# Figshare Scraper (`crawlerbros/figshare-scraper`) Actor This actor extracts metadata and content information from Figshare, one of the world's largest open research data repositories. It supports full-text keyword search, direct article ID lookup, and institution-specific article browsing across all Figshare content types. - **URL**: https://apify.com/crawlerbros/figshare-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Automation, Developer tools, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 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 ## Figshare Scraper Scrape research articles, datasets, code, figures, and more from [Figshare](https://figshare.com/) using its public REST API — no authentication or proxy required. ### What It Does This actor extracts metadata and content information from Figshare, one of the world's largest open research data repositories. It supports full-text keyword search, direct article ID lookup, and institution-specific article browsing across all Figshare content types. ### Key Features - **No authentication required** — uses the public Figshare API - **Three modes**: keyword search, fetch by ID, or browse by institution - **Filter by content type**: datasets, papers, theses, code, figures, presentations, and more - **Full detail extraction**: authors, categories, tags, license, files, DOI - **HTML description stripping** — descriptions are returned as clean plain text - **Automatic pagination** — retrieves up to 1,000 results per run ### Input Fields | Field | Type | Description | |-------|------|-------------| | `mode` | Select | `searchArticles` (default), `getById`, or `searchByInstitution` | | `searchQuery` | String | Keyword query (e.g. `climate change`, `CRISPR`) | | `itemType` | Select | Filter by content type (see table below) | | `articleIds` | Array | Figshare article IDs for `getById` mode | | `institutionId` | String | Institution numeric ID for `searchByInstitution` mode | | `maxItems` | Integer | Max results to return (1–1000, default 50) | #### Item Types | Value | Type | |-------|------| | (empty) | All types | | `1` | Figure | | `2` | Media | | `3` | Dataset | | `4` | Poster | | `5` | Paper | | `6` | Presentation | | `7` | Thesis | | `8` | Code | | `9` | Preprint | ### Output Fields Each item in the dataset contains: | Field | Type | Description | |-------|------|-------------| | `articleId` | Integer | Unique Figshare article ID | | `title` | String | Article title | | `description` | String | Plain-text abstract/description (HTML stripped) | | `doi` | String | Digital Object Identifier | | `publishedDate` | String | Publication date (ISO 8601) | | `modifiedDate` | String | Last modified date (ISO 8601) | | `authors` | Array | List of author full names | | `tags` | Array | Keyword tags | | `categories` | Array | Subject category names | | `license` | String | License name (e.g. `CC BY 4.0`) | | `figshareUrl` | String | Public URL on Figshare | | `sourceUrl` | String | Same as `figshareUrl` | | `thumbUrl` | String | Thumbnail image URL | | `downloadUrl` | String | Direct download URL for the primary file | | `itemType` | String | Content type name (e.g. `dataset`, `paper`) | | `citation` | String | Full citation string | | `viewCount` | Integer | Number of views (when available) | | `citationCount` | Integer | Number of citations (when available) | | `recordType` | String | Always `"article"` | | `scrapedAt` | String | Timestamp when the record was scraped | ### Example Output ```json { "articleId": 32513898, "title": "Perspectives of Allied Health Professionals on Digital Health Services in South Australia", "description": "This research project explores the perspectives of allied health professionals on digital health services in South Australia.", "doi": "10.25909/32513898.v1", "publishedDate": "2026-05-30T02:03:44Z", "modifiedDate": "2026-05-30T02:03:44Z", "authors": ["Muhammad Khan"], "tags": ["digital health activism"], "categories": ["Audiology", "Occupational therapy", "Physiotherapy", "Speech pathology"], "license": "CC BY 4.0", "figshareUrl": "https://adelaide.figshare.com/articles/poster/...", "sourceUrl": "https://adelaide.figshare.com/articles/poster/...", "thumbUrl": "https://s3-eu-west-1.amazonaws.com/ppreviews-adelaide-.../thumb.png", "downloadUrl": "https://ndownloader.figshare.com/files/65104542", "itemType": "poster", "citation": "Khan, Muhammad (2026). Perspectives of Allied Health...", "recordType": "article", "scrapedAt": "2026-05-30T10:00:00.000000+00:00" } ```` ### Use Cases - **Research discovery**: Find datasets or papers by keyword across all disciplines - **Data science**: Collect open datasets for analysis and modeling - **Literature reviews**: Gather papers, theses, and preprints by topic - **Institution profiling**: Browse all public outputs from a specific university - **Open science auditing**: Track open data and code availability by subject - **Citation analysis**: Collect DOIs for downstream citation graph work ### FAQs **Q: Does this require an API key?