Comparer des méthodes

	Citation Analysis for Collection Development	Collection Overlap Analysis
Domaine	Library Information Science	Library Information Science
Famille	Process / pipeline	Process / pipeline
Année d'origine	2005	1998
Auteur d'origine	Library collection-development literature; Jennifer E. Knievel & Charlene Kellsey (comparative humanities study)	Library collection-management literature; Thomas E. Nisonger (synthesis)
Type	Bibliometric pipeline applying local citation patterns to collection-building decisions	Set-comparison pipeline for measuring duplication and uniqueness across collections
Source fondatrice	Knievel, J. E., & Kellsey, C. (2005). Citation Analysis for Collection Development: A Comparative Study of Eight Humanities Fields. The Library Quarterly, 75(2), 142-168.	Nisonger, T. E. (1998). Management of Serials in Libraries. Englewood, CO: Libraries Unlimited. ISBN: 9781563084782
Alias	Local Citation Analysis, Citation-Based Collection Evaluation, Reference Citation Study, Citation Analysis for Acquisitions	Collection Overlap Study, Holdings Overlap Analysis, Title Duplication Analysis, Collection Comparison Analysis
Apparentées	3	2
Résumé	Citation analysis for collection development studies what a library's own community actually cites, in their theses, dissertations, and publications, and uses those patterns to guide what the library should buy, keep, and cancel. Rather than mapping the global structure of a field, it asks a local, practical question: which formats, languages, ages, and specific titles do our researchers rely on? By tabulating the references in locally produced scholarship, the method reveals, for example, whether a discipline depends on monographs or journals, how quickly its literature ages, and which journals or books appear most often, evidence that can be matched against holdings to find gaps and guide budgets. Knievel and Kellsey's comparative study of eight humanities fields showed how sharply these citation patterns vary by discipline, underscoring why collection decisions should rest on field-specific local evidence.	Collection overlap analysis measures the degree to which two or more library collections hold the same titles, quantifying how much of each collection is shared, how much is unique, and how much in total the collections cover together. By treating holdings as sets and computing intersection, union, and overlap coefficients on matched identifiers such as ISBN, ISSN, or OCLC number, the method turns a vague sense of duplication into reproducible figures. These figures drive concrete decisions: where consortial partners can rely on one another, which titles are uniquely held and so must be preserved, and where duplicate purchasing or storage can be reduced. The technique is a workhorse of cooperative collection development and shared-print retention, summarized across the serials and collection-management literature including Nisonger's syntheses.