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This is where the files will go.
The My files are in2 different places:Did development work here
==Status==
Check my work log to see what I have done on a day to day basis
Currently the web scraper is able to gather all of the data that I can gather from the HTML.There are a few cases where the Investigation Number is not FAQs listed and I need to test for those andhere fix that in the code https://www.usitc.gov/documents/337Info_FAQ.pdf
Next steps will be to parse There is a query builder for Section 337 Notices Here https://pubapps2.usitc.gov/337external/advancedTo use you must select fields from the PDFSGUI at the bottom of the page
no edit summary
{{Project|Has project output=Data,Tool|Has sponsor=McNair ProjectsCenter
|Has title=USITC Data
|Has owner=Harrison Brown
}}
==Files==
E:\McNair\Projects\USITC
I had to use to the Postgres SQL server to download the PDFSThe Postgres SQL Server: 128.42.44.182/bulk/USITC ==Additional Information==There is more information that the USITC provides besides 337 notices. Here is information and a database on Section 701/731 https://www.usitc.gov/trade_remedy/trade_research_tools https://pubapps2.usitc.gov/sunset/ =New Work===USITC 337 Cases Tab Delimited Text==USITC patent information was gathered from the investigations.json file downloaded from the USITC website (https://pubapps2.usitc.gov/337external/, Click on Cases Instituted After 2008).This contains information on 337 cases and their respondents/complainants and the patents that were part of the case. The code and results for this program are here: Projects/USITC/JSON_scraping_pythonThe program grabs the information, places it into lists of lists in Python, and then writes to the file names listed below. The files do not have headers and null values are set to be empty strings.To create the tab delimited text files, run code.py in the JSON_scraping_python directory. This has all of the file names hard coded. It will create the following files investigation_info.txt Schema for this file is id, title, investigation number, investigation type, docket number, date of publication notice complainant_info.txt Schema for this file is investigation id, investigation number, Complaintant name, complainant outside party ID, comp_city, comp country respondent_info.txt Schema for this file is investigation id, investigation number, Respondent Outside Party ID , Respondent Name, Respondent City, Respondent Country patent_info.txt Schema for this file is Investigation Number, Patent ID, Patent Number, Active Date, Inactive Date, ==XML Information==UPDATE: used JSON file of data to convert to tab-delimited text.There is an XML file that contains information on investigations. To get it go to the link below and 'xml' link that is under the tab that under 'Cases instituted after October 2008'. https://pubapps2.usitc.gov/337external/ The information that is found this file can be grabbed with an XML parser. For each investigation, we can find out* Investigation Number ex - (<entry key="investigationNo">966</entry>)* Date of publication Notice - (<entry key="dateOfPublicationFrNotice">2015-09-24T04:00:00.000Z</entry>)* Title ex - <entry key="title">Silicon-on-Insulator Wafers</entry>* There is an entry for patent numbers, ex - <entry key="patentNumbers">* Investigation Type ex - <entry key="investigationType">Violation</entry>* Respondents can be found under <entry key="respondent">* Complainant can be found under <entry key="complainant">Additional information can also be gathered from the XML document To find information on cases prior to 2008, go to the link above and click on 'Looking for cases instituted prior to October 2008?', and it willdownload a csv file.* The investigation number, Title, Unfair Act Alleged, Patent Numbers,Complainants, Respondents, can be grabbed easily from the CSV* Target Date, Beginning and Ending Dates contain notes (some cases are extended and dates are changed)and so we may need to do some text processing to grab this information ==Old Work==This is the work that was done before I knew about the XML files provided by the USITC (see Alternative Solutions section below) Here is a csv of the data that I have been able to scrape from the HTMLof https://www.usitc.gov/secretary/fed_reg_notices/337.htmThe results.csv file found here, E:\McNair\Projects\USITC
For every notice paper, there is a line in the CSV file that
contains the Investigation Title, Investigation No., link to the PDF on the website, Notice description, and date the notice was issued
I have also downloaded the PDFS from the website. These are the pdfs from the links that are in the csv file. Some of the PDFS were not able to be downloaded. The PDFs are here
E:\McNair\Projects\USITC\pdfs_copy
These files were downloaded using the script on the Postgres Server. There are issues downloading PDFs onto the remote windows machine for some reason.
You must download the PDFs on the Postgres Server and transfer them to the RDP. The script to download the PDFS
is
128.42.44.182\bulk\USITC\download
Using the pdf scraper from previous project found here
E:\McNair\software\utilities\PDF_RIPPER
You can scrape the PDFs. This file was modified to scrape all of the pdfs in the pdfs folder. The modified code is in the McNair/Project/USITC/ directory and it is
called pdf_to_text_bulk.py
An example of PDF parsing that works is parsing this pdf: https://www.usitc.gov/secretary/fed_reg_notices/337/337_959_notice02062017sgl.pdf
E:\McNair\Projects\USITC\Parsed_Texts\337_959_notice02062017sgl.txt
There are PDFs where the parsing does not work completely and the text is scrambled.
I have started using NLTK to gather information about the filings. See code in Projects/USITC/ProcessingTexts
I am working on extracting the respondents from these documents.
==Alternative Solutions==
Here is where you can get data on the USITC 337 notices instead of extracting this information from PDFs
337Info - Unfair Import Investigations Information System
https://pubapps2.usitc.gov/337external/
This link has links to Complaints. Most of the data that can be gathered is there and it is in a nice format that could be easily web scraped if we needed to. They have a query builder (link below). There is also a link that download all of the raw data in JSON or XML.
Here are links to various statistics we could use:
Section 337 Statistics: Settlement Rate Data
https://www.usitc.gov/intellectual_property/337_statistics_settlement_rate_data.htm
Section 337 Statistics
https://www.usitc.gov/press_room/337_stats.htm
Section 337 Statistics: Number of New, Completed, and Active Investigations by Fiscal Year (Updated Quarterly)
https://www.usitc.gov/intellectual_property/337_statistics_number_new_completed_and_active.htm
Section 337 Statistics
This contains links to various other pages with statistics
https://www.usitc.gov/intellectual_property/337_statistics.htm
Here is a dictionary of terms used in these Documents
https://www.usitc.gov/documents/337Info_ext_DataDictionary.pdf
