# ORCID Researcher Profile Scraper (`parseforge/orcid-researcher-scraper`) Actor Scrape researcher profiles from ORCID including names, biographies, publication counts, current affiliations, employment history, and external identifiers like Scopus ID. Search by name or fetch detailed profiles by ORCID ID. - **URL**: https://apify.com/parseforge/orcid-researcher-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Education, Lead generation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $6.50 / 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 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 ![ParseForge Banner](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner.jpg) ## 🔬 ORCID Researcher Profile Scraper Academic hiring teams, research agencies, and science publishers all need clean researcher data. This tool pulls structured profiles from the global ORCID registry - names, institutions, emails, and identifiers - so you can build contact lists, verify authors, or map research communities. > **The ORCID Scraper collects academic researcher profiles with ORCID IDs, names, institutions, emails, and public profile URLs. Search by keyword, institution, or direct ORCID ID lookup.** ### ✨ What Does It Do - 🧑‍🔬 **Researcher profiles** - given names, family names, credit names, and alternate names - 🆔 **ORCID identifiers** - the 16-digit ID that uniquely identifies every registered researcher - 🏛️ **Institutions** - affiliations with universities, research labs, and companies - 📧 **Public emails** - contact addresses when the researcher has made them public - 🔍 **Powerful search** - query by keyword, name, or full affiliation name - 🔗 **Direct lookup** - fetch a specific researcher by ORCID ID ### 🔧 Input - **Search Query** - keyword or ORCID query syntax (e.g. `machine learning`, `given-names:John AND family-name:Smith`) - **Institution** - filter by institution name (e.g. `Stanford`, `MIT`, `Oxford`) - **ORCID ID** - look up one researcher directly (e.g. `0000-0001-2345-6789`) - **Max Items** - free users get 10 records, paid users up to 1,000,000 ```json { "query": "artificial intelligence", "maxItems": 200 } ```` ### 📊 Output Each researcher record includes ID, name, affiliation, and contact fields. Download as JSON, CSV, or Excel. | 📌 Field | 📄 Description | |----------|---------------| | 🆔 orcidId | 16-digit ORCID identifier | | 👤 givenNames | First/given name | | 👤 familyNames | Last/family name | | 📝 creditName | How the researcher prefers to be cited | | 🏛️ institutions | Affiliated universities or organizations | | 📧 emails | Public email addresses | | 🔗 profileUrl | Public ORCID profile page | ```json { "orcidId": "0000-0002-1825-0097", "givenNames": "Josiah", "familyNames": "Carberry", "creditName": "J. Carberry", "otherNames": ["Josiah S. Carberry"], "emails": ["j.carberry@example.edu"], "institutions": ["Brown University", "Wesleyan University"], "profileUrl": "https://orcid.org/0000-0002-1825-0097", "scrapedAt": "2026-04-10T12:00:00.000Z" } ``` ### 💎 Why Choose the ORCID Researcher Scraper? | Feature | Our Tool | Manual ORCID Search | |---------|----------|---------------------| | Bulk profile collection | ✅ Up to 1M records | ❌ Page-by-page | | Keyword + institution filters | ✅ Combined | ⚠️ Limited UI | | Direct ID lookup | ✅ Instant | ✅ Yes | | Email + institution capture | ✅ Structured | ⚠️ Buried in profile | | Export to JSON/CSV/Excel | ✅ Yes | ❌ Not supported | | Scheduled monitoring | ✅ Daily/weekly | ❌ Not possible | ### 📋 How to Use 1. **Sign Up** - [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) 2. **Configure** - set your search query, institution filter, or ORCID ID 3. **Run It** - click Start and get researcher records in seconds No coding, no manual profile clicking. ### 🎯 Business Use Cases - 🎓 **Academic recruiting** - build candidate lists for faculty positions by research area - 📚 **Publisher outreach** - identify authors in a specific field for peer review or editorial invites - 🔬 **Grant programs** - find potential reviewers and awardees by keyword or institution - 📊 **Bibliometric research** - map researcher communities across disciplines and institutions - 🏛️ **University rankings** - count active researchers at an institution for ranking studies - 🤝 **Partnership discovery** - find collaborators who share your research focus ### ❓ FAQ 🧑‍🔬 **What is ORCID?** ORCID is a nonprofit that issues unique identifiers to researchers worldwide, helping to disambiguate authors with the same name and link them to their work. 🔍 **How do ORCID search queries work?** You can use free text (e.g. `climate change`) or structured fields like `given-names:`, `family-name:`, `affiliation-org-name:`. See the ORCID documentation for the full syntax. 📧 **Will I always get an email?** No. Researchers can choose whether to make emails public. Many do not, so the `emails` field can be empty. 