ORCID Researchers Scraper (Profiles, Affiliations & Works)

Here is one real result, with every field the actor returns (all three AI add-ons enabled). The long biography and the affiliations / recentWorks arrays are trimmed with a [trimmed] marker, and source em dashes are rendered as hyphens; every value shown is otherwise real:

{
  "orcidId": "0000-0002-9510-6777",
  "orcidUri": "https://orcid.org/0000-0002-9510-6777",
  "givenNames": "DR. GOUTAM",
  "familyName": "SARKER, Ph.D. (Machine Learning)",
  "creditName": null,
  "fullName": "DR. GOUTAM SARKER, Ph.D. (Machine Learning)",
  "otherNames": [],
  "biography": "Dr. Goutam Sarker is an Eminent Retired Associate Professor and Former Head in Computer Science and Engineering Department, NIT Durgapur, INDIA. He received his B.E. (Electronics, 1982), M.E. (1986) and Ph.D. (Machine Learning, 1994) from Jadavpur University [trimmed]",
  "country": "IN",
  "keywords": ["Artificial Intelligence", "Machine Learning and Machine Transcription", "Biometric Base Person Identification", "Deep Learning", "Data Science", "Data Mining", "Pattern Recognition and Computer Vision", "Astronomy, Astrophysics and Space Science"],
  "websites": ["http://sites.google.com/view/gsarker-general-", "http://sites.google.com/view/gsarker-astronomy-", "http://sites.google.com/view/gsarker-meditation-"],
  "websiteNames": ["General Website", "ASTRONOMY Website", "Meditation Website"],
  "linkedinUrl": null,
  "publicEmail": "dr.goutamsarker@gmail.com",
  "externalIds": [],
  "scopusAuthorId": null,
  "researcherId": null,
  "isni": null,
  "currentAffiliationOrg": "National Institute of Technology Durgapur",
  "currentAffiliationRole": "Retired Associate Professor (Present position)",
  "currentAffiliationCity": "Durgapur",
  "currentAffiliationCountry": "IN",
  "currentAffiliationRorId": null,
  "topEducationOrg": "Jadavpur University Faculty of Engineering and Technology",
  "topEducationRole": "Ph.D.(Engineering)",
  "employmentsCount": 1,
  "educationsCount": 3,
  "affiliations": [
    "National Institute of Technology Durgapur - Retired Associate Professor (Present position) (1998-2025) Durgapur, IN",
    "Jadavpur University Faculty of Engineering and Technology - Ph.D.(Engineering) (1990-1994) Kolkata, IN"
  ],
  "worksCount": 102,
  "topWorkTitle": "20  K. Roy, Sarker G. (2013),A Location Invariant Face Identification and Localization with Modified RBF Network , International Conference on Computer and Systems ICCS-2013, 21-22 September, 2013, pp - 23-28, Bardhaman.",
  "topWorkYear": null,
  "topWorkDoi": null,
  "recentWorks": [
    "20  K. Roy, Sarker G. (2013),A Location Invariant Face Identification and Localization with Modified RBF Network , International Conference on Computer and Systems ICCS-2013 [conference-paper]",
    "A New Method of Galaxy Classification Using Optimal Convolution Neural Network - International Symposium on Artificial Intelligence (ISAI-2022) Feb. 2022. [conference-paper]"
  ],
  "recentWorkDois": [],
  "searchTerm": "machine learning",
  "source": "ORCID public researcher registry",
  "observedAt": "2026-08-14T06:26:54.285Z",
  "aiSummary": "Dr. Goutam Sarker is an expert in Machine Learning and Artificial Intelligence, with extensive experience in teaching and research. His work encompasses areas such as machine translation, speech recognition, pattern recognition, and data mining, alongside interests in astronomy and black hole research.",
  "aiKeywords": ["Machine Learning", "Artificial Intelligence", "Data Mining", "Pattern Recognition", "Computer Vision", "Deep Learning", "Biometric Authentication", "Speech to Text", "Astronomy", "Astrophysics"],
  "aiField": "Machine Learning"
}

The most complete ORCID researcher scraper available. It returns every field the public ORCID registry exposes for each researcher, including full name and other names, biography, country, stated keywords, websites, LinkedIn, public email, external identifiers (Scopus, ResearcherID, ISNI), current affiliation and education, full affiliation history, works count and recent works with DOIs, and gives you name, institution, keyword and country filters plus optional AI add-ons (biography summary, inferred keywords, field classification).

