What problem does it solve?
OpenAlex enables fast discovery and enrichment of scholarly works (papers, authors, institutions, journals, and concepts) so you can avoid manual database searching when building datasets for research and analysis.
Core Features & Use Cases
- Search and filter across 250M+ works: Retrieve relevant literature by keyword, author, DOI, ORCID, or OpenAlex ID while applying constraints like year, open access, citation counts, and concepts.
- Lookup and enrich metadata: Fetch a single work by DOI or ID and extract useful fields such as title, publication year, citation counts, abstract (when available), and open-access URLs.
- Build citation and reference networks: Retrieve referenced works and citing works to support bibliometrics, co-citation exploration, and reference-graph traversal.
- Use cases: Create systematic literature review corpora, disambiguate authors via ORCID/OpenAlex IDs, enrich DOI lists with citation/venue/abstract metadata, and analyze publication trends by concept, institution, journal, or country.
Quick Start
Use the openalex-database skill to search OpenAlex works for the query "single-cell RNA sequencing" filtered to years 2020-2024 and open-access papers, then return the top results with title, year, citation count, DOI, and open-access URL.
