# Dryad Research Datasets Scraper (`parseforge/datadryad-datasets-scraper`) Actor
Gather structured records from Datadryad Datasets with names, identifiers, dates, descriptions, status flags and source links. Loved by research, intelligence and operational dashboards. Run on demand or on a recurring schedule and feed every row into your favourite analytics or workflow stack.
- **URL**: https://apify.com/parseforge/datadryad-datasets-scraper.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** News, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
Pay per usage
This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## ๐ Dryad Research Datasets Scraper
> ๐ **Get 70,000+ open research datasets from the Dryad data repository.** available as a dataset, or data.
> ๐ **Last updated** 2026-05-27 ยท **๐ 6+ fields** per record ยท Live data
Pulls research datasets from datadryad.org with DOI, title, authors (incl. ORCID and affiliation), abstract, related publication ISSN, storage size and access URL.
---
### Target Audience / Use Cases
| ๐ฏ Target Audience | ๐ก Primary Use Cases |
|---|---|
| Analysts | Source data extraction |
| Researchers | Academic and policy studies |
| Journalists | Data-driven storytelling |
| Businesses | Market and competitive intelligence |
| Developers | Power data products |
---
### ๐ What this scraper does
- Connects to the official source
- Pulls every record matching your filters
- Returns structured rows ready for analysis
- Bulk dataset outputs
> ๐ก **Why it matters:** skip manual collection and get clean structured data in seconds.
---
### ๐ฌ Full Demo
๐ง Coming soon
---
### โ๏ธ Input
Field
Type
Description
maxItems
integer
Free users: Limited to 10. Paid users: Optional, max 1,000,000.
query
string
Optional free-text search query.
````
{
"maxItems": 5
}
````
> โ ๏ธ **Good to Know:** the actor returns whatever the live source returns at runtime.
---
### ๐ Output
Key fields: identifier, title, authors, abstract, relatedPublicationISSN, storageSize, sourceUrl, scrapedAt.
---
### โจ Why choose this Actor
- ๐ข Backed by official source data
- ๐ข No login or API key required
- ๐ข Up to 1,000,000 records per paid run
- ๐ข Bulk dataset outputs
---
### ๐ How it compares to alternatives
| Option | Free | Bulk | Live |
|---|---|---|---|
| Source website | Yes | No | Yes |
| **ParseForge Scraper** | **Yes** | **Yes** | **Live** |
---
### ๐ How to use
1. [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp)
2. Open this actor in the Apify Console
3. Set your input filters (or use the prefill)
4. Click **Start** and wait for the run to finish
5. open the dataset
---
### ๐ผ Business use cases
- Market intelligence
- Competitive monitoring
- Lead research
- Trend analysis
---
### ๐ Automating Dryad Research Datasets Scraper
Trigger runs from Make, Zapier, n8n, Airbyte, GitHub Actions, Google Sheets, Slack, Airtable or any HTTP client via the Apify API.
---
### ๐ Beyond business use cases
- Research and academic studies
- Personal data projects
- Non-profit transparency
- Tech experimentation
---
### ๐ค Ask an AI assistant
Open the run URL with ChatGPT, Claude, Perplexity or Copilot for instant insights.
---
### โ Frequently Asked Questions
**Is this affiliated with the source?** No.
**Is login required?** No, only public data.
**Does it open in a spreadsheet?** Yes.
**Is the data live?** Yes, every run.
**What's the maximum number of records?** Up to 1,000,000 on paid plans.
---
### ๐ Integrate with any app
Apify API works with REST, webhooks, Make, Zapier, Airbyte, n8n, Slack, Google Drive, GitHub, Airtable.
---
### ๐ Recommended Actors
| Actor | What it does |
|---|---|
| [Google Maps Scraper](https://apify.com/compass/crawler-google-places) | Business listings from Google Maps |
| [LinkedIn Profile Scraper](https://apify.com/curious_coder/linkedin-profile-scraper) | Public LinkedIn profile data |
| [Amazon Product Scraper](https://apify.com/junglee/amazon-crawler) | Amazon product listings |
> ๐ก **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge).
**๐ Need Help?** [Open our contact form](https://tally.so/r/BzdKgA)
> **โ ๏ธ Disclaimer:** independent tool, not affiliated with the source. Only publicly available data collected.
# Actor input Schema
## `maxItems` (type: `integer`):
Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000
## `query` (type: `string`):
Optional free-text query.
## Actor input object example
```json
{
"maxItems": 10
}
````
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"maxItems": 10
};
// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/datadryad-datasets-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ 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);
});
// ๐ Want to learn more ๐? Go to โ 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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "maxItems": 10 }
# Run the Actor and wait for it to finish
run = client.actor("parseforge/datadryad-datasets-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"maxItems": 10
}' |
apify call parseforge/datadryad-datasets-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=parseforge/datadryad-datasets-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Dryad Research Datasets Scraper",
"description": "Gather structured records from Datadryad Datasets with names, identifiers, dates, descriptions, status flags and source links. Loved by research, intelligence and operational dashboards. Run on demand or on a recurring schedule and feed every row into your favourite analytics or workflow stack.",
"version": "0.1",
"x-build-id": "WujwMxMtue1xA0fOT"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/parseforge~datadryad-datasets-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-parseforge-datadryad-datasets-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/parseforge~datadryad-datasets-scraper/runs": {
"post": {
"operationId": "runs-sync-parseforge-datadryad-datasets-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/parseforge~datadryad-datasets-scraper/run-sync": {
"post": {
"operationId": "run-sync-parseforge-datadryad-datasets-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"maxItems": {
"title": "Max Items",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000"
},
"query": {
"title": "Search query",
"type": "string",
"description": "Optional free-text query."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```