📥 Input · 📤 Output · 💰 Pricing · ▶️ Examples

Table of contents

• What it does
• Quickstart
• Input reference
• Output reference
• Example output record
• Run via API and CLI
• Fetch results
• Billing and limits
• FAQ and troubleshooting

What it does

The actor searches the public ORCID registry for each of your queries (or looks up exact ORCID iDs), applies the name, institution, keyword and country filters you pass, optionally attaches each researcher's recent works, and writes one normalized record per researcher to the run's dataset. Each record captures the researcher's identity, biography, stated keywords, websites and public email, external author identifiers, current and past affiliations, and works. Missing source values are returned as null.

Optional AI add-ons (paid plans only) can generate a short biography summary, infer research keywords, and classify the researcher's primary field. Each add-on is billed per researcher only when it produces usable output.

Quickstart

Open the actor, paste this into the input, and press Run. It returns up to 50 researchers matching "machine learning", with recent works attached.

{
  "searchQueries": ["machine learning"],
  "maxResearchers": 50,
  "includeWorks": true
}

Look up exact researchers by ORCID iD instead:

{
  "orcidIds": ["0000-0001-5109-3700"]
}

Every input field is optional. Turn on the AI add-ons only on a paid plan.

Input reference

Field	Type	Required	Default	Description
searchQueries	string[]	no	["machine learning"]	One or more free-text searches by researcher name, institution or topic. Every term is searched in one run.
orcidIds	string[]	no	(empty)	One or more exact ORCID iDs to look up directly, for example 0000-0001-5109-3700.
familyName	string	no	(empty)	Filter by researcher family (last) name.
givenNames	string	no	(empty)	Filter by researcher given (first) names.
affiliationOrg	string	no	(empty)	Filter by affiliation organization name, for example Stanford University.
keyword	string	no	(empty)	Filter by a research keyword listed on the profile.
country	string	no	(empty)	Keep only researchers whose profile country matches this 2-letter ISO code, for example US, GB, DE.
includeWorks	boolean	no	true	Include each researcher's recent works (title, type, year, DOI).
maxResearchers	integer	no	50	Maximum researcher profiles to return across all searches.
withAiSummary	boolean	no	false	Paid add-on. Generate a 1-2 sentence summary from the biography. Billed only when a summary is produced.
withAiKeywords	boolean	no	false	Paid add-on. Infer 5-10 research-topic keywords per researcher. Billed only when keywords are produced.
withAiField	boolean	no	false	Paid add-on. Classify each researcher's primary field/discipline. Billed only when a classification is produced.

Output reference

One dataset item per researcher. Types: string, integer, boolean, string[], or null when the source value is absent.

Field	Type	Description
orcidId	string	ORCID iD (unique researcher identifier).
orcidUri	string	Full ORCID profile URL.
givenNames	string	Given (first) names.
familyName	string	Family (last) name.
creditName	string	Published / credit name, or null.
fullName	string	Best full display name.
otherNames	string[]	Alternate names listed on the profile.
biography	string	Profile biography text, or null.
country	string	Profile country (ISO code), or null.
keywords	string[]	Research keywords stated on the profile.
websites	string[]	Website URLs listed on the profile.
websiteNames	string[]	Labels for the website links.
linkedinUrl	string	LinkedIn URL if present, or null.
publicEmail	string	Public email if the researcher published one, or null.
externalIds	string[]	External identifiers as type: value strings.
scopusAuthorId	string	Scopus Author ID, or null.
researcherId	string	Web of Science ResearcherID, or null.
isni	string	ISNI identifier, or null.
currentAffiliationOrg	string	Current employer / affiliation organization.
currentAffiliationRole	string	Current role / title.
currentAffiliationCity	string	Current affiliation city.
currentAffiliationCountry	string	Current affiliation country.
currentAffiliationRorId	string	ROR ID of the current organization, or null.
topEducationOrg	string	Most relevant education organization.
topEducationRole	string	Degree / education role.
employmentsCount	integer	Number of employment entries.
educationsCount	integer	Number of education entries.
affiliations	string[]	Full employment and education history as readable strings.
worksCount	integer	Number of works on the profile.
topWorkTitle	string	Title of the most recent / top work, or null.
topWorkYear	string	Year of the top work, or null.
topWorkDoi	string	DOI of the top work, or null.
recentWorks	string[]	Recent works as readable strings (title, year, type, DOI).
recentWorkDois	string[]	DOIs of the recent works.
searchTerm	string	The query that surfaced this researcher, or null.
source	string	Always ORCID public researcher registry.
observedAt	string	ISO 8601 timestamp of when the record was collected.
aiSummary	string	AI biography summary (paid add-on), else null.
aiKeywords	string[]	AI-inferred research keywords (paid add-on), else null.
aiField	string	AI-classified primary field (paid add-on), else null.

