# DataCite Scraper (Datasets, Software, Research Outputs) (`scrapyx/datacite-scraper`) Actor

Search DataCite, the CC0 DOI registry for research outputs beyond journal articles -- 133M+ datasets, software, samples, instruments, images, text, workflows and dissertations. Lucene query plus filters (type, publisher, year, provider, ORCID, ROR, funding). Cursor pagination past 10k. DOI lookup.

- **URL**: https://apify.com/scrapyx/datacite-scraper.md
- **Developed by:** [Ibnu Adzim](https://apify.com/scrapyx) (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 $1.40 / 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

## DataCite Scraper (Datasets, Software, Research Outputs)

Search **[DataCite](https://datacite.org)** — the DOI registry for the
research outputs that *aren't* journal articles: **datasets, software,
samples, instruments, images, text, workflows, computational notebooks,
dissertations, preprints**. ~133M DOIs, metadata **CC0**, no key, no login.

Companion to `openalex-scholar-scraper` (works), `crossref-works-scraper`
(articles) and `pubmed-articles-scraper` (biomedical).

- **`search`** — a Lucene `query` and/or structured filters (resource type,
  publisher / repository, publication year range, provider, client, DOI
  prefix, ORCID, ROR, subject, has-citations / views / downloads / funding).
  **Cursor-paginated** — no 10,000-result ceiling.
- **`dois`** — look up specific DOIs → the full record each.

| Record type | One per | Carries |
| --- | --- | --- |
| `SEARCH_SUMMARY` | search run | composed `query`, `upstreamCount`, `resultsReturned`, `cursorPages`, `filtersApplied` |
| `RESULT` | DOI | `doi`, `title`, `resourceTypeGeneral`, `publisher`, `publicationYear`, `creators` (+ ORCID + affiliation), `description`, `subjects`, `citationCount` / `viewCount` / `downloadCount`, `license`, `geoLocations`, `fundingReferences`, `relatedIdentifiers`, `containerTitle` |
| `ERROR` | bad input / missing DOI | `_error` + `_errorDetail` |

Every `RESULT` row carries the verbatim DataCite record in `raw` (drop with
`slimOutput`).

### Things this API will mislead you about

Each is measured, and each has a scenario in
`tests/smoke/datacite-scraper_traps.sh` (10/10 passing).

**`page[number]` pagination is capped at 10,000 results.** This Actor uses
`page[cursor]` + `links.next` throughout, which has no ceiling —
`deepPaginationViaCursor` on the summary confirms it.

**An unknown `resourceType` returns `total: 0`, silently** — a "no such
output" that is really "no such type". `resourceType` is validated against
DataCite's controlled list up front.

**An empty `query` matches all 133M records.** A query is not required, but a
query *or* a filter is — a bare search is rejected.

**`page[size]` maxes at 1000** (a larger value is silently clamped).

**`titles`, `creators`, `descriptions`, `subjects`, `rightsList` are arrays
of objects, often empty**, and `creators[].name` can be `"Anonymous"`. The
normaliser takes the first title, joins creator names into `creatorNames`,
and pulls the first `Abstract`-type description.

**A DOI lookup is case-insensitive** and the slash may be raw or `%2F`. A DOI
that DataCite never registered (e.g. a Crossref journal DOI like
`10.1038/nature12373`) is an honest HTTP 404 → `record_not_found` with a hint
to try `crossref-works-scraper`.

### Notes on cost

`search`: one request per 1000 results (cursor pages). `dois`: one request per
DOI. No proxy needed.

# Actor input Schema

## `mode` (type: `string`):

`search` runs a query / filters against the DataCite index (133M+ DOIs). `dois` looks up specific DOIs.

## `query` (type: `string`):

`search` mode. Lucene syntax against titles / descriptions / creators / subjects, e.g. `climate model`, `"sea surface temperature"`, `creators.name:Smith`. Optional if you supply filters instead.

