Harmonizing the Bibliometric Symphony of Scopus and Web of Science
BibexPy is a Python-based software designed to streamline bibliometric data integration, deduplication, metadata enrichment, and format conversion. It simplifies the preparation of high-quality datasets for advanced analyses by automating traditionally manual and error-prone tasks.
- DOI-Based Deduplication and Merging: Identifies and removes duplicate entries while enriching metadata by merging complementary records.
- API-Driven Metadata Enrichment: Completes missing fields such as abstracts, keywords, and affiliations using APIs like Unpaywall and Semantic Scholar.
- Format Conversion: Generates outputs compatible with VosViewer and Biblioshiny for easy analysis.
- Command-Line Interface (CLI): Offers user-friendly interaction with minimal setup requirements.
- Python ≥ 3.9.0
Libraries:
python-dotenv==1.0.0
pandas>=2.0.0
openpyxl>=3.1.2
numpy>=1.24.0
requests>=2.31.0
scikit-learn>=1.3.0
scipy>=1.11.0
tqdm>=4.65.0
xlrd>=2.0.1
xlsxwriter>=3.1.0
colorama >= 0.4.6
typing-extensions >= 4.7.0
-
Clone the Repository
git clone https://github.com/bcankara/BibexPy.git
-
Navigate to the Directory
cd BibexPy
-
Install Dependencies
pip install -r requirements.txt
-
(Optional) Virtual Environment Setup
python -m venv venv source venv/bin/activate # Mac/Linux venv\Scripts\activate # Windows
-
Run the Application
python DataProcessor.py
-
Follow the Workflow
- Select your project.
- Upload Scopus (
.csv
) and Web of Science (.txt
) files. - Choose to enrich metadata (optional).
- Review and save the processed datasets.
BibexPy generates the following outputs:
- Unified datasets (
Prefix_Bib.xlsx
). - VosViewer-compatible files (
Prefix_Vos.txt
). - Statistical summaries for dataset quality and completeness.
For detailed documentation and examples, visit: BibexPy Documentation
For questions or feedback, contact:
📧 [email protected]
BibexPy is licensed under the GNU General Public License (GPL). See the LICENSE file for details.
Enhance your bibliometric research with BibexPy, making data preparation efficient, reliable, and analysis-ready!