar to that of [JSON-LD](https://www.w3.org/TR/json-ld11-api/) but accepts arbitrary JSON and does not require a `@context`.\n\nThe resulting RDF representation is lossless with the exception of array ordering and some [datatype round-tripping](https://www.w3.org/TR/json-ld11-api/#data-round-tripping).\nThe 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`.\n\nA 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.\nSPARQL is an inherently more flexible RDF mapping mechanism than JSON-LD `@context`.\n\n## Build\n\n mvn clean install\n\nThat should produce an executable JAR file `target/json2rdf-jar-with-dependencies.jar` in which dependency libraries will be included.\n\n## Usage\n\nThe JSON data is read from `stdin`, the resulting RDF data is written to `stdout`.\n\nJSON2RDF is available as a `.jar` as well as a Docker image [atomgraph/json2rdf](https://hub.docker.com/r/atomgraph/json2rdf) (recommended).\n\nParameters:\n* `base` - the base URI for the data. Property namespace is constructed by adding `#` to the base URI.\n\nOptions:\n* `--input-charset` - JSON input encoding, by default UTF-8\n* `--output-charset` - RDF output encoding, by default UTF-8\n\n## Examples\n\nJSON2RDF output is streaming and produces N-Triples, therefore we pipe it through [`riot`](https://jena.apache.org/documentation/io/) to get a more readable Turtle output.\n\n***\n\nBob DuCharme's blog post on using JSON2RDF: [Converting JSON to RDF](http://www.bobdc.com/blog/json2rdf/).\n\n***\n\nJSON data in [`ordinary-json-document.json`](https://www.w3.org/TR/json-ld11/#interpreting-json-as-json-ld)\n```json\n{\n \"name\": \"Markus Lanthaler\",\n \"homepage\": \"http://www.markus-lanthaler.com/\",\n \"image\": \"http://twitter.com/account/profile_image/markuslanthaler\"\n}\n```\n\nJava execution from shell:\n\n```bash\ncat ordinary-json-document.json | java -jar json2rdf-jar-with-dependencies.jar https://localhost/ | riot --formatted=TURTLE\n```\n\nAlternatively, Docker execution from shell:\n```bash\ncat ordinary-json-document.json | docker run --rm -i -a stdin -a stdout -a stderr atomgraph/json2rdf https://localhost/ | riot --formatted=TURTLE\n```\n\nNote that using Docker you need to [bind](https://docs.docker.com/engine/reference/commandline/run/#attach-to-stdinstdoutstderr--a) `stdin`/`stdout`/`stderr` streams.\n\nTurtle output\n\n```turtle\n[ \"http://www.markus-lanthaler.com/\" ;\n \"http://twitter.com/account/profile_image/markuslanthaler\" ;\n \"Markus Lanthaler\"\n] .\n```\n\nThe following SPARQL query can be used to map this generic RDF to the desired target RDF, e.g. a structure that uses [schema.org](https://schema.org) vocabulary.\n\n```sparql\nBASE \nPREFIX : <#>\nPREFIX schema: \n\nCONSTRUCT\n{\n ?person schema:homepage ?homepage ;\n schema:image ?image ;\n schema:name ?name .\n}\n{\n ?person :homepage ?homepageStr ;\n :image ?imageStr ;\n :name ?name .\n BIND (URI(?homepageStr) AS ?homepage)\n BIND (URI(?imageStr) AS ?image)\n}\n```\n\nTurtle output after the mapping\n\n```turtle\n[ ;\n ;\n \"Markus Lanthaler\"\n] .\n```\n\n***\n\nJSON data in [`city-distances.json`](https://www.w3.org/TR/xslt-30/#json-to-xml-mapping)\n\n```json\n{\n \"desc\" : \"Distances between several cities, in kilometers.