# Crossref Scraper (`anyxsolutions/crossref-scraper`) Actor
Search 180M+ scholarly papers, books and preprints registered with Crossref, or look up works by DOI. Get titles, journals, authors with ORCID iDs and affiliations, abstracts, citation counts, funders, licenses and full-text links as clean JSON. No API key, no proxy.
- **URL**: https://apify.com/anyxsolutions/crossref-scraper.md
- **Developed by:** [Anyx Solutions](https://apify.com/anyxsolutions) (community)
- **Categories:** AI, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $2.50 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event
## What's an Apify Actor?
An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.
For examples already wired to this Actor's own input schema, see the [API](#api) section below.
Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).
# README
## Crossref Scraper
**Search 180 million scholarly works, or look papers up by DOI, and get clean metadata: authors, abstracts, citations, funders and full-text links.**
Crossref is the registry behind most DOIs: journal articles, conference papers, book chapters,
preprints, dissertations and datasets from more than 20,000 publishers. This Actor searches it
by keyword, author or journal, or looks works up by DOI, and returns one clean row per work:
title, journal, publisher, publication date, authors with ORCID iDs and affiliations, the
abstract as plain text and HTML, reference and citation counts, ISSNs, volume, issue and pages,
licenses, funders with grant numbers, and links to the full text. Filter by publication date,
work type or abstract availability, and sort by relevance, date or citations. There is no
login, no API key and no proxy to configure. Built for literature reviews, research
intelligence, bibliometrics, citation tracking and building datasets for AI and search.
### ⚡ Quick start
```json
{
"startUrls": [
{
"url": "https://search.crossref.org/search/works?q=microplastics+in+drinking+water&from_ui=yes"
}
],
"maxItems": 5
}
```
Or search by keyword with filters:
```json
{
"searchTerms": ["crispr off-target effects"],
"dateFrom": "2023",
"type": "journal-article",
"hasAbstract": true,
"sortBy": "is-referenced-by-count",
"maxItems": 50
}
```
### 🧩 Input
| Field | Type | Required | Default | Description |
| -------------------- | ------- | -------- | ---------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `startUrls` | array | no | — | Crossref search URLs (`search.crossref.org/search/works?q=…`) or DOI links (`https://doi.org/10.1145/3641289`). |
| `searchTerms` | array | no | — | Words to search titles, abstracts, authors and journals for, one search per entry. |
| `author` | string | no | — | Narrow every search to works by this author. On its own, it searches for the author's works. |
| `dois` | array | no | — | DOIs to look up, such as `10.1145/3641289`. DOI links and the `doi:` prefix work too. |
| `issns` | array | no | — | Journal ISSNs whose works to list, such as `0028-0836` for Nature. |
| `dateFrom` | string | no | — | Published from: only works published on or after this date (`2024`, `2024-03` or `2024-03-01`). |
| `dateTo` | string | no | — | Published until: only works published on or before this date. |
| `type` | string | no | — | Work type: `journal-article`, `proceedings-article`, `book-chapter`, `book`, `posted-content` (preprints), `dissertation`, `report`, `dataset` and more. |
| `hasAbstract` | boolean | no | `false` | Only works with an abstract. |
| `sortBy` | string | no | `"relevance"` | Sort by `relevance`, `published` (newest first) or `is-referenced-by-count` (most cited). |
| `maxItems` | integer | no | — | Maximum works per search term, start URL or journal. The input form starts at 5; leave it empty to get every match. |
| `proxyConfiguration` | object | no | `{ "useApifyProxy": false }` | Proxy settings. Crossref's public data needs no proxy. |
Give at least one of `startUrls`, `searchTerms`, `author`, `dois` or `issns`. The filters and the
sort order apply to every search and journal; DOI lookups always return the one work.
**Search URLs.** Search on [search.crossref.org](https://search.crossref.org/) and paste the address
of the results page. "Sort by year" and "Filter on this publication" carry over.
### 📤 Output
Each work is one dataset row. Fields Crossref has no value for are `null`, or an empty list.
