Reproducible Patent Data

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A continuation of Redesigning Patent Database that aims to write faster, more centralized code to deal with data from the United States Patent and Trademark Office (USPTO). By having an end-to-end pipeline we can easily reproduce or update data without worrying about unintentional side effects or missing data.

McNair Project
Reproducible Patent Data
Uspto web logo.jpg
Project Information
Project Title Reproducible Patent Data
Owner Oliver Chang
Start Date May 17
Deadline
Primary Billing
Notes
Has project status Active
Subsumes: Redesigning Patent Database, Patent Assignment Data Restructure
Copyright © 2016 edegan.com. All Rights Reserved.


Progress

  1. Downloader done
  2. Splitter done
  3. Parser done
  4. Setup PostgreSQL JDBC done
  5. Create naive schema based on previous approaches done
  6. Create new data structures done
  7. Database Insert (modify models/ files with some mapping to database fields) done
  8. Create tooling for minions skipped
  9. Investigate parallel speedup (e.g. multithread, mmap) done
  10. Create XPath queries for reissue, design patents (only utility right now)
  11. Create semantic parser for APS files
  12. Data Cleanup (reference Marcela and Sonia's work)
  13. Data Source Merger (only USPTO granted, maintfee, assignment not USPTO applications or Harvard Dataverse or Lex Machina currently)
  14. Setup pipeline script to complete all of these steps in series
  15. Add constraints to database tables, e.g. correct types, foreign keys, not null, lookup tables
  16. Add deduplication
  17. Remove duplicate code through the addition of more abstract classes
  18. first 5 zipcode; centroid
  19. patent id

Directory Layout

Where is the Data?

Directories

All of the information for this project is located at E:\McNair\Projects\SimplerPatentData

There are several interesting directories:

  • data/downloads/ is USPTO bulkdata, unmodified straight from the scraper
  • data/extracts/ is a directory of a strict subset of the information stored in data/downloads/. It is the result of running a bulk 7-zip job on that directory to get everything unzipped in a flat data structure. Note that these files have the USPTO modified-by time since that metadata is stored in the zipfiles. To extract files in this nice format, select all of the zipfiles and setup an extraction job like in this screenshot
  • data/backups/ is a 7zip'd backup of the corresponding directory in extracts
  • src/ is the main code repository for the java project

Input Files

All of the text-only Red Book files for granted patents from 1976 to 2016, inclusive. To find a specific year's XML file, find it in

E:\McNair\Projects\SimplerPatentData\data\extracts\granted\

To find application data from 2001 to 2016, inclusive, look in

E:\McNair\Projects\SimplerPatentData\data\extracts\applications\

To find assignment data, look in

E:\McNair\Projects\SimplerPatentData\data\extracts\granted\

To find maintenance fee data, look in

E:\McNair\Projects\SimplerPatentData\data\downloads\maintenance

Where is the Code?

The code has the same parent directory as the data, so it is at E:\McNair\Projects\SimplerPatentData\src. You might notice a lot of single-entry directories; this is an idiomatic Java pattern that is used for package separation. If using IntelliJ or some other IDE, these directories are a bit less annoying.

The development environment is Java 8 JDK, IntelliJ Ultimate IDE, Maven build tools, and git VCS.

The git repository can be found at https://rdp.mcnaircenter.org/codebase/Repository/ReproduciblePatent

Prior Art

This tool is not so concerned with adding new functionality; rather, it aims to take a bunch of spread out Perl scripts and create a faster system that is easier to work with. As such, its functionality is largely stolen from those scripts:

  • Downloader: E:\McNair\Software\Scripts\Patent\USPTO_Parser.pl
  • XML Splitter: E:\McNair\PatentData\splitter.pl
  • XML Parsing: E:\McNair\PatentData\Processed\xmlparser_4.5_4.4_4.3.pl and E:\McNair\PatentData\Processed\*.pm

In addition, I used several non-standard Java libraries listed below:

If using maven, these dependencies are listed and should automatically be setup.

Using Code

Any file with a line that says public static void main(String[] args) { can be run as a standalone file. The easiest way to do this is to load the project and then the file in IntelliJ and click the little green play arrow next to this bit of code.

The code can also be run via the standard javac and java commands but since this project has a complicated structure you end up having to run commands like