\",\n \"updated\" : \"2014-02-04T18:50:45\",\n \"uptodate\": true,\n \"author\" : null,\n \"cities\" : {\n \"Brussels\": [\n {\"to\": \"London\", \"distance\": 322},\n {\"to\": \"Paris\", \"distance\": 265},\n {\"to\": \"Amsterdam\", \"distance\": 173}\n ],\n \"London\": [\n {\"to\": \"Brussels\", \"distance\": 322},\n {\"to\": \"Paris\", \"distance\": 344},\n {\"to\": \"Amsterdam\", \"distance\": 358}\n ],\n \"Paris\": [\n {\"to\": \"Brussels\", \"distance\": 265},\n {\"to\": \"London\", \"distance\": 344},\n {\"to\": \"Amsterdam\", \"distance\": 431}\n ],\n \"Amsterdam\": [\n {\"to\": \"Brussels\", \"distance\": 173},\n {\"to\": \"London\", \"distance\": 358},\n {\"to\": \"Paris\", \"distance\": 431}\n ]\n }\n}\n```\n\nJava execution from shell:\n```bash\ncat city-distances.json | java -jar json2rdf-jar-with-dependencies.jar https://localhost/ | riot --formatted=TURTLE\n```\n\nAlternatively, Docker execution from shell:\n```bash\ncat city-distances.json | docker run --rm -i -a stdin -a stdout -a stderr atomgraph/json2rdf https://localhost/ | riot --formatted=TURTLE\n```\n\nTurtle output\n\n```turtle\n[ [ [ \"431\"^^ ;\n \"Paris\"\n ] ;\n [ \"358\"^^ ;\n \"London\"\n ] ;\n [ \"173\"^^ ;\n \"Brussels\"\n ] ;\n [ \"322\"^^ ;\n \"London\"\n ] ;\n [ \"265\"^^ ;\n \"Paris\"\n ] ;\n [ \"173\"^^ ;\n \"Amsterdam\"\n ] ;\n [ \"358\"^^ ;\n \"Amsterdam\"\n ] ;\n [ \"322\"^^ ;\n \"Brussels\"\n ] ;\n [ \"344\"^^ ;\n \"Paris\"\n ] ;\n [ \"431\"^^ ;\n \"Amsterdam\"\n ] ;\n [ \"344\"^^ ;\n \"London\"\n ] ;\n [ \"265\"^^ ;\n \"Brussels\"\n ]\n ] ;\n \"Distances between several cities, in kilometers.\" ;\n \"2014-02-04T18:50:45\" ;\n true\n] .\n```\n### Mapping Twitter export to RDF\n\nYou can [download your Twitter data](https://twitter.com/settings/download_your_data) which includes tweets in `tweets.js`. Remove the `window.YTD.tweets.part0 = ` string and save the rest as `tweets.json`.\n\nTo get the RDF output, save the following query as `tweets.rq`\n\n```sparql\nBASE \nPREFIX : <#>\nPREFIX xsd: \nPREFIX sioc: \nPREFIX dct: \n\nCONSTRUCT\n{\n ?tweet a sioc:Post ;\n sioc:id ?id ;\n dct:created ?created ;\n sioc:content ?content ;\n sioc:reply_of ?reply_of .\n}\n{\n ?tweet_obj :id ?id ;\n :created_at ?created_at_string ;\n :full_text ?content .\n OPTIONAL\n {\n ?tweet_obj :in_reply_to_status_id ?in_reply_to_status_id ;\n :in_reply_to_screen_name ?in_reply_to_screen_name .\n BIND(URI(CONCAT(?in_reply_to_screen_name, \"/status/\", ?in_reply_to_status_id)) AS ?reply_of)\n }\n\n BIND(\"atomgraphhq\" AS ?username)\n BIND(URI(CONCAT(?username, \"/status/\", ?id)) AS ?tweet)\n BIND(SUBSTR(?created_at_string, 27, 4) AS ?year_string)\n BIND(SUBSTR(?created_at_string, 5, 3) AS ?month_string)\n BIND(SUBSTR(?created_at_string, 9, 2) AS ?day_string)\n VALUES (?month_string ?month_number_string)\n {\n (\"Jan\" \"01\")\n (\"Feb\" \"02\")\n (\"Mar\" \"03\")\n (\"Apr\" \"04\")\n (\"May\" \"05\")\n (\"Jun\" \"06\")\n (\"Jul\" \"07\")\n (\"Aug\" \"08\")\n (\"Sep\" \"09\")\n (\"Oct\" \"10\")\n (\"Nov\" \"11\")\n (\"Dec\" \"12\")\n }\n BIND(SUBSTR(?created_at_string, 12, 8) AS ?time)\n BIND(SUBSTR(?created_at_string, 21, 3) AS ?tz_hours)\n BIND(SUBSTR(?created_at_string, 24, 2) AS ?tz_minutes)\n BIND(STRDT(CONCAT(?year_string, \"-\", ?month_number_string, \"-\", ?day_string, \"T\", ?time, ?tz_hours, \":\", ?tz_minutes), xsd:dateTime) AS ?created)\n}\n```\nadjust your Twitter handle in the query string as `?username`, and then run this command:\n```bash\ncat tweets.json | docker run --rm -i -a stdin -a stdout -a stderr atomgraph/json2rdf https://twitter.com/ > tweets.nt && \\\n sparql --data tweets.nt --query tweets.rq > tweets.ttl\n```\nOutput sample:\n```turtle\n\n a sioc:Post ;\n dct:created \"2022-06-10T12:37:44+00:00\"^^xsd:dateTime ;\n sioc:content \"Follow it on GitHub!