Võrdle meetodeid

	Bibliographic Record Quality Analysis	Controlled Vocabulary Indexing
Valdkond	Library Information Science	Library Information Science
Perekond	Process / pipeline	Process / pipeline
Tekkeaasta	2018	2005
Looja	Philip Hider; Elaine Svenonius	ANSI/NISO Z39.19; Elaine Svenonius
Tüüp	Evaluation pipeline for bibliographic record quality	Indexing pipeline using a controlled vocabulary
Algallikas	Hider, P. (2018). Information Resource Description: Creating and Managing Metadata (2nd ed.). London: Facet Publishing. ISBN: 9781783302239	NISO. (2005). ANSI/NISO Z39.19-2005 (R2010): Guidelines for the Construction, Format, and Management of Monolingual Controlled Vocabularies. Baltimore: NISO.
Rööpnimetused	Catalogue Record Quality Analysis, MARC Record Quality Assessment, Bibliographic Data Quality Evaluation, Cataloguing Quality Analysis	Subject Indexing, Controlled Indexing, Assigned Indexing, Vocabulary-Controlled Subject Indexing
Seotud	3	3
Kokkuvõte	Bibliographic record quality analysis evaluates the catalogue records that describe library resources — typically MARC or linked-data records built to standards such as RDA — to determine how well they serve their purpose. Philip Hider's account of information resource description frames quality in terms of accuracy, completeness, consistency, and conformance to cataloguing rules, while Elaine Svenonius's objectives of the catalogue — to find, identify, select, and obtain resources — supply the functional yardstick against which records are ultimately judged. The analysis samples records, scores them on each quality criterion, checks their encoding and content against the relevant standard, and asks whether they actually let users carry out the catalogue's core tasks. The result is evidence about where cataloguing is strong, where it fails, and what remediation or policy change is needed.	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.