[{"_1":2,"_174":-5,"_175":-5},"loaderData",{"_3":4,"_13":14,"_21":22,"_153":154},"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":152},"canonicalUrl","https://hub.docker.com/r/atomgraph/csv2rdf/tags","mcpServer","canSeeDockerfile","canSeeAutobuilds","namespace","atomgraph","reponame","csv2rdf","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","2019-07-02T09:23:47.88422Z","description","Converts tabular CSV data to RDF triples using SPARQL query","is_private","last_updated","2020-11-14T22:09:05.697234Z","last_modified","2024-10-16T13:48:34.145251Z","media_types",[52],"application/vnd.docker.container.image.v1+json","name","pull_count",490,"repository_type","star_count",1,"status","status_description","active","source","collaborator_count",0,"full_description","# CSV2RDF\nStreaming, transforming CSV to RDF converter\n\nReads CSV/TSV data as generic CSV/RDF, transforms each row using SPARQL `CONSTRUCT` or `DESCRIBE`, and streams the output triples.\nThe generic CSV/RDF format is based on the minimal mode of [Generating RDF from Tabular Data on the Web](https://www.w3.org/TR/2015/REC-csv2rdf-20151217/#dfn-minimal-mode).\n\nSuch transformation-based approach enables:\n* building resource URIs on the fly\n* fixing/remapping datatypes\n* mapping different groups of values to different RDF structures\n\nCSV2RDF differs from [tarql](https://tarql.github.io) in the way how mapping queries use graph patterns in the `WHERE` clause. tarql queries operate on a table of bindings\n(provided as an implicit `VALUES` block) in which CSV column names become variable names. CSV2RDF generates an intermediary RDF graph for each CSV row (using column names as relative-URI properties)\nthat the `WHERE` patterns explicitly match against.\n\nBuild\n-----\n\n mvn clean install\n\nThat should produce an executable JAR file `target/csv2rdf-2.0.0-jar-with-dependencies.jar` in which dependency libraries will be included.\n\nUsage\n-----\n\nThe CSV data is read from `stdin`, the resulting RDF data is written to `stdout`.\n\nCSV2RDF is available as a `.jar` as well as a Docker image [atomgraph/csv2rdf](https://hub.docker.com/r/atomgraph/csv2rdf) (recommended).\n\nParameters:\n* `query-file` - a text file with SPARQL 1.1 [`CONSTRUCT`](https://www.w3.org/TR/sparql11-query/#construct) query string\n* `base` - the base URI for the data (also becomes the `BASE` URI of the SPARQL query). Property namespace is constructed by adding `#` to the base URI.\n\nOptions:\n* `-d`, `--delimiter` - value delimiter character, by default `,`.\n* `--max-chars-per-column` - max characters per column value, by default 4096\n* `--input-charset` - CSV input encoding, by default UTF-8\n* `--output-charset` - RDF output encoding, by default UTF-8\n\n_Note that delimiters might have a [special meaning](https://www.tldp.org/LDP/abs/html/special-chars.html) in shell._ Therefore, always enclose them in single quotes, e.g. `';'` when executing CSV2RDF from shell.\n\nIf you want to retrieve the raw CSV/RDF output, use the [identity transform](https://en.wikipedia.org/wiki/Identity_transform) query `CONSTRUCT WHERE { ?s ?p ?o }`.\n\nExample\n-------\n\nCSV data in `parking-facilities.csv`:\n \n postDistrict,roadCode,houseNumber,name,FID,long,lat,address,postcode,parkingSpace,owner,parkingType,information\n 1304 København K,24,5,Adelgade 5 p_hus.0,p_hus.0,12.58228733,55.68268042,Adelgade 5,1304,92,Privat,P-Kælder,\"Adelgade 5-7, Q-park.\"\n\n`CONSTRUCT` query in `parking-facilities.rq`:\n\n```sparql\nPREFIX schema: \nPREFIX geo: \nPREFIX xsd: \nPREFIX rdf: \n\nCONSTRUCT\n{\n ?parking a schema:ParkingFacility ;\n geo:lat ?lat ;\n geo:long ?long ;\n schema:name ?name ;\n schema:streetAddress ?address ;\n schema:postalCode ?postcode ;\n schema:maximumAttendeeCapacity ?spaces ;\n schema:additionalProperty ?parkingType ;\n schema:comment ?information ;\n schema:identifier ?id .