OpenAlex Scholarly Works Scraper
Pricing
from $0.001 / work scraped
OpenAlex Scholarly Works Scraper
Search 250M+ academic papers via OpenAlex: title, abstract, authors, institutions, venue, citation count, DOI, open-access status and topics. Filter by year, type and open access. For research, R&D and lit reviews. No key.
Pricing
from $0.001 / work scraped
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hiper soft
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6 days ago
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OpenAlex Scholarly Works Scraper — 250M+ papers, citations & abstracts, structured JSON, no API key
Search the open catalog of scholarly works via the OpenAlex API and get back clean, structured JSON for every paper — title, reconstructed abstract, authors and their institutions, venue, publisher, citation count, DOI, open-access status and research topics. Filter by publication year, work type and open access, and collect thousands of works per search term. No account, no API key. Ideal for literature reviews, R&D scouting, bibliometrics and building research datasets.
Features
- 🔎 Multi-term search — pass any number of
searchTerms(matched against title, abstract and fulltext); each term runs separately and results are deduped by OpenAlex work ID. - 📅 Year filtering — bound results with
fromYearandtoYearto focus on a publication window (0 = no bound). - 🔓 Open-access filter — flip
openAccessOnlyto keep only OA works, and getoaStatusplus a directoaUrlfor each. - 🗂️ Work-type filter — narrow to
article,preprint,review,book-chapter,datasetand more viaworkType. - 📝 Reconstructed abstracts — toggle
includeAbstractto rebuild readable abstract text from OpenAlex's inverted index. - 👥 Rich authorship — every author with their affiliated institutions, plus a ready-to-read
authorsListstring andauthorCount. - 📈 Bibliometrics built in — citation counts, referenced-works counts, venue, publisher and research
topicson every record; scale tomaxResultsPerSearchup to 10,000.
What you get
Each dataset row is one scholarly work:
{"searchTerm": "machine learning","title": "Deep Residual Learning for Image Recognition","doi": "https://doi.org/10.1109/cvpr.2016.90","openAlexId": "https://openalex.org/W2194775991","publicationYear": 2016,"publicationDate": "2016-06-01","type": "article","language": "en","citedByCount": 210453,"referencedWorksCount": 38,"authorsList": "Kaiming He; Xiangyu Zhang; Shaoqing Ren; Jian Sun","authors": [{ "name": "Kaiming He", "institutions": ["Microsoft Research"] }],"authorCount": 4,"venue": "IEEE Conference on Computer Vision and Pattern Recognition","publisher": "IEEE","isOpenAccess": true,"oaStatus": "green","oaUrl": "https://arxiv.org/pdf/1512.03385","topics": ["Deep Learning", "Image Classification"],"url": "https://doi.org/10.1109/cvpr.2016.90","abstract": "Deeper neural networks are more difficult to train..."}
Input
{"searchTerms": ["crispr gene editing", "large language models"],"fromYear": 2020,"toYear": 0,"openAccessOnly": false,"workType": "article","maxResultsPerSearch": 50,"includeAbstract": true}
| Field | Description |
|---|---|
searchTerms | Terms to search across title, abstract and fulltext. One search per term. |
fromYear / toYear | Publication-year bounds; 0 means no lower/upper bound. |
openAccessOnly | Keep only open-access works. |
workType | Optional type filter (e.g. article, preprint, review, dataset). |
maxResultsPerSearch | Maximum works per search term (1–10,000). |
includeAbstract | Reconstruct and include each paper's abstract text. |
Use cases
- Run a systematic literature review and export a structured, citation-ranked corpus.
- Map the most-cited authors, institutions and venues for a research topic.
- Track emerging preprints and open-access work in a fast-moving field.
- Build training or RAG datasets of abstracts and metadata for research tooling.
Pricing
Pay-per-event: you're billed a small amount per run and per item scraped — you only pay for what you get. See the Pricing tab for current rates.
FAQ
Do I need an API key? No. This Actor uses the public OpenAlex API with no account, login or API key required — just enter your search terms and run.
How many papers can I scrape per run?
Up to 10,000 works per search term via maxResultsPerSearch, and you can pass multiple searchTerms in one run, so a single run can collect tens of thousands of works (deduped by OpenAlex work ID).
Is scraping OpenAlex legal? Yes. OpenAlex is a fully open catalog of scholarly metadata, and this Actor reads only those openly available records through the official API and returns them as-is.
What format is the output? Structured JSON — one row per scholarly work — exportable as JSON, CSV or Excel. Each record includes title, reconstructed abstract, authors with institutions, venue, publisher, citation count, DOI and open-access status.
Can I filter by year or open access?
Yes. Bound results with fromYear/toYear, keep only open-access works with openAccessOnly, and narrow to a specific workType such as article, preprint, review or dataset.
Related Actors
Building a bibliometrics or literature dataset? These other hipersoft scrapers work well alongside this one:
- Crossref Scraper — DOIs, citation counts and metadata from 150M+ registered works
- Semantic Scholar Scraper — papers with citation and influential-citation metrics
- arXiv Papers Scraper — preprints with full abstracts and PDF links
- PubMed Scraper — biomedical literature, abstracts and MeSH terms
Notes
This Actor uses the public OpenAlex API and returns that catalog's own metadata as-is, over openly available records with no login required. It is an independent tool and is not affiliated with, endorsed by, or sponsored by OpenAlex or OurResearch.