** A: No. The Figshare public API is freely accessible without authentication. **Q: How many results can I get?** A: Up to 1,000 per run. Figshare hosts millions of items. **Q: What does `searchByInstitution` mode do?** A: It retrieves all public articles published by a specific institution on Figshare. You need the institution's numeric ID (e.g., University of Manchester = `2`). **Q: Are descriptions HTML-free?** A: Yes. The actor strips all HTML tags from descriptions, returning clean plain text. **Q: Why is `viewCount` sometimes absent?** A: The Figshare public API does not always return view/citation statistics in the article detail endpoint. The field is only included when the data is available. **Q: Can I search for code repositories?** A: Yes — set `itemType` to `8` (Code) and use any keyword in `searchQuery`. **Q: How fresh is the data?** A: The Figshare API returns live data. New uploads appear within minutes of publication. # Actor input Schema ## `mode` (type: `string`): Scraping mode: search articles, fetch by ID, or search by institution. ## `searchQuery` (type: `string`): Keyword search query (e.g. 'climate change', 'neural networks', 'protein folding'). ## `itemType` (type: `string`): Filter by Figshare item type. ## `articleIds` (type: `array`): List of Figshare article IDs to fetch (used in 'Get by ID' mode). Example: \[21096680, 32513898]. ## `institutionId` (type: `string`): Figshare institution ID for 'Search by Institution' mode (e.g. '2'). ## `maxItems` (type: `integer`): Maximum number of articles to return. ## Actor input object example ```json { "mode": "searchArticles", "searchQuery": "climate change", "itemType": "3", "maxItems": 10 } ``` # 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 = { "mode": "searchArticles", "searchQuery": "climate change", "itemType": "3", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/figshare-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "mode": "searchArticles", "searchQuery": "climate change", "itemType": "3", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/figshare-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 '{ "mode": "searchArticles", "searchQuery": "climate change", "itemType": "3", "maxItems": 10 }' | apify call crawlerbros/figshare-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/figshare-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Figshare Scraper", "description": "This actor extracts metadata and content information from Figshare, one of the world's largest open research data repositories. It supports full-text keyword search, direct article ID lookup, and institution-specific article browsing across all Figshare content types.", "version": "1.0", "x-build-id": "rV8tanazn9XhSM7QK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~figshare-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-figshare-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/crawlerbros~figshare-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-figshare-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/crawlerbros~figshare-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-figshare-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": { "mode": { "title": "Mode", "enum": [ "searchArticles", "getById", "searchByInstitution" ], "type": "string", "description": "Scraping mode: search articles, fetch by ID, or search by institution.", "default": "searchArticles" }, "searchQuery": { "title": "Search Query", "type": "string", "description": "Keyword search query (e.g. 'climate change', 'neural networks', 'protein folding')." }, "itemType": { "title": "Item Type", "enum": [ "", "1", "2", "3", "4", "5", "6", "7", "8", "9" ], "type": "string", "description": "Filter by Figshare item type.", "default": "" }, "articleIds": { "title": "Article IDs", "type": "array", "description": "List of Figshare article IDs to fetch (used in 'Get by ID' mode). Example: [21096680, 32513898]." }, "institutionId": { "title": "Institution ID", "type": "string", "description": "Figshare institution ID for 'Search by Institution' mode (e.g. '2')." }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of articles to return.", "default": 50 } } }, "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 } } } } } } } } } } ```