#### Fields
| Field | Type | Description |
| ----------------- | ------ | ------------------------------------------------------------------------------------------------------------------------------ |
| `doi` | string | The work's DOI. |
| `url` | string | The DOI link, which resolves to the publisher's page. |
| `title` | string | Title. |
| `subtitle` | string | Subtitle, when set. |
| `containerTitle` | string | The journal, book or proceedings the work appears in. |
| `publisher` | string | Publisher. |
| `type` | string | Work type, such as `journal-article`, `book-chapter` or `posted-content`. |
| `publishedDate` | string | Publication date (ISO 8601: `2024-03-29`, or `2024-03` / `2024` when only that is known). |
| `authors` | array | Authors in order: `given`, `family`, `name`, `orcid` (iD link) and `affiliations`. |
| `abstractText` | string | Abstract as plain text, one paragraph per line. |
| `abstractHtml` | string | Abstract as HTML, with italics, sub/superscripts, section headings and paragraphs. |
| `referencesCount` | number | Number of references the work cites. |
| `citedByCount` | number | Number of Crossref works that cite this one. |
| `subjects` | array | Subject areas, when the publisher sets them. |
| `issn` | array | ISSNs of the journal. |
| `isbn` | array | ISBNs, for books and chapters. |
| `volume` | string | Volume. |
| `issue` | string | Issue. |
| `page` | string | Page range. |
| `articleNumber` | string | Article number, for journals that number articles instead of pages. |
| `language` | string | Language code, when set. |
| `licenseUrls` | array | License links, such as a Creative Commons license. |
| `funders` | array | Funders: `name`, `doi` (Funder Registry ID) and `awards` (grant numbers). |
| `fullTextLinks` | array | Full-text links the publisher lists: `url`, `contentType` and `intendedApplication` (`text-mining`, `similarity-checking`, …). |
| `publisherUrl` | string | The page the DOI resolves to. |
| `sourceUrl` | string | The search, journal or DOI link this work was found through. |
Example output
```json
{
"doi": "10.1145/3641289",
"url": "https://doi.org/10.1145/3641289",
"title": "A Survey on Evaluation of Large Language Models",
"subtitle": null,
"containerTitle": "ACM Transactions on Intelligent Systems and Technology",
"publisher": "Association for Computing Machinery (ACM)",
"type": "journal-article",
"publishedDate": "2024-03-29",
"authors": [
{
"given": "Yupeng",
"family": "Chang",
"name": "Yupeng Chang",
"orcid": "https://orcid.org/0000-0001-7178-6088",
"affiliations": [
"School of Artificial Intelligence, Jilin University, Changchun, China"
]
},
{
"given": "Xu",
"family": "Wang",
"name": "Xu Wang",
"orcid": "https://orcid.org/0009-0001-5904-5313",
"affiliations": [
"School of Artificial Intelligence, Jilin University, Changchun, China"
]
}
],
"abstractText": "Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. …",
"abstractHtml": "Large language models (LLMs) are gaining increasing popularity in both academia and industry, … focusing on three key dimensions: what to evaluate, where to evaluate, and how to evaluate. …
",
"referencesCount": 267,
"citedByCount": 2920,
"subjects": [],
"issn": ["2157-6904", "2157-6912"],
"isbn": [],
"volume": "15",
"issue": "3",
"page": "1-45",
"articleNumber": null,
"language": "en",
"licenseUrls": [
"https://www.acm.org/publications/policies/copyright_policy#Background"
],
"funders": [{ "name": "NSF", "doi": null, "awards": ["III-2106758"] }],
"fullTextLinks": [
{
"url": "https://dl.acm.org/doi/10.1145/3641289",
"contentType": "unspecified",
"intendedApplication": "text-mining"
},
{
"url": "https://dl.acm.org/doi/pdf/10.1145/3641289",
"contentType": "unspecified",
"intendedApplication": "similarity-checking"
}
],
"publisherUrl": "https://dl.acm.org/doi/10.1145/3641289",
"sourceUrl": "https://doi.org/10.1145/3641289"
}
```