## `dois` (type: `array`):

`dois` mode. One per line: `10.5281/zenodo.1234567`, a `https://doi.org/...` URL, or `doi:...`. A DOI that DataCite did not register (e.g. a Crossref journal DOI) becomes a `record_not_found` error.

## `resourceType` (type: `string`):

`search` filter. One DataCite type: `dataset`, `software`, `text`, `image`, `physical-object`, `audiovisual`, `collection`, `conference-paper`, `dissertation`, `preprint`, `report`, `workflow`, `computational-notebook`, `model`, `instrument`, `other`. An unknown value would return zero results silently, so it is rejected.

## `publisher` (type: `string`):

`search` filter. e.g. `Zenodo`, `Dryad`, `PANGAEA`, `figshare`, `Harvard Dataverse`.

## `fromPublicationYear` (type: `integer`):

`search` filter. Keep DOIs published in or after this year.

## `toPublicationYear` (type: `integer`):

`search` filter. Keep DOIs published in or before this year.

## `createdYear` (type: `integer`):

`search` filter. Year the DOI metadata was first created at DataCite.

## `registeredYear` (type: `integer`):

`search` filter. Year the DOI was registered (findable).

## `providerId` (type: `string`):

`search` filter. A DataCite member (consortium) id, e.g. `cern`, `bl` (British Library), `tib`.

## `clientId` (type: `string`):

`search` filter. A specific repository id, e.g. `cern.zenodo`, `dryad.dryad`, `pangaea.repository`.

## `prefix` (type: `string`):

`search` filter. A DOI prefix, e.g. `10.5281` (Zenodo), `10.5061` (Dryad).

## `personId` (type: `string`):

`search` filter. An ORCID (`0000-0001-2345-6789` or the full URL) — DOIs with this person as a creator or contributor.

## `affiliationId` (type: `string`):

`search` filter. A ROR id — DOIs with a creator affiliated to this organisation.

## `subject` (type: `string`):

`search` filter. A subject / keyword phrase, matched against `subjects.subject`.

## `hasCitations` (type: `boolean`):

`search` filter. Keep only DOIs with at least one recorded citation.

## `hasViews` (type: `boolean`):

`search` filter. Keep only DOIs with at least one recorded view.

## `hasDownloads` (type: `boolean`):

`search` filter. Keep only DOIs with at least one recorded download.

## `hasFunding` (type: `boolean`):

`search` filter. Keep only DOIs with a funding reference.

## `rawQuery` (type: `string`):

Appended verbatim (AND-joined) to the composed `query`. Full Elasticsearch query-string syntax, e.g. `types.resourceType:"Specimen"`, `container.title:*`.

## `slimOutput` (type: `boolean`):

By default every RESULT row carries the verbatim DataCite record in `raw`. Turn on for the normalised fields only.

## `maxResults` (type: `integer`):

`search` mode cap. Cursor pagination is used, so this can exceed 10,000.

## `maxConcurrency` (type: `integer`):

Parallel in-flight requests (matters for `dois` mode).

## `minRequestInterval` (type: `number`):

Politeness pacing for a non-profit's infrastructure.

## `proxyConfiguration` (type: `object`):

Optional. No anti-bot layer, so a proxy is OFF by default.

## Actor input object example

```json
{
  "mode": "search",
  "query": "sea level rise",
  "hasCitations": false,
  "hasViews": false,
  "hasDownloads": false,
  "hasFunding": false,
  "slimOutput": false,
  "maxResults": 500,
  "maxConcurrency": 4,
  "minRequestInterval": 0.3,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `items` (type: `string`):

One row per scraped record. See the dataset's default view for field definitions.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "sea level rise"
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapyx/datacite-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "query": "sea level rise" }

# Run the Actor and wait for it to finish
run = client.actor("scrapyx/datacite-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "sea level rise"
}' |
apify call scrapyx/datacite-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapyx/datacite-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/RBqxe6WIIJ0HPFQWT/builds/9RfD0acuTlrqxgtHb/openapi.json