\n}\nWHERE\n{\n ?parkingRow <#FID> ?id ;\n <#name> ?name ;\n <#address> ?address ;\n <#lat> ?lat_string ;\n <#postcode> ?postcode ;\n <#parkingSpace> ?spaces_string ;\n <#parkingType> ?parkingType ;\n <#information> ?information ;\n <#long> ?long_string . \n\n BIND(URI(CONCAT(STR(<>), ?id)) AS ?parking) # building URI from base URI and ID\n BIND(xsd:integer(?spaces_string) AS ?spaces)\n BIND(xsd:float(?lat_string) AS ?lat)\n BIND(xsd:float(?long_string) AS ?long)\n}\n```\nJava execution from shell:\n\n cat parking-facilities.csv | java -jar csv2rdf-2.0.0-jar-with-dependencies.jar parking-facilities.rq https://localhost/ > parking-facilities.ttl\n\nAlternatively, Docker execution from shell:\n\n cat parking-facilities.csv | docker run -i -a stdin -a stdout -a stderr -v \"$(pwd)/parking-facilities.rq\":/tmp/parking-facilities.rq atomgraph/csv2rdf /tmp/parking-facilities.rq https://localhost/ > parking-facilities.ttl\n\nNote that using Docker you need to:\n* [bind](https://docs.docker.com/engine/reference/commandline/run/#attach-to-stdinstdoutstderr--a) `stdin`/`stdout`/`stderr` streams\n* [mount](https://docs.docker.com/storage/volumes/) the query file to the container, and use the filepath from _within the container_ as `query-file`\n\nOutput in `parking-facilities.ttl`:\n\n .\n \"12.58228733\"^^ .\n \"p_hus.0\" .\n \"P-Kælder\" .\n \"Adelgade 5-7, Q-park.\" .\n \"1304\" .\n \"55.68268042\"^^ .\n \"Adelgade 5\" .\n \"Adelgade 5 p_hus.0\" .\n \"92\"^^ .\n\nQuery examples\n--------------\n\nMore mapping query examples can be found under [LinkedDataHub](https://github.com/AtomGraph/LinkedDataHub)'s [`city-graph`](https://github.com/AtomGraph/LinkedDataHub-Apps/tree/master/demo/city-graph/queries) demo app.\n\nPerformance\n-----------\n\nLargest dataset tested so far: 2.8 GB / 3709725 rows of CSV to 21.7 GB / 151348939 triples in under 27 minutes. Hardware: x64 Windows 10 PC with Intel Core i5-7200U 2.5 GHz CPU and 16 GB RAM.\n\nDependencies\n------------\n\n* [Apache Jena](https://jena.apache.org/)\n* [uniVocity-parsers](https://www.univocity.com/pages/univocity_parsers_tutorial)\n* [picocli](https://picocli.info)","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",947501860,"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,"_86":116,"_117":118,"_46":135,"_136":113,"_137":29,"_138":52,"_53":139,"_140":141,"_142":126,"_143":135,"_144":61,"_145":17},"content_type","creator",1909764,"full_size",310365378,60708339,"images",[119],{"_120":121,"_122":123,"_124":104,"_125":126,"_127":128,"_129":130,"_131":104,"_132":-5,"_133":115,"_59":61,"_134":-5},"architecture","amd64","digest","sha256:d97d475c177238daa97e6ec0188d68e11be312684e6db3696cd7be3a49c0c086","features","last_pulled","2026-09-19T21:58:16.400585529Z","last_pushed","2020-11-14T22:09:06Z","os","linux","os_features","os_version","size","variant","2020-11-14T22:09:05.280654Z","last_updater","last_updater_username","media_type","latest","repository",7346597,"tag_last_pulled","tag_last_pushed","tag_status","v2","sbxKitMetadata","isPotentialSpam","isHubSbxKitsEnabled","displaySecurityMetadata","tagAttestations","tagsHaveAttestations",[],"routes/_layout.r.$namespace.$reponame.tags",{"_34":155,"_162":163,"_151":172,"_173":11},{"_36":156,"_38":157,"_41":42,"_43":44,"_45":11,"_46":47,"_48":49,"_50":158,"_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":159,"_75":11,"_76":161,"_81":29,"_82":83},[],[40],[52],{"_71":11,"_72":160},[74],{"_78":17,"_79":11,"_80":11},"tags",{"_164":58,"_165":-5,"_166":-5,"_167":168},"count","next","previous","results",[169],{"_111":40,"_112":113,"_114":115,"_86":116,"_117":170,"_46":135,"_136":113,"_137":29,"_138":52,"_53":139,"_140":141,"_142":126,"_143":135,"_144":61,"_145":17},[171],{"_120":121,"_122":123,"_124":104,"_125":126,"_127":128,"_129":130,"_131":104,"_132":-5,"_133":115,"_59":61,"_134":-5},[],"canDeleteTags","actionData","errors"]

atomgraph/csv2rdf

Tags for atomgraph/csv2rdf