Process / pipelineLibrary Information ScienceLibrary & information science / authority controlPipeline

Name Authority Control Evaluation

Also known as: Authority Control Assessment, Name Authority File Evaluation, Identity Disambiguation Evaluation, Authority Data Quality Evaluation

OriginatorIFLA FRANAR (FRAD model); Elaine SvenoniusYear2009Sources2Related methods5

Name authority control evaluation is the systematic assessment of how well a name authority file fulfils its core task: gathering everything by or about a given person, family, or corporate body under one controlled access point, while keeping distinct identities apart. The IFLA Functional Requirements for Authority Data (FRAD) model supplies the conceptual yardstick, defining the entities authority data describes and the user tasks — find, identify, contextualize, and justify — that authority control must support. Elaine Svenonius's analysis of the cataloguing objectives explains why collocation and disambiguation are the heart of the matter. Evaluation samples access points, measures collocation (are all of an identity's works gathered?) and disambiguation (are unlike identities kept separate?), and audits the quality of the authority records themselves against FRAD's requirements.

Key highlights

  • Grounds assessment in the FRAD user tasks, so quality is defined by support for finding, identifying, and contextualizing entities.
  • Separates the two failure modes — scattering one identity (low collocation) and merging several (low disambiguation) — and measures each.
  • Maps naturally onto recall and precision, giving familiar, interpretable metrics for identity management.
  • Audits record-level richness (variant forms, sources, relationships), distinguishing genuine identity management from mere heading assignment.

Intuition

This section is available to Pro members. Upgrade to Pro

How it works

This section is available to Pro members. Upgrade to Pro

When to use it

Use name authority control evaluation when the trustworthiness of identities in a catalogue, repository, or research-information system matters and you need evidence of how well names are being collocated and disambiguated. It is appropriate when auditing a legacy authority file, when migrating or merging catalogues, when integrating with identifier systems such as ISNI, ORCID, or VIAF, and when assessing the quality of automatically generated or crowd-sourced authority data. The approach presupposes that you can establish ground-truth identities for a sample, which requires accessible external evidence. It is less applicable where names are not used as primary access points, or for collections so small that informal inspection suffices. It is most valuable in scholarly, archival, and bibliographic settings where disambiguating creators is central to discovery and to crediting work correctly.

Strengths & limitations

Strengths
  • Grounds assessment in the FRAD user tasks, so quality is defined by support for finding, identifying, and contextualizing entities.
  • Separates the two failure modes — scattering one identity (low collocation) and merging several (low disambiguation) — and measures each.
  • Maps naturally onto recall and precision, giving familiar, interpretable metrics for identity management.
  • Audits record-level richness (variant forms, sources, relationships), distinguishing genuine identity management from mere heading assignment.
Limitations
  • Requires reliable ground-truth identities, which can be hard or impossible to establish for obscure or historical names.
  • Sampling and identity adjudication are labour-intensive and depend on the evaluator's access to external evidence.
  • Collocation and disambiguation can trade off, and weighting them requires judgement tied to the collection's purpose.
  • Results describe the file at evaluation time but say little about ongoing maintenance unless repeated.

Common pitfalls

This section is available to Pro members. Upgrade to Pro

Applications

This section is available to Pro members. Upgrade to Pro

Frequently asked

What is the difference between collocation and disambiguation in authority control?

Collocation is the gathering of all of a single identity's works under one controlled access point; it fails when a person or body is split across several variant forms, so a searcher finds only part of their output. Disambiguation is the separation of distinct identities that share a name; it fails when different people are conflated under one heading, so a search retrieves a mixture. They are the recall and precision sides of authority control respectively, and a good evaluation measures both, because an authority file can be strong on one and weak on the other.

How does the FRAD model inform authority control evaluation?

FRAD (Functional Requirements for Authority Data) provides the conceptual yardstick. It defines the entities authority data describes — persons, families, corporate bodies, names, identifiers — and the user tasks authority control must support: find, identify, contextualize, and justify. Evaluation uses these as criteria: it asks whether the authority data lets users find and unambiguously identify an entity, place it among related entities, and see the justification for the chosen access point. This turns 'is the authority file good?' into measurable questions tied to the tasks the file exists to serve.

Why involve external identifiers like ISNI, ORCID, or VIAF in the evaluation?

External identifier systems provide independent, persistent anchors for real-world identities, which helps both in establishing ground truth and in assessing interoperability. Comparing a file's headings against VIAF clusters or matching creators to ORCID and ISNI records can reveal splits and conflations and shows how well the catalogue connects to the wider identity ecosystem. But the linkage must be verified rather than trusted blindly: an evaluation should confirm that the identifier actually denotes the intended entity, since incorrect identifier matches can introduce the very conflation errors authority control is meant to prevent.

Sources

  1. 1.
    IFLA Working Group on Functional Requirements and Numbering of Authority Records (FRANAR). (2009). Functional Requirements for Authority Data: A Conceptual Model. The Hague: IFLA (rev. 2013).
  2. 2.
    Svenonius, E. (2000). The Intellectual Foundation of Information Organization. Cambridge, MA: MIT Press.
    ISBN 9780262194334

You have read it. What now?

Cite this page

ScholarGate. (2026, June 23). Name Authority Control Evaluation. ScholarGate. https://scholargate.app/library-information-science/name-authority-control-evaluation