Crossref Works Scraper — DOIs, Authors & Citations

What this Actor scrapes

Crossref is the DOI registration agency behind most scholarly publishing — 150M+ journal articles, book chapters, datasets, preprints, and proceedings, each with publisher-submitted metadata exposed through one keyless JSON API. The catch is cursor-only deep paging plus metadata that nests authors, funders, and licenses several levels down. This Actor walks Crossref's cursor pages for you and flattens every work into one row — authors keep their ORCID and affiliation, funders keep their award numbers — so a scholarly-output tracker or funder-compliance report lands straight in a spreadsheet.

What we handle for you

• 🛡️ Browser fingerprint rotation — the target sees a real browser TLS handshake, not a script.
• 🌐 Proxy rotation — fresh exit on every block through Apify Proxy.
• 🔁 Retries with backoff — 408 / 429 / 5xx retried up to five times, Retry-After honoured.
• 🧊 Clean, typed rows — schema-validated output with ISO-8601 timestamps.
• 💰 Pay per result — no data, no result charge.

Use cases

• Track a competitor lab's or institution's new publications as they're registered with Crossref.
• Pull citation counts for a grant or tenure report without hand-rolling the API.
• Check funder compliance — confirm published works credit the right funder and award number.
• Build a publisher- or journal-level dataset of works, ISSNs, and licenses for a research-ops pipeline.

Input

Paste this into the Apify Console, or send it as the run input over the API. Proxy settings are on by default; you rarely need to touch them.

{
  "query": "climate change adaptation",
  "workType": "journal-article",
  "maxResults": 3,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Output

One row per result, schema-validated before it is written. Export JSON, CSV, Excel or XML from the run, or read it over the API.

doititletypepublishercontainer_titleauthorsauthor_countpublished_datevolumeissuepageissnlicense_urllicense_countfundersis_referenced_by_count

{
  "doi": "10.1371/journal.pone.0212345",
  "title": "Example study on citation graphs",
  "type": "journal-article",
  "publisher": "Public Library of Science (PLoS)",
  "container_title": "PLOS ONE",
  "authors": [
    {
      "name": "Jane Q. Researcher",
      "orcid": "0000-0002-1234-5678",
      "affiliation": "University of Somewhere"
    }
  ],
  "author_count": 1,
  "published_date": "2023-04-12",
  "volume": "18",
  "issue": "4",
  "page": "e0212345",
  "issn": [
    "1932-6203"
  ],
  "license_url": "https://creativecommons.org/licenses/by/4.0/",
  "license_count": 1,
  "funders": [
    {
      "name": "Wellcome Trust",
      "doi": "10.13039/100004440",
      "award_numbers": [
        "WT12345"
      ]
    }
  ],
  "is_referenced_by_count": 42,
  "abstract": "<jats:p>We present an analysis of...</jats:p>",
  "url": "https://doi.org/10.1371/journal.pone.0212345"
}

Pricing

You pay only for results that land. Cap any run with maxTotalChargeUsd. See pricing & billing for worked examples.

Limitations

• Metadata only — it does not download PDFs or full text.
• The abstract field is passed through verbatim, JATS XML tags included; the Actor does not strip or reformat it.
• Free-text funder-name matching is a client-side substring match and can return false positives (e.g. "Gates" matches multiple foundations) — pass the exact Funder DOI for precision.