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OpenAlex Scholarly Works Scraper

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from $0.001 / work scraped

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OpenAlex Scholarly Works Scraper

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.

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from $0.001 / work scraped

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hiper soft

hiper soft

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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 fromYear and toYear to focus on a publication window (0 = no bound).
  • 🔓 Open-access filter — flip openAccessOnly to keep only OA works, and get oaStatus plus a direct oaUrl for each.
  • 🗂️ Work-type filter — narrow to article, preprint, review, book-chapter, dataset and more via workType.
  • 📝 Reconstructed abstracts — toggle includeAbstract to rebuild readable abstract text from OpenAlex's inverted index.
  • 👥 Rich authorship — every author with their affiliated institutions, plus a ready-to-read authorsList string and authorCount.
  • 📈 Bibliometrics built in — citation counts, referenced-works counts, venue, publisher and research topics on every record; scale to maxResultsPerSearch up 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
}
FieldDescription
searchTermsTerms to search across title, abstract and fulltext. One search per term.
fromYear / toYearPublication-year bounds; 0 means no lower/upper bound.
openAccessOnlyKeep only open-access works.
workTypeOptional type filter (e.g. article, preprint, review, dataset).
maxResultsPerSearchMaximum works per search term (1–10,000).
includeAbstractReconstruct 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.

Building a bibliometrics or literature dataset? These other hipersoft scrapers work well alongside this one:

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.