🆔 **How do I look up one specific researcher?** Paste their ORCID ID (the 16-digit code from their profile URL) into the `orcidId` field. This overrides the search query. 🌍 **Does it cover international researchers?** Yes. ORCID has millions of registered researchers worldwide across every discipline. ### 🔗 Integrate ORCID Researcher Scraper with any app - [Make](https://docs.apify.com/platform/integrations/make) - automate researcher contact imports - [Zapier](https://docs.apify.com/platform/integrations/zapier) - push new profiles into your CRM - [Slack](https://docs.apify.com/platform/integrations/slack) - share recruiting shortlists with your team - [Google Sheets](https://docs.apify.com/platform/integrations/drive) - build talent spreadsheets - [Webhooks](https://docs.apify.com/platform/integrations/webhooks) - trigger workflows on completion ### 💡 Recommended Actors Looking for more data collection tools? Check out these related actors: | Actor | Description | Link | |-------|-------------|------| | Hugging Face Model Scraper | Collect AI model metadata | [Link](https://apify.com/parseforge/hugging-face-model-scraper) | | GreatSchools Scraper | School ratings and district data | [Link](https://apify.com/parseforge/greatschools-scraper) | | FINRA BrokerCheck Scraper | Broker registration lookups | [Link](https://apify.com/parseforge/finra-brokercheck-scraper) | | Pitchbook Investors Scraper | Private equity and VC profiles | [Link](https://apify.com/parseforge/pitchbook-investors-scraper) | | Hubspot Marketplace Scraper | Hubspot app listings | [Link](https://apify.com/parseforge/hubspot-marketplace-scraper) | **Pro Tip:** 💡 Browse the full [ParseForge catalog](https://apify.com/parseforge) to find more data tools. ### 🆘 Need Help? - Check the FAQ section above for common questions - Visit the [Apify documentation](https://docs.apify.com) for platform guides - Contact us at [Tally contact form](https://tally.so/r/BzdKgA) ### ⚠️ Disclaimer > This Actor is an independent tool and is not affiliated with, endorsed by, or connected to ORCID or any university. It collects only publicly available researcher profile data that users have chosen to share. # Actor input Schema ## `maxItems` (type: `integer`): Free users: Limited to 10 researchers. Paid users: Optional, max 1,000,000 ## `query` (type: `string`): ORCID search query. Examples: 'machine learning', 'given-names:John AND family-name:Smith', 'affiliation-org-name:"Stanford"' ## `institution` (type: `string`): Filter by institution name (overrides query if set). ## `orcidId` (type: `string`): Look up a specific researcher by their ORCID ID (e.g. '0000-0001-2345-6789'). Overrides search. ## Actor input object example ```json { "maxItems": 10, "query": "artificial intelligence" } ``` # Actor output Schema ## `overview` (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, "query": "artificial intelligence" }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/orcid-researcher-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 = { "maxItems": 10, "query": "artificial intelligence", } # Run the Actor and wait for it to finish run = client.actor("parseforge/orcid-researcher-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 '{ "maxItems": 10, "query": "artificial intelligence" }' | apify call parseforge/orcid-researcher-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/orcid-researcher-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ORCID Researcher Profile Scraper", "description": "Scrape researcher profiles from ORCID including names, biographies, publication counts, current affiliations, employment history, and external identifiers like Scopus ID. Search by name or fetch detailed profiles by ORCID ID.", "version": "1.0", "x-build-id": "8go6O8Yyhm7gi8sik" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~orcid-researcher-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-orcid-researcher-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~orcid-researcher-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-orcid-researcher-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~orcid-researcher-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-orcid-researcher-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 researchers. Paid users: Optional, max 1,000,000" }, "query": { "title": "Search Query", "type": "string", "description": "ORCID search query. Examples: 'machine learning', 'given-names:John AND family-name:Smith', 'affiliation-org-name:\"Stanford\"'" }, "institution": { "title": "Institution", "type": "string", "description": "Filter by institution name (overrides query if set)." }, "orcidId": { "title": "ORCID ID", "type": "string", "description": "Look up a specific researcher by their ORCID ID (e.g. '0000-0001-2345-6789'). Overrides search." } } }, "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 } } } } } } } } } } ```