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from $2.00 / 1,000 work record returneds

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Crossref DOI & Paper Metadata API: Citations, Journals

Try for free

Look up scholarly papers by DOI or keyword using the official Crossref API: title, authors, journal, date, citation count, license and abstract.

Pricing

from $2.00 / 1,000 work record returneds

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Developer

asaf meizner

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5 days ago

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Crossref DOI & Paper Metadata API

Turn DOIs or keywords into clean scholarly metadata using the official Crossref REST API (open bibliographic data, no login, no scraping). Each row has title, authors (names only), journal, publisher, publication date, volume/issue/pages, citation count, reference count, license link, subjects and abstract when Crossref has it.

Use cases

Enrich a reference list or spreadsheet of DOIs.
Find the most cited papers on a topic since a given year.
Check citation counts for a set of papers over time (schedule a run).
Feed bibliographic data to research or RAG pipelines.

Input

{ "dois": ["10.1038/nature12373", "https://doi.org/10.1126/science.169.3946.635"] }

or a keyword search:

{ "query": "graph neural networks", "maxResults": 50, "fromPubDate": "2022", "sortByCitations": true }

contactEmail is optional: it is sent in the User-Agent so Crossref can contact you (their "polite pool").

Output

{ "doi": "10.1038/nature12373", "status": "ok", "title": "...", "type": "journal-article",
  "authors": ["..."], "journal": "Nature", "publishedDate": "2013-07", "citedByCount": 1234 }

DOIs that do not exist return {"status": "not_found"} and are not charged.

Pricing

Pay per event: $0.002 per work record returned (about $2 per 1,000). Not-found rows are free.

Notes

Sequential requests at about one per second with an identifying User-Agent; stops on repeated errors. Abstracts are only present when the publisher deposited them. Coverage and citation counts are those of Crossref, which differ from Google Scholar or Scopus.

Keyword searches use Crossref’s broad relevance matching; results may not contain every search word. Check titles and abstracts before using them as a topic-specific research set.

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