"C:\Program Files\Java\jdk1.8.0_131\bin\java" "-javaagent:C:\Users\OliverC\IntelliJ IDEA 2017.1.3\lib\idea_rt.jar=62364:C:\Users\OliverC\IntelliJ IDEA 2017.1.3\bin" -Dfile.encoding=UTF-8 -classpath "C:\Program Files\Java\jdk1.8.0_131\jre\lib\charsets.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\deploy.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\access-bridge-64.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\cldrdata.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\dnsns.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\jaccess.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\jfxrt.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\localedata.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\nashorn.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\sunec.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\sunjce_provider.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\sunmscapi.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\sunpkcs11.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\ext\zipfs.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\javaws.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\jce.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\jfr.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\jfxswt.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\jsse.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\management-agent.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\plugin.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\resources.jar;C:\Program Files\Java\jdk1.8.0_131\jre\lib\rt.jar;E:\McNair\Projects\SimplerPatentData\target\classes;C:\Users\OliverC\.m2\repository\com\mashape\unirest\unirest-java\1.4.9\unirest-java-1.4.9.jar;C:\Users\OliverC\.m2\repository\org\apache\httpcomponents\httpclient\4.5.2\httpclient-4.5.2.jar;C:\Users\OliverC\.m2\repository\org\apache\httpcomponents\httpcore\4.4.4\httpcore-4.4.4.jar;C:\Users\OliverC\.m2\repository\commons-logging\commons-logging\1.2\commons-logging-1.2.jar;C:\Users\OliverC\.m2\repository\org\apache\httpcomponents\httpasyncclient\4.1.1\httpasyncclient-4.1.1.jar;C:\Users\OliverC\.m2\repository\org\apache\httpcomponents\httpcore-nio\4.4.4\httpcore-nio-4.4.4.jar;C:\Users\OliverC\.m2\repository\org\apache\httpcomponents\httpmime\4.5.2\httpmime-4.5.2.jar;C:\Users\OliverC\.m2\repository\org\json\json\20160212\json-20160212.jar;C:\Users\OliverC\.m2\repository\com\google\guava\guava\21.0\guava-21.0.jar;C:\Users\OliverC\.m2\repository\org\jsoup\jsoup\1.10.2\jsoup-1.10.2.jar;C:\Users\OliverC\.m2\repository\commons-codec\commons-codec\1.10\commons-codec-1.10.jar;C:\Users\OliverC\.m2\repository\org\jetbrains\annotations\15.0\annotations-15.0.jar;C:\Users\OliverC\.m2\repository\org\apache\commons\commons-lang3\3.5\commons-lang3-3.5.jar;C:\Users\OliverC\.m2\repository\org\postgresql\postgresql\42.1.1\postgresql-42.1.1.jar" org.bakerinstitute.mcnair.uspto_assignments.XmlDriver

to include all of the runtime dependencies and it's just not worth it.

Altering Code

  • Use the IntelliJ command Reformat code (found in the menus at Code > Reformat Code
  • Use the optimize imports function found under the same menu
  • Use spaces for indentation
  • Loosely try to keep lines below 120 characters
  • Commit changes to the Git remote repository "bonobo"

Schema Reconciliation

As it turns out, since many of the fields we care about are date and author data the schemas are the same ("universal"). However, it uses parts of the base schema that are unused in the granted patent data. From a short, cursory glance it seems like the meat of the join data appears in the <us-related-documents> tag.

Data Formats
Dates Used Format Supported by Parser? Utility Reissue Design Plant
January 1976 to December 2001 APS Kinda
January 2001 to December 2001 SGML Ignored; use concurrently recorded APS data N/A N/A N/A N/A
January 2002 to December 2004 XML Version 2.5 Only syntax
January 2005 to December 2005 XML Version 4.0 ICE Maybe
January 2006 to December 2006 XML Version 4.1 ICE Maybe
January 2007 to December 2012 XML Version 4.2 ICE Maybe
January 2013 to September 24, 2013 XML Version 4.3 ICE Yes ✓ ✓ ✓
October 8, 2013 to December 2014 XML Version 4.4 ICE Yes ✓ ✓ ✓
January 2015 to December 2016 XML Version 4.5 ICE Yes ✓ ✓ ✓

APS Rosetta Stone

The Advanced Patent System (APS) is a fixed-width text format used to store historical patent grant data. The documentation for this sucks; there are pages missing at random. Luckily, we only care about the content contained here: File:PatentFullTextAPSDoc GreenBook pgs13-22.pdf.

It's worth mentioning that the APS contains an advanced text markup system for chemical formulae, basic text markup, tables, etc. that can lead to seemingly garbled text that is perfectly well-formed.

Database

Because there isn't a compelling reason not to, I used the existing PostgreSQL infrastructure on the RDP. The "Java Way" of interacting with databases is the Java Database Connectivity API (JDBC), an implementation-agnostic API for interacting with databases. This project uses the stock Postgres JDBC, version 42.1.1

  1. Create an empty database: $ createdb --username=postgres patents_june_2017 # password is tabspaceenter
  2. Create tables via script at E:\McNair\Projects\SimplerPatentData\src\db\NaiveSchema.sql
    • Prior Example E:\McNair\Software\Scripts\Patent\createTables.sql
    • Aim to create a completely naive schema with as few constraints as possible--iteratively add more constraints in the future

Since writing raw SQL is a bit cumbersome and error-prone, I have added some abstraction layers that make it much easier to quickly add bulk data. By using Postgres's CopyManager class, we buffer SQL copy commands in memory (as many as possible) and then flush these rows. To understand how the abstraction layers work, see the code in E:\McNair\Projects\SimplerPatentData\src\main\java\org\bakerinstitute\mcnair\postgres. For a concrete example, see E:\McNair\Projects\SimplerPatentData\src\main\java\org\bakerinstitute\mcnair\uspto_assignments\GeonamesZips.java for a simple, self-contained example or E:\McNair\Projects\SimplerPatentData\src\main\java\org\bakerinstitute\mcnair\models\GrantedPatent.java for an example of how to extend the abstraction layer to deal with more complex scenarios.

Address Data

  • Question: "In which zipcodes are the most patents granted?"
  • Zipcode granularity--if possible, finer detail wanted
  • Filter non-US, null addresses
  • Need to cleanup addresses
  • Extract zipcode or reverse locate to find zip
  • "The 4-5 digit reel number refers to the microfilm reel number of the assignment entry in physical USPTO records; similarly the

1-4 digit frame number refers to the location of the assignment entry on the reel number in physical USPTO records. Thus, each assignment recorded with the USPTO has a unique reel number and frame number combination. While both reel number and frame number are sequential, there are missing values in the sequence because each only specifies the first page of the assignment records and records may have multiple pages." from https://www.uspto.gov/sites/default/files/documents/USPTO_Patents_Assignment_Dataset_WP.pdf, pg12, footnote 38

Related Pages

External Links

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