Uporedite metode

	Name Authority Control Evaluation	Controlled Vocabulary Indexing
Oblast	Library Information Science	Library Information Science
Porodica	Process / pipeline	Process / pipeline
Godina nastanka	2009	2005
Tvorac	IFLA FRANAR (FRAD model); Elaine Svenonius	ANSI/NISO Z39.19; Elaine Svenonius
Tip	Evaluation pipeline for name authority control quality	Indexing pipeline using a controlled vocabulary
Temeljni izvor	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).	NISO. (2005). ANSI/NISO Z39.19-2005 (R2010): Guidelines for the Construction, Format, and Management of Monolingual Controlled Vocabularies. Baltimore: NISO.
Drugi nazivi	Authority Control Assessment, Name Authority File Evaluation, Identity Disambiguation Evaluation, Authority Data Quality Evaluation	Subject Indexing, Controlled Indexing, Assigned Indexing, Vocabulary-Controlled Subject Indexing
Srodne	3	3
Sažetak	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.	Controlled vocabulary indexing is the process of representing what a document is about by assigning preferred terms drawn from an established controlled vocabulary or thesaurus, rather than from the document's own free-text words. ANSI/NISO Z39.19 codifies the practice: the indexer first performs conceptual analysis to determine a document's aboutness, then translates each concept into the vocabulary's preferred term, choosing how many concepts to capture (exhaustivity) and how finely to express each (specificity). Elaine Svenonius's account of subject languages explains why this controlled translation matters — it eliminates the synonymy and homonymy of natural language so that one concept is always indexed under one term. Done consistently, controlled vocabulary indexing gives a collection reliable, predictable subject access that free-text search alone cannot guarantee.