Overview
OpenAlex is a massive, open-source bibliographic index of the world’s scholarly research system, launched by the non-profit OurResearch as a direct successor to the Microsoft Academic Graph (MAG). By 2026, it has become the gold standard for 'Open Science' infrastructure, indexing over 250 million works, 90 million authors, and 100,000 institutions. Its technical architecture is built on a persistent identifier (PID) graph, linking DOIs, ORCIDs, ROR IDs, and PubMed IDs into a unified schema. OpenAlex uses advanced machine learning models for author disambiguation and automated concept tagging, allowing researchers and developers to perform complex bibliometric analysis without the restrictive licensing costs of legacy systems like Scopus or Web of Science. It operates on a 'linked data' philosophy, providing a REST API and complete data snapshots in JSON-LD format. This allows for massive-scale data mining, institutional benchmarking, and the creation of custom discovery tools. As a critical node in the AI research stack, it serves as a primary data source for training Large Language Models (LLMs) on high-quality, peer-reviewed scientific literature.