Comparar métodos

	Name Authority Control Evaluation	Metadata Quality Assessment
Área	Library Information Science	Library Information Science
Família	Process / pipeline	Process / pipeline
Ano de origem	2009	2004
Autor original	IFLA FRANAR (FRAD model); Elaine Svenonius	Thomas Bruce & Diane Hillmann; Jung-ran Park & Yuji Tosaka
Tipo	Evaluation pipeline for name authority control quality	Measurement pipeline for metadata quality
Fonte seminal	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).	Bruce, T. R., & Hillmann, D. I. (2004). The Continuum of Metadata Quality: Defining, Expressing, Exploiting. In D. I. Hillmann & E. L. Westbrooks (Eds.), Metadata in Practice (pp. 238-256). Chicago: ALA.
Outros nomes	Authority Control Assessment, Name Authority File Evaluation, Identity Disambiguation Evaluation, Authority Data Quality Evaluation	Metadata Quality Evaluation, Metadata Quality Measurement, Metadata Assessment, Digital Repository Metadata Evaluation
Relacionados	3	3
Resumo	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.	Metadata quality assessment is the systematic measurement of how good a collection's descriptive metadata is for its intended purposes. Thomas Bruce and Diane Hillmann's influential framework defined quality along a continuum of dimensions — completeness, accuracy, conformance to expectations, logical consistency and coherence, timeliness, accessibility, and provenance — and argued that quality must be defined relative to use, then expressed and exploited. Jung-ran Park and Yuji Tosaka surveyed how digital repositories operationalize the three most widely accepted criteria — accuracy, completeness, and consistency — into concrete control mechanisms. Assessment turns these dimensions into measurable indicators, scores records and collections against them, and produces diagnostics that pinpoint where metadata falls short, so that interoperability, discovery, and trust can be improved.