What it does

OpenAlex is a free, open-access index of academic works, authors, institutions, funding sources, and concepts maintained by OurResearch (formerly Impactstory). It catalogs roughly 250 million works with full citation graph data and makes all of it available via a public REST API — no account or subscription required for most use cases.

It was built partly from Microsoft Academic Graph after Microsoft shut that database down in January 2022, and has since incorporated Crossref, ORCID, ROR, Unpaywall, and other open scholarly infrastructure sources. The underlying data is released as CC0 (public domain).

For researchers, it’s most useful as either a free replacement for Scopus/WoS citation lookups, or as the data layer behind a custom literature pipeline that would otherwise require a costly commercial API license.

Best for

Researchers at institutions without Scopus or Web of Science access, or anyone building programmatic literature workflows who needs citation graph data without a commercial license. Also well-suited for systematic reviewers who want to verify citation counts and reference lists without paying per-query fees, and for bibliometric or science-of-science research.

Pricing

Completely free. The website (openalex.org) is free to browse. The API allows up to 10 requests/second without authentication; adding your email address via the “polite pool” parameter (mailto=your@email.com in the query string) raises the limit to 100 requests/second and makes you easier to contact if your queries cause problems.

A snapshot of the full database is also available for bulk download at no cost.

Strengths

Free and openly licensed (CC0) — zero cost for both browsing and API access
~250 million works with full citation data including references and cited-by counts
Covers preprints (arXiv, bioRxiv), open access papers, and journal articles alongside traditional literature
Rich metadata: DOI, abstract, concepts/topics, open-access status, funding, institution, author ORCID links
Official Python client (pyalex) makes integration straightforward for custom pipelines
The “Topics” classification system (derived from citation patterns) lets you filter by research area without knowing the right MeSH terms or journal lists

Limitations

Author disambiguation is less accurate than Scopus/WoS — researchers with common names or who have changed institutions can be split across multiple author records or merged incorrectly. Always verify author profiles before using for bibliometric analysis
Coverage gaps exist in some areas — humanities, conference proceedings, and grey literature are less complete than Elsevier’s databases
No full-text search — OpenAlex indexes titles and abstracts but not the full text of papers
Citation counts may differ from Scopus/WoS because each database indexes a different universe of source documents; for formal bibliometric work, note which source you used

How it compares

vs.	Key difference
Scopus	Scopus has better author disambiguation and broader conference coverage; OpenAlex is free and has a more permissive API
Web of Science	WoS is the gold standard for impact factor and journal-level metrics; OpenAlex covers more preprints and open-access content
Semantic Scholar	Semantic Scholar has AI-powered concept extraction and better NLP features; OpenAlex has a broader coverage universe and is fully open data
PubMed	PubMed is authoritative for biomedical literature with MeSH indexing; OpenAlex is broader but less curated in the medical domain

Practical notes

The API query format is straightforward. To find all papers citing a given DOI:

https://api.openalex.org/works?filter=cites:W2741809807&mailto=your@email.com

To get a paper by DOI:

https://api.openalex.org/works/https://doi.org/10.1038/nature12373

The pyalex library wraps these calls with a Pythonic interface if you prefer not to construct raw URLs.