USPatents: Publishing and Interlinking the USPTO Patent Data

A patent is a set of exclusive rights granted to an inventor by a sovereign state for a solution, be it a product or a process, for a solution to a particular technological problem. The United States Patent and Trademark Office (USPTO) is part of the US department of Commerce that provides patents to businesses and inventors for their inventions in addition to registration of products and intellectual property identification. Each year, the USPTO grants over 150,000 patents to individuals and companies all over the world. As of December 2011, 8,743,423 patents have been issued and 16,020,302 applications have been received. The USPTO patents are accepted in electronic form and are filed as PDF documents. However, the indexing is not perfect and it is cumbersome to search through the PDF documents. Additionally, Google has also made all the patents available for download in XML format, albeit only from the years 2002 to 2015. Thus, we converted this bulk of data (spanning 13 years) from XML to RDF to conform to the Linked Data principles.

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About the dataset

Excerpt of the RDF representation of a single patent from the year 2012

    PREFIX patent: <http://us.patents.aksw.org></http:> .
    PREFIX patents: <http://us.patents.aksw.org/ontology></http:> .
    PREFIX patentp: <http://us.patents.aksw.org/property></http:> .
    PREFIX dc: <http://purl.org/dc/terms></http:> .
    PREFIX xsd: <http://www.w3.org/2001/XMLSchema#> .
    PREFIX foaf: <http://xmlns.com/foaf/0.1></http:> .
    PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

    patent:06906845
    a        patents:Patent ;
    patentp:national-classification         patent:359290 ;
    patentp:citedBy                         patent:5285196 ;
    dc:date                                 "2005-06-14"^^xsd:date ;
    patentp:primaryExaminer                 patent:examiner-Hung%20Xuan-Dang ;
    patentp:agent                           patent:agent-06906845-01 ;
    patentp:assignee                        patent:assignee-Samsung%20Electronics%20Co.%2C%20Ltd. ;
    dc:abstract                             "The micro-mechanical structure includes an anti-stiction ..."@en ;
    patentp:Year                            "2005"^^xsd:gYear ;
    patentp:country                         patent:country-US ;
    patentp:applicant                       patent:applicant-06906845-001 ;
    patentp:docNo                           "06906845"^^xsd:int ;
    patentp:kind                            patent:B2 ;
    patentp:inventionTitle                  "Micro-mechanical device"@en ;
    patentp:secondaryExaminer               patent:examiner-Joseph-Martinez .

    patent:359290
    patentp:mainSubclassLabel               "OPTICAL MODULATOR Light wave temporal modulation...."@en ;
    patentp:mainClassLabel                  "Optical: systems and elements"@en ;
    patentp:mainClassCode                   "359290" .

    patent:applicant-06906845-001
    a                                        patents:Applicant ;
    foaf:lastName                            "Cho"@en ;
    patentp:country                          patent:country-KR ;
    foaf:firstName                           "Chang-ho"@en ;
    patentp:city                             patent:Suwon ;
    patentp:residence                        patent:country-KR ;
    patentp:nationality                      patent:nationality-KR .

    patent:examiner-Hung%20Xuan-Dang
    a                                        patents:Examiner, foaf:Person ;
    foaf:firstName                           "Hung Xuan"@en ;
    foaf:lastName                            "Dang"@en .

    patent:agent-06906845-01
    a                                        foaf:Agent ;
    foaf:Organization                        "Sughrue Mion, PLLC"@en ;

    patent:assignee-Samsung%20Electronics%20Co.%2C%20Ltd.
    a                                        foaf:Assignee ;
    patentp:orgname                          patent:Samsung%20Electronics%20Co.%2C%20Ltd. ;
    patentp:assignee-city                    patent:Gyeonggi-do ;
    patentp:country                          patent:country-KR ;
    patentp:role                             patent:03 .

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News

SANSA 0.7.1 (Semantic Analytics Stack) Released ( 2020-01-17T09:52:41+01:00 by Prof. Dr. Jens Lehmann)

2020-01-17T09:52:41+01:00 by Prof. Dr. Jens Lehmann

We are happy to announce SANSA 0.7.1 – the seventh release of the Scalable Semantic Analytics Stack. SANSA employs distributed computing via Apache Spark and Flink in order to allow scalable machine learning, inference and querying capabilities for large knowledge graphs. Read more about "SANSA 0.7.1 (Semantic Analytics Stack) Released"

More Complete Resultset Retrieval from Large Heterogeneous RDF Sources ( 2019-12-05T15:46:09+01:00 Andre Valdestilhas)

2019-12-05T15:46:09+01:00 Andre Valdestilhas

Over recent years, the Web of Data has grown significantly. Various interfaces such as LOD Stats, LOD Laundromat and SPARQL endpoints provide access to hundreds of thousands of RDF datasets, representing billions of facts. Read more about "More Complete Resultset Retrieval from Large Heterogeneous RDF Sources"

DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released ( 2019-09-24T22:41:46+02:00 by Simon Bin)

2019-09-24T22:41:46+02:00 by Simon Bin

Dear all, The Smart Data Analytics group [1] and the E.T.-db-MOLE sub-group located at the InfAI Leipzig [2] is happy to announce DL-Learner 1.4. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. Read more about "DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released"

DBpedia Day @ SEMANTiCS 2019 ( 2019-08-01T10:35:05+02:00 Sandra Bartsch)

2019-08-01T10:35:05+02:00 Sandra Bartsch

 We are happy to announce that SEMANTiCS 2019 will host the 14th DBpedia Community Meeting at the last day of the conference on September 12, 2019. Read more about "DBpedia Day @ SEMANTiCS 2019"

LDK conference @ University of Leipzig ( 2019-03-22T09:21:41+01:00 by Julia Holze)

2019-03-22T09:21:41+01:00 by Julia Holze

With the advent of digital technologies, an ever-increasing amount of language data is now available across various application areas and industry sectors, thus making language data more and more valuable. Read more about "LDK conference @ University of Leipzig"