This repository hosts the R code that was used to create the software that fetches and formats data from openalex.org for scientific analysis with NodeXL
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Updated
Sep 10, 2025 - R
This repository hosts the R code that was used to create the software that fetches and formats data from openalex.org for scientific analysis with NodeXL
This repository contains tools for analyzing institutional collaborations using the OpenAlex API. The tools help visualize collaboration networks, trends, and patterns between academic institutions.
CLI for generating JATS XML citations from DOIs using multiple academic data providers.
ScholarImpact: A Python tool to analyse, visualise, and share individual research impact, output and scholarly influence using bibliometric data
Normalize OpenAlex Works JSONL into fixed-schema, versioned CSV files for downstream use. Schema enforcement only. No analytics or visualization.
This repository contains a Python pipeline developed as part of my work at the IPP Computational Social Sciences program. It automates the retrieval and analysis of academic journal articles from OpenAlex, with the aim of supporting and accelerating systematic literature reviews.
ViCom CollabMap: A data science project that visualizes research collaborations, extracts expertise using OpenAI, and maps potential partnerships via Streamlit and Folium.
Diagnostic topic-mapping workflows for OpenAlex data in MATLAB. Exploratory visualizations only; not a validated analytical framework.
This is a basic setup and demonstration of how to query the OpenAlex API to download PDFs of scientific documents and pipe the documents into 2 separate OCR engines to extract the information from the PDFs.
UrbanLitTracker coleta artigos acadêmicos sobre mudanças urbanas via OpenAlex API, processa e armazena em MongoDB. Oferece dashboard interativo com Dash, exibindo dados como trabalhos mais relevantes, autores e palavras-chave frequentes, facilitando a análise e visualização da literatura urbana.
MATLAB utilities to fetch OpenAlex Works data and store them as JSONL / MAT files. Acquisition only. No normalization, analysis, or visualization.
Community network analysis of the Science for Sustainability theme of Utrecht University
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