\\nhttps://t.co/pu5KkOoIOX\" ;\n sioc:id \"1535239790693699587\" ;\n sioc:reply_of .\n```\nImprovements to the mapping query are welcome.\n\n## Performance\n\nLargest dataset tested so far: 2.95 GB / 30459482 lines of JSON to 4.5 GB / 21964039 triples in 2m10s.\nHardware: x64 Windows 10 PC with Intel Core i5-7200U 2.5 GHz CPU and 16 GB RAM.\n\n## Dependencies\n\n* [javax.json](https://mvnrepository.com/artifact/org.glassfish/javax.json)\n* [Apache Jena](https://jena.apache.org/)\n* [picocli](https://picocli.info)\n","has_starred","hub_user","immutable_tags_settings",{"_71":11,"_72":73},"enabled","rules",[74],".*","is_automated","permissions",{"_78":17,"_79":11,"_80":11},"read","write","admin","user","storage_size",3097947937,"orgData",{"_86":87,"_88":89,"_90":91,"_92":29,"_93":94,"_95":96,"_97":98,"_99":100,"_101":102,"_103":104,"_105":104,"_106":104,"_107":17},"id","0d3d01fc4124439dac86df38a58a5b5a","uuid","0d3d01fc-4124-439d-ac86-df38a58a5b5a","type","organization","orgname","full_name","AtomGraph","location","Kaunas, Lithuania","company","UAB Linked Data","profile_url","https://atomgraph.com","date_joined","2017-07-05T20:54:02.134084Z","gravatar_url","","gravatar_email","badge","is_active","recentTags",[110],{"_111":40,"_112":113,"_114":115,"_116":117,"_86":118,"_119":120,"_46":135,"_136":113,"_137":29,"_138":52,"_53":139,"_140":141,"_142":126,"_143":135,"_144":61,"_145":17},"content_type","creator",1909764,"digest","sha256:810d98f212a6c867c98a54a5fa6bda1f8d6d1be026af29bcaca717ff40a25938","full_size",503719158,65472506,"images",[121],{"_122":123,"_114":115,"_124":104,"_125":126,"_127":128,"_129":130,"_131":104,"_132":-5,"_133":117,"_59":61,"_134":-5},"architecture","amd64","features","last_pulled","2026-09-24T16:46:33.496354833Z","last_pushed","2023-08-31T19:15:11Z","os","linux","os_features","os_version","size","variant","2023-08-31T19:15:10.612504Z","last_updater","last_updater_username","media_type","latest","repository",7553552,"tag_last_pulled","tag_last_pushed","tag_status","v2","sbxKitMetadata","isPotentialSpam","isHubSbxKitsEnabled","showSbxLogoOverride","sbxTrademarkText","displaySecurityMetadata","tagAttestations","tagsHaveAttestations",[],"routes/_layout.r.$namespace.$reponame.tags",{"_34":157,"_164":165,"_153":174,"_175":11},{"_36":158,"_38":159,"_41":42,"_43":44,"_45":11,"_46":47,"_48":49,"_50":160,"_53":31,"_28":29,"_54":55,"_56":40,"_57":58,"_59":58,"_60":61,"_62":-5,"_63":64,"_65":66,"_67":11,"_68":29,"_69":161,"_75":11,"_76":163,"_81":29,"_82":83},[],[40],[52],{"_71":11,"_72":162},[74],{"_78":17,"_79":11,"_80":11},"tags",{"_166":58,"_167":-5,"_168":-5,"_169":170},"count","next","previous","results",[171],{"_111":40,"_112":113,"_114":115,"_116":117,"_86":118,"_119":172,"_46":135,"_136":113,"_137":29,"_138":52,"_53":139,"_140":141,"_142":126,"_143":135,"_144":61,"_145":17},[173],{"_122":123,"_114":115,"_124":104,"_125":126,"_127":128,"_129":130,"_131":104,"_132":-5,"_133":117,"_59":61,"_134":-5},[],"canDeleteTags","actionData","errors"]

atomgraph/json2rdf

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