DOI-Extractor-OEG
Description
DOI-Extractor-OEG is a tool for extracting all paper's name and DOI from OEG publications.
They are extracted from two main resources:
-
https://portalcientifico.upm.es/es/ipublic/entity/16247 , corresponding to all papers from OEG.
-
ExistingPapers/ Papers.csv with already extracted data from some OEG papers.
The resulting information is placed in Outputs folder, which include:
-
A dois.txt containing, for each paper, the URL to the pdf if it was founded or if not the doi
-
A results.csv, containing the title and the doi of every paper found, in addition to OpenAlex primary location attribute
-
A results.json, containing the same information as results.csv but in a json format
Project Structure
DOI-Extractor-OEG
├───doiExtractor
| ├───ExistingPapers
| | ├───name_doi_papers.csv
| | └───Papers.csv
| ├───Outputs
| | ├───dois.csv
| | |───results.csv
| | └───results.json
| ├───__init__.py
| ├───doiExtractor.py
| ├───main.py
| └───openAlex.py
├───.gitignore
├───LICENSE.txt
├───README.MD
└───setup.py
doiExtractor.py - Contains the functions to extract the name and doi from portalcientifico.upm.es and to merge that information with the existing papers.
openAlex.py - Contains the functions to extract the primary location from openAlex and if the DOI was not found with doiExtractor.py, it tries to extract it using Open Alex.
Installation
- Clone the repository:
git clone https://github.com/ptorija/DOI-Extractor-OEG.git
- Change to the DOI-Extractor-OEG directory:
cd DOI-Extractor-OEG
- Create a virtual environment:
python -m venv .env
- Activate the virtual environment:
(Linux)
source .env/bin/activate
(Windows)
.env\Scripts\activate
- Install the package dependencies:
pip install -e .
Usage
Download the package from Pypi or install the tool from Github:
pip install DataExtractorOEG
The tool can be used from the command line with the following argument:
--start- To start the doi extraction
The script will execute and extract DOIs from the specified webpage and then merge them with the ones from ExistingPapers.
Options:
--url <path>- Specify the webpage of the group you want to extract the information. Default: Ontology Engieneering Group--output <path>- Specify the path for the output files. Default: Outputs
Example
- Install the tool from Pypi ( https://pypi.org/project/DataExtractorOEG/ )
pip install DataExtractorOEG
- Start the execution
DataExtractorOEG --start
When the execution ends, the following files will be saved in doiExtractor/Outputs folder:
- dois.txt
- results.csv
- results.json
If you want to use RSEF with the output provided by this tool, follow the following steps
- Clone RSEF repository:
git clone https://github.com/SoftwareUnderstanding/RSEF.git
- Install the required dependencies by running:
pip install -e .
- Use RSEF with the extracted results.json from DOI-Extractor-OEG, this will create a downloaded_metadata.json and a processed_metadata.json:
rsef process -j <path to results.json>
If you didn't execute DOI-Extractor-OEG previously, you can also execute DataExtractorOEG --start and then the previous command
- To check the implementations of the papers use:
rsef asses -i <path to processed_metadata.json>
-U flag to check Unidirectionality
-B flag to check Bidirectionality
Release files for DataExtractorOEG 0.5.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dataextractoroeg-0.5.2.tar.gz | 165.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| DataExtractorOEG-0.5.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 381.6 kB
Release files / dataextractoroeg-0.5.2.tar.gz
| Download URL | dataextractoroeg-0.5.2.tar.gz |
|---|---|
| Size | 165.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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Release files / DataExtractorOEG-0.5.2-py3-none-any.whl
| Download URL | DataExtractorOEG-0.5.2-py3-none-any.whl |
|---|---|
| Size | 216.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.0
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