agentsclimarketplace

Viaf authority api

Skill brycewang-stanford/Auto-Empirical-Research-Skills/skills/43-wentorai-research-plugins/skills/literature/metadata/viaf-authority-api

Disambiguate author identities via the VIAF authority file APIFrom its SKILL.md

Install
npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill viaf-authority-api

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.

SKILL.md

5.7 KB, ~1.5k tokens by cl100k_base, as published. Nobody here has run it

VIAF (Virtual International Authority File) API

Overview

VIAF clusters authority records from 50+ national libraries worldwide, linking different forms of an author's name into a single canonical identity. It covers 50M+ personal, corporate, and geographic name entries. Essential for author disambiguation in bibliometric research — resolving "J. Smith", "John Smith", and "Smith, J.A." to the same person. Free, no authentication.

API Endpoints

Base URL

https://viaf.org

Search

# Search by name (AutoSuggest)
curl "https://viaf.org/viaf/AutoSuggest?query=einstein+albert"

# Search via SRU (structured query)
curl "https://viaf.org/viaf/search?query=local.personalNames+all+\"hinton+geoffrey\"&\
sortKeys=holdingscount&httpAccept=application/json"

# Search corporate names
curl "https://viaf.org/viaf/search?query=local.corporateNames+all+\"MIT\"&\
httpAccept=application/json"

Get Record by VIAF ID

# JSON format
curl "https://viaf.org/viaf/75121530/viaf.json"

# Linked data formats
curl -H "Accept: application/json" "https://viaf.org/viaf/75121530"

# Cluster data (all linked identities)
curl "https://viaf.org/viaf/75121530/justlinks.json"

Cross-Reference by External ID

# Look up by Library of Congress ID
curl "https://viaf.org/viaf/lccn/n79021164/viaf.json"

# Look up by ISNI
curl "https://viaf.org/viaf/isni/0000000121174331/viaf.json"

# Look up by ORCID
curl "https://viaf.org/viaf/sourceID/ORCID|0000-0002-1825-0097/viaf.json"

# Look up by Wikidata QID
curl "https://viaf.org/viaf/sourceID/WKP|Q937/viaf.json"

Source Codes

CodeLibrary/Source
LCLibrary of Congress
DNBGerman National Library
BNFBibliothèque nationale de France
NLANational Library of Australia
NDLNational Diet Library (Japan)
NKCNational Library of Czech Republic
WKPWikidata
ISNIISNI

Response Structure

{
  "viafID": "75121530",
  "nameType": "Personal",
  "mainHeadings": {
    "data": [
      {
        "text": "Einstein, Albert, 1879-1955",
        "sources": {"s": ["LC", "DNB", "BNF"]}
      }
    ]
  },
  "x400s": {
    "x400": [
      {"datafield": {"subfield": [{"text": "Albert Einstein"}]}}
    ]
  },
  "birthDate": "1879",
  "deathDate": "1955",
  "sources": {
    "source": [
      {"nsid": "n79022889", "sid": "LC|n79022889"},
      {"nsid": "118529579", "sid": "DNB|118529579"}
    ]
  }
}

Python Usage

import requests

BASE_URL = "https://viaf.org/viaf"


def search_person(name: str, limit: int = 10) -> list:
    """Search VIAF for personal name authorities."""
    resp = requests.get(
        f"{BASE_URL}/AutoSuggest",
        params={"query": name},
    )
    resp.raise_for_status()
    data = resp.json()

    results = []
    for item in data.get("result", [])[:limit]:
        results.append({
            "viaf_id": item.get("viafid"),
            "name": item.get("displayForm"),
            "name_type": item.get("nametype"),
            "source_count": len(item.get("sources", "").split("|")),
        })
    return results


def get_authority(viaf_id: str) -> dict:
    """Get full VIAF authority record."""
    resp = requests.get(f"{BASE_URL}/{viaf_id}/viaf.json")
    resp.raise_for_status()
    data = resp.json()

    name_forms = []
    for heading in data.get("mainHeadings", {}).get("data", []):
        if isinstance(heading, dict):
            name_forms.append({
                "text": heading.get("text"),
                "sources": heading.get("sources", {}).get("s", []),
            })

    external_ids = {}
    for src in data.get("sources", {}).get("source", []):
        sid = src.get("sid", "")
        if "|" in sid:
            prefix, local_id = sid.split("|", 1)
            external_ids[prefix] = local_id

    return {
        "viaf_id": data.get("viafID"),
        "name_forms": name_forms,
        "birth": data.get("birthDate"),
        "death": data.get("deathDate"),
        "external_ids": external_ids,
    }


def resolve_by_orcid(orcid: str) -> dict:
    """Resolve ORCID to VIAF authority record."""
    resp = requests.get(
        f"{BASE_URL}/sourceID/ORCID|{orcid}/viaf.json"
    )
    resp.raise_for_status()
    return resp.json()


# Example: disambiguate an author name
candidates = search_person("Geoffrey Hinton")
for c in candidates:
    print(f"VIAF {c['viaf_id']}: {c['name']} "
          f"({c['source_count']} libraries)")

# Example: get all name forms for an author
if candidates:
    record = get_authority(candidates[0]["viaf_id"])
    print(f"\nName forms for {record['viaf_id']}:")
    for form in record["name_forms"]:
        sources = ", ".join(form["sources"][:3])
        print(f"  {form['text']} [{sources}]")
    print(f"External IDs: {record['external_ids']}")

Use Cases

  1. Author disambiguation: Resolve name variants to canonical identities
  2. Cross-library linking: Connect records across national catalogs
  3. Bibliometric deduplication: Merge author records from different databases
  4. Identity verification: Confirm author identity via multiple authority sources
  5. Linked data enrichment: Bridge ORCID, Wikidata, and library authorities

References

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,144. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.