# OpenAIRE Research Graph Scraper (`logiover/openaire-research-graph-scraper`) Actor

Search and export research outputs, projects, organizations, data sources and researcher profiles from the OpenAIRE Graph. Cursor-based high-volume extraction for R\&D intelligence and scholarly data.

- **URL**: https://apify.com/logiover/openaire-research-graph-scraper.md
- **Developed by:** [Logiover](https://apify.com/logiover) (community)
- **Categories:** Developer tools, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 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/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## OpenAIRE Research Graph Scraper

Search and export the OpenAIRE Research Graph through its official cursor API. One Actor covers research products, funded projects, research organizations, repositories/data sources and researcher profiles, producing analysis-ready records for commercial and academic workflows.

### Buyer use cases

- R\&D and competitor intelligence
- Grant, funder and consortium discovery
- University and research-organization enrichment
- Pharma/biotech landscape analysis
- Scholarly search, bibliometrics and citation datasets
- AI/RAG corpora with authors, subjects, identifiers and provenance

OpenAIRE spans a very large research corpus. Cursor pagination bypasses the normal 10,000-result page window and lets a run save up to **500,000 unique records**.

### Input

| Field | Description | Default |
|---|---|---|
| `entityType` | `researchProducts`, `projects`, `organizations`, `dataSources`, or `persons` | `researchProducts` |
| `query` | Full-text OpenAIRE search | `artificial intelligence` |
| `countryCodes` | Optional two-letter country filters | all |
| `types` | Optional exact type labels | all |
| `fromYear` / `toYear` | Publication/start-year interval | none |
| `openAccessOnly` | Keep open/green records only | `false` |
| `maxResults` | Maximum unique records, 1–500,000 | `500` |
| `includeRawRecord` | Include the full nested API response | `false` |

Example — recent open-access climate research:

```json
{
  "entityType": "researchProducts",
  "query": "climate change",
  "fromYear": 2024,
  "openAccessOnly": true,
  "maxResults": 100000
}
```

Example — AI-funded projects:

```json
{
  "entityType": "projects",
  "query": "artificial intelligence",
  "fromYear": 2020,
  "maxResults": 50000
}
```

### Output

The normalized union schema exposes ID, entity type, title/name, project/source code, type, dates/year, description, authors, countries, language, publisher, access right, citation count, persistent identifiers, subjects, website, funded amount/total cost/currency, funding programmes, projects and participating organizations. Enable `includeRawRecord` when you need the complete entity-specific API response; leaving it disabled substantially improves bulk throughput.

```json
{
  "id": "openaire____::example",
  "entityType": "researchProducts",
  "title": "Example research article",
  "type": "publication",
  "year": 2025,
  "authors": ["Ada Example", "Linus Researcher"],
  "accessRight": "OPEN",
  "citationCount": 12,
  "identifiers": [{"scheme":"doi","value":"10.0000/example"}]
}
```

### API usage

```bash
curl -X POST "https://api.apify.com/v2/acts/YOUR_USERNAME~openaire-research-graph-scraper/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"entityType":"organizations","query":"quantum","maxResults":10000}'
```

### Source and limitations

Records come from the [OpenAIRE Graph API](https://graph.openaire.eu/docs/11.1.1/apis/graph-api/). OpenAIRE aggregates multiple providers, so field availability, deduplication, access labels, citation metrics and update times vary. Local filters apply to the records returned by OpenAIRE's relevance-ordered search; verify critical claims with the linked identifiers/providers.

### Changelog

- **2026-08-01 — v1.0.0:** Initial release. Added five graph entity types, resilient cursor pagination, local country/type/year/open-access filters, deduplication, normalized plus optional raw output, 500,000-item runs and live default/multi-entity tests.

# Actor input Schema

## `entityType` (type: `string`):

Choose the OpenAIRE Graph collection to search.

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

Full-text query sent to the official OpenAIRE Graph API. Empty searches the collection broadly.

## `countryCodes` (type: `array`):

Optional two-letter country codes applied to returned records.

## `types` (type: `array`):

Optional exact type labels, matched case-insensitively (for example publication, dataset or software).

## `fromYear` (type: `integer`):

Optional minimum publication or start year.

## `toYear` (type: `integer`):

Optional maximum publication or start year.

## `openAccessOnly` (type: `boolean`):

Only retain records marked OPEN or green open access.

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

Maximum unique records to save; cursor pagination supports exports up to 500,000 items.

## `includeRawRecord` (type: `boolean`):

Add the full nested OpenAIRE response to every item. Keep off for faster high-volume exports.

## Actor input object example

```json
{
  "entityType": "researchProducts",
  "query": "artificial intelligence",
  "countryCodes": [],
  "types": [],
  "openAccessOnly": false,
  "maxResults": 500,
  "includeRawRecord": false
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("logiover/openaire-research-graph-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("logiover/openaire-research-graph-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{}' |
apify call logiover/openaire-research-graph-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=logiover/openaire-research-graph-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/TpjOvSMGFXP4Uab2I/builds/IXbLn3KEvy4CqZe8M/openapi.json