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reapxdev/crossref-scraper

Crossref Scraper · DOI Metadata, Authors, Journals & Citations Scrape scholarly DOI metadata, works, journal articles, authors, citations, funding, and licenses from the Crossref REST API. Fast HTTP scraper with pay-per-event pricing. Rows in this dataset 2,492 Fields 29 Collector runs behind it 50 Most recent observation 2026-08-04 Browsable presentation https://reapx.dev/data/crossref-scraper/ — 2,492 entity pages Run the collector yourself… See the full description on the dataset page: https://huggingface.co/datasets/reapxdev/crossref-scraper.

sourceHugging Facecc-by-4.0updated 2mo agoView on Hugging Face
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Dataset Card

reapX — public sources in, addressable records out

Crossref Scraper · DOI Metadata, Authors, Journals & Citations

Scrape scholarly DOI metadata, works, journal articles, authors, citations, funding, and licenses from the Crossref REST API. Fast HTTP scraper with pay-per-event pricing.

Rows in this dataset2,492
Fields29
Collector runs behind it50
Most recent observation2026-08-04
Browsable presentationhttps://reapx.dev/data/crossref-scraper/ — 2,492 entity pages
Run the collector yourselfhttps://apify.com/reapx/crossref-scraper

What this is

Every row here was returned by a real run of a public collector. Nothing is generated from a template over a keyword list: a row exists because a run observed it.

A browsable presentation of the subset that carries an addressable doi is published as 2,492 entity pages at https://reapx.dev/data/crossref-scraper/, one page per entity. This dataset is the larger of the two — rows whose payload has no field that can address a page are here and are not published there.

Provenance

Each row carries _run_id and _dataset_id, naming the collector run that produced it, so any row can be traced back to the run that observed it. Rows observed by more than one run are deduplicated on content; 8 duplicate observations were collapsed.

Files

  • crossref-scraper.jsonl — one JSON object per row, the canonical form
  • crossref-scraper.csv — the same rows flattened; nested values are JSON-encoded within their cell so they round-trip
  • dataset.json — schema.org Dataset metadata

Loading it

python
from datasets import load_dataset
ds = load_dataset("reapxdev/crossref-scraper", split="train")

A sample of the published entities

Related

  • All sources: <https://reapx.dev/data/> · machine-readable index: <https://reapx.dev/llms.txt>
  • The collector is a public Apify Actor; agents reach it through <https://mcp.apify.com>

Licence

Collected from public sources. This metadata and the published pages are CC BY 4.0; the underlying records remain under the terms of their originating source.