sonad 0.1.0

Software name disambiguation pipeline

SONAD: Software Name Disambiguation

SONAD (Software Name Disambiguation) is a command-line tool and Python package that links software mentions in scientific papers to their corresponding repository URLs. It leverages NLP, third-party tools like SOMEF, and metadata to resolve software names accurately. It is limited to fetching URLs from GitHub, PyPI and CRAN.

---

Installation

Install using pip:

pip install sonad

For development mode (auto-refreshes when you edit the code):

pip install sonad -e .

---

Initial Configuration

Before using SONAD, you must install and configure SOMEF
(https://github.com/KnowledgeCaptureAndDiscovery/somef/?tab=readme-ov-file),
which is used for software metadata extraction.

Follow their installation instructions to make sure somef runs correctly on your system.

It is also strongly recommended to provide a GitHub API token to avoid rate limits when querying GitHub. You can configure this once using:

sonad configure

Your token will be saved for future runs.

---

Requirements

SONAD requires Python 3.9. All dependencies are installed automatically.

Some key libraries:

• pandas
• scikit-learn
• xgboost
• sentence-transformers
• beautifulsoup4
• requests
• SPARQLWrapper
• somef
• textdistance
• lxml
• cloudpickle

---

Usage

After installation, you can run the main command:

sonad process -i <input_file.csv> -o <output_file.csv> [-t <temp_folder>] 

Parameters

• -i, --input (required): Path to the input CSV file.
• -o, --output (required): Path where the output CSV will be saved.
• -t, --temp (optional): Folder where temporary files will be written it the folder is provided.

---

Input Format

The input CSV must contain the following columns:

• name: The software name mentioned in the paper.
• doi: The DOI of the paper.
• paragraph: The paragraph in which the software is mentioned.

Optionally, it can include:

• candidate_urls: A comma-separated list of candidate software URLs that might correspond to the software.

Example:

name,doi,paragraph,candidate_urls
Scikit-learn,10.1000/xyz123,"We used Scikit-learn for classification.","https://github.com/scikit-learn/scikit-learn"

---

License

MIT License © Jelena Djuric
https://github.com/jelenadjuric01

---

Contributions

Feel free to submit issues or pull requests on the GitHub repository:
https://github.com/jelenadjuric01/Software-Disambiguation