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RDF-extraction

Extraction scripts for transforming the Orlando XML data into Linked Data (CIDOC edition) (cidoc-revisions branch)

Note: The CWRC version of these extraction scripts can be found on the Classic Branch

You must have Python installed, at least version 3.8.

Setup

Download files from CWRC

Prerequisites

You must have a CWRC account to be able to do this with the appropriate permissions. (Sign up here)

In Root folder:

  1. Create a Virtual Environment: python3 -m venv venv
  2. Start Virtual Environment: source ./venv/bin/activate
  3. Install modules: pip install -r requirements.txt
  4. Create an .env file with username=XXX and password=yyy, replacing xxx and yyy with the respective credentials.

Example file:

username=John Doe
password=mySuperSecretpassword12!

Run download script

  1. Run script: python3 islandora_auth.py (This by default will only download the Entries)

To Run Extraction scripts

These commands take place in Biography folder (cd Biography)

  1. Update default directory field within testcases.json to match where your source data files are
  2. Create a Virtual Environment: python3 -m venv venv
  3. Start Virtual Environment: source ./venv/bin/activate
  4. Install modules: pip install -r requirements.txt
  5. Run script python3 bio_extraction.py

Features

Run python3 bio_extraction.py -h for a list of available options

No particular testcases available, please add to testcases.json
usage: bio_extraction.py [-h] [-qa | -s | -g | -i | -id ORLANDO | -f FILE | -d DIRECTORY | -r [RANDOM] | -l [LAST] | -fi [FIRST]] [-v {0,1,2,3}] [-fmt {rdf,rdf/xml,ttl,turtle,json-ld,nt,trix,n3,all}] [-u UPDATE] [-p]

Extract the Majority of biography related data information from selection of orlando xml documents

optional arguments:
  -h, --help            show this help message and exit
  -qa                   will run through qa test cases that are related to www.github.com/cwrc/testData/tree/master/qa, Which currently are:'aguigr', 'alcolo', 'atwoma', 'bronch', 'bronem', 'levyam', 'seacma',
                        'shakwi', 'woolvi'
  -s, -special          will run through special cases that are of particular interest atm which currently are: 'fielmi'
  -g, -graffles, -graffle
                        will run through cases related to our graffles'seacma', 'lel___', 'edgema', 'blesma', 'leonan'
  -i, -ignored          will run through files that are currently being ignored which currently include: 'fielmi'
  -id ORLANDO, -orlando ORLANDO, --orlando ORLANDO
                        entry id of a single orlando document to run extraction upon, ex. woolvi
  -f FILE, -file FILE, --file FILE
                        single orlando xml document to run extraction upon
  -d DIRECTORY, -directory DIRECTORY, --directory DIRECTORY
                        directory of files to run extraction upon
  -r [RANDOM], -random [RANDOM], --random [RANDOM]
                        chooses {RANDOM} random file(s) to run extraction upon
  -l [LAST], -last [LAST], --last [LAST]
                        chooses {last} file(s) to run extraction upon, ex. the last 20 files
  -fi [FIRST], -first [FIRST], --first [FIRST]
                        chooses {first} file(s) to run extraction upon, ex. the first 20 files
  -v {0,1,2,3}, --verbosity {0,1,2,3}
                        increase output verbosity
  -fmt {rdf,rdf/xml,ttl,turtle,json-ld,nt,trix,n3,all}, --format {rdf,rdf/xml,ttl,turtle,json-ld,nt,trix,n3,all}
  -p, -pause, --pause   pause after every entry to examine output and be prompted to continue/quit

Each script within Biography/ can be run on its own, bio_extraction.py is the current main driver that calls needed functions within separate scripts. The same arguments are applicable to those scripts.

Example: If you just wanted to test the extraction of cultural forms. You could do python3 culturalForm.py -r 1

This would only extract from culturalform tags, from 1 random source file. This allows for better testing and more modular classes to be made.

Additional Configuration details

Design Considerations