USPTO Datasets

Contains detailed information on roughly 6 million patent assignments and other transactions recorded at the USPTO since 1970 and involving over 10 million patents and patent applications. For more information: http://www.uspto.gov/learning-and-resources/electronic-data-products/data

Contains Artificial Intelligence Patent Landscape data classifying 13,244,037 granted patents and PGPubs published from 1976 through 2020 in eight AI component technologies using state-of-the art machine learning based models.

Contains detailed information on 9.2 million publicly viewable patent applications filed with the USPTO through December 2020. The data are sourced from the Public Patent Application Information Retrieval (Public PAIR) system. There are several data files, each of which coincides with a tab on USPTO's Public PAIR web portal. The data files include information on each application's characteristics, prosecution history, continuation history, claims of foreign priority, patent term adjustment history, publication history, and correspondence address information.

Contains Cooperative Patent Classification (CPC) classification information for all Utility patent grants issued by the U.S. Patent and Trademark Office (USPTO) from 1790 to present. It is available as XML with schemas or text monthly (usually by the 15th of the month).

Contains Cooperative Patent Classification (CPC) classification information for all Utility patent applications published by the U.S. Patent and Trademark Office (USPTO) from March 15, 2001 to present. It is available as XML with schemas or text monthly (usually by the 15th of the month).

Current U.S. classification information for all patent applications (non-provisional utility and plant) published by the USPTO from March 15, 2001 to present. Approx. 450 main divisions of technology, called classifications/classes, broken into approx. 150,000 subdivisions, called subclassifications/subclasses. Provided in published patent application number sequence with the current U.S. original classification/subclassification and any cross-reference classification/subclassifications with the format of ASCII text.

Contains detailed U.S. District Courts patent litigation data on 74,623 unique court cases filed during the period 1963 - 2016. The data was collected from the Public Access to Court Electronic Records (PACER) and RECAP as sources for all of the content. The final output datasets, provided in five different files, include information on the litigating parties involved and their attorneys; the cause of action; the court location; important dates in the litigation history; and, covering over 5 million document level information from the docket reports, descriptions of all documents submitted in a given case.

Contains detailed information on 4.4 million Office actions mailed from 2008 through June 2017 for 2.2 million publicly viewable patent applications. The data are sourced from the text of Non-Final Rejection and Final Rejection Office actions issued by patent examiners to applicants during the patent examination process. The data files include information on grounds for rejection raised, the claims in question, and pertinent prior art.

Contains detailed information on claims from U.S. patents granted between January 1976 and December 2014 and U.S. patent applications published between March 15, 2001 and December 2014. The dataset is derived from the Patent Grant Full Text and Patent Application Full Text bulk data files. The Office of Chief Economist (OCE) applied a Python algorithm to identify individual claims as well as the dependency relationship between claims. From the parsed claims text, OCE created six data files containing individually-parsed claims, claim-level statistics, and document-level statistics, including newly-developed measures of patent scope.

This curated dataset consists of 269,353 patent documents (published patent applications and granted patents) spanning the 1976 to 2016 period and is intended to help identify promising R&D on the horizon in diagnostics, therapeutics, data analytics, and model biological systems.