Example output record

See the hero record at the top of this page. It is a real researcher (ORCID 0000-0002-9510-6777) pulled from a live run with all three AI add-ons enabled (input {"searchQueries":["machine learning"],"withAiSummary":true,"withAiKeywords":true,"withAiField":true,"includeWorks":true}), with the biography and works trimmed and source em dashes rendered as hyphens; every value shown is otherwise real.

Run via API and CLI

Start a run and wait for it to finish, then read the dataset. Replace <TOKEN> with your Apify API token.

Run synchronously and get dataset items in one call:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~orcid-researchers-scraper/run-sync-get-dataset-items?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"searchQueries":["quantum computing"],"affiliationOrg":"Stanford University","maxResearchers":25}'

Look up specific ORCID iDs:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~orcid-researchers-scraper/runs?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"orcidIds":["0000-0001-5109-3700"],"includeWorks":true}'

Apify CLI:

apify call scrapers_lat/orcid-researchers-scraper \
  --input '{"searchQueries":["machine learning"],"maxResearchers":50}'

Fetch results

Every run writes to a dataset. Fetch items as JSON, CSV, or Excel by changing format:

# JSON
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=json"

# CSV
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=csv"

# Paginate large datasets
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&offset=1000&limit=1000"

<DATASET_ID> is returned as defaultDatasetId in the run object. Use offset and limit to page through large result sets. clean=true drops empty and internal fields.

Billing and limits

• Pay per result. You are charged per researcher returned (result event). See the pricing tab for the current per-result price.
• AI add-ons are billed separately and only when they produce usable output, on paid plans only.
• No charge on failure. If a run errors, the actor writes a single item with a populated error field and does not charge for it. Empty runs cost nothing.
• Spend cap respected. Set maxTotalChargeUsd on the run; once reached, the actor stops emitting and charging further billable results.
• Free Apify plans are capped at 10 researchers per run, and cannot use the AI add-ons. Upgrade for higher maxResearchers and AI enrichment.

FAQ and troubleshooting

A run returned 0 records. Why? The query matched no public ORCID profiles, or the filters excluded everyone. Loosen the name / institution / keyword / country filters, or check the ORCID iD. Zero-result runs are not charged.

Do I get email addresses? Only when a researcher has published a public email on their ORCID profile. It is returned in publicEmail, otherwise null. Emails are never invented.

What do the AI add-ons cost? Each add-on is billed per researcher only when it returns output, and only on paid Apify plans. On the free plan the AI fields stay null.

How do I look up one exact person? Pass their ORCID iD in orcidIds. This is exact and precise.

Is this an official ORCID tool? No. This actor is independent and has no affiliation with ORCID. It reads only data that researchers have made public in the ORCID registry. Use it in accordance with ORCID's terms.

Related scrapers

• Crossref Scraper: scholarly works and DOIs.
• arXiv Papers Scraper: arXiv preprints and metadata.
• Open Library Books Scraper: book records from Open Library.
• GitHub Contributor Contacts Scraper: developer contact leads from GitHub.
• ClinicalTrials.gov Scraper: registered clinical trials worldwide.

More scrapers at scrapers.lat

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Independent tool, not affiliated with ORCID. Accesses only data that researchers have made public in the ORCID registry.