Critical Views of LCSH, 1990–2001: The Third Bibliographic Essay

Fischer, Karen S.

doi:10.1300/j104v41n01_05

Cited by 18 publications

(5 citation statements)

References 4 publications

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“…O'Neill and Aluri () reported 1.41 LCSH strings per record in their sample of 33,455 monographic records from the OCLC database, and McClure () reported a mean of 1.3 LCSH strings per record in a sampling of 500 entries from the National Union Catalogue. The increase in the mean number of LCSH strings per bibliographic record is partly explained by a policy change at LC for increasing the number of LCSH strings indexers can assign (Fischer, ).…”

Section: Methodsmentioning

confidence: 99%

Constructing a true LCSH tree of a science and engineering collection

Julien

Tirilly

Leide

et al. 2012

J Am Soc Inf Sci Tec

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The Library of Congress Subject Headings (LCSH) is a subject structure used to index large library collections throughout the world. Browsing a collection through LCSH is difficult using current online tools in part because users cannot explore the structure using their existing experience navigating file hierarchies on their hard drives. This is due to inconsistencies in the LCSH structure, which does not adhere to the specific rules defining tree structures. This article proposes a method to adapt the LCSH structure to reflect a real‐world collection from the domain of science and engineering. This structure is transformed into a valid tree structure using an automatic process. The analysis of the resulting LCSH tree shows a large and complex structure. The analysis of the distribution of information within the LCSH tree reveals a power law distribution where the vast majority of subjects contain few information items and a few subjects contain the vast majority of the collection.

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Section: Methodsmentioning

confidence: 99%

Constructing a true LCSH tree of a science and engineering collection

Julien

Tirilly

Leide

et al. 2012

J Am Soc Inf Sci Tec

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“…But LIS should also be about how to improve systems, and for this purpose theoretical, empirical and critical studies are important. Three articles collectively review the critiques of LCSH published between 1944 and 2001: those by Cochrane and Kirtland (1981), Kirtland and Cochrane (1982), Shubert (1992) and Fischer (2005). No subsequent article has brought this literature review fully up to date.…”

Section: Lcsh: History and Criticismmentioning

confidence: 99%

The coverage of information science and knowledge organization in theLibrary of Congress Subject Headings

Furner

Hjørland

2023

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PurposeThis article examines the Library of Congress Subject Headings (LCSH), which is the most used subject heading system in the world and an instance of a controlled vocabulary (CV).Design/methodology/approachThe method used to examine the system is based on both authors’ subject knowledge in the field of information science (IS) and the subfield of knowledge organization (KO). Core concepts in this domain were examined (1) by checking if they are present or not in the system; (2) if not, by determining whether LCSH contains alternative terms useful for searching documents about the missing concept, by examining books indexed by the Library of Congress; (3) by identifying the semantic relations between subject headings.FindingsThe results demonstrate fundamental problems in the logical consistency of the representation of IS and KO in LCSH.Practical implicationsThe implications for CVs in general are discussed.Originality/valueNo previous study has used our method to examine LCSH’s coverage of IS.

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“…comparison of machine‐generated classification structures and well‐established classification schemes and thesauri [14, 15, 16, 17, 18];…”

Section: Evaluating Classification Decisionsmentioning

confidence: 99%

“…The citations in this article are illustrative and not comprehensive. The research tends to focus on several contexts for evaluation, including comparison of human and machine classification practices [5, 6, 7, 8, 9, 10]; assessment of the variability of classification decisions among human and machine classifiers [11, 12, 13]; comparison of machine‐generated classification structures and well‐established classification schemes and thesauri [14, 15, 16, 17, 18]; the quality of classification in the context of information retrieval [19, 20, 21]; and evaluations of the quality of statistically generated classes [22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]. …”

Section: Evaluating Classification Decisionsmentioning

confidence: 99%

Evaluating classification schema and classification decisions

Bedford

2012

Bul. Am. Soc. Info. Sci. Tech.

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Stacy Surla is the Bulletin's associate editor for IA. She serves on the IA Institute Board of Directors and is a past chair of the IA Summit. She can be reached at T his article considers how evaluation pertains to taxonomies. Taxonomies and evaluation are both rich concepts, so it is best to start out with some definitions that help to define our discussion. What do we mean by taxonomy? And what do we mean by evaluation? TaxonomiesFor seasoned information professionals the traditional characterization of a taxonomy is as a hierarchical classification scheme. This characterization has expanded in the last 20 years as the taxonomy community and the information environment have expanded. Today the taxonomy community includes people who design taxonomies, those who build systems that support them and those who use them. Our complex information environment may call for a variety of taxonomic structures, including I flat taxonomies such as lists of languages or lists of countries; I hierarchical taxonomies such as topical or subject classifications, business classifications or service classifications; I faceted taxonomies such as metadata or parametric search structures; I ring taxonomies such as synonyms or authority control data; and I network taxonomies such as fully relationed thesauri or knowledge networks. Each of these structures has its own set of principles and behaviors. And each requires an evaluation method that aligns with those principles and behaviors. This article focuses on the second type of taxonomy -the traditional classification scheme or hierarchical taxonomy. Classification schemes govern the organization of objects into groups according to explicit properties or values. Classification schemes are in widespread use in everyday life -from grocery stores to websites to personal information spaces. C O N T E N T S N E X T P A G E > N E X T A R T I C L E > < P R E V I O U S P A G E Special SectionEDITOR'S SUMMARY Direction on the construction and application of classification schemes such as taxonomies is readily available, but relatively little has been offered on evaluating the schemes themselves and their use to categorize content. A classification scheme can be judged for how well it meets its purpose and complies with standards, and a strong evaluative framework is reflected in S.R. Ranganathan's principles of classification. The degree of certainty of classification decisions depends on objective understanding of the object to be classified, the scope and details of the class and the coverage and organization of the overall classification scheme. The more complete the information about each class, the more reliable the goodness-of-fit for an object to a class is likely to be, whether chosen by human or machine classifiers. This information comes through definitions, examples, prior use and semantic relationships. The risk of misclassification can be reduced by analyzing the goodness-of-fit of objects to classes and the patterns of missed or erroneous selections. KEYWORDS

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Critical Views of LCSH, 1990–2001: The Third Bibliographic Essay

Cited by 18 publications

References 4 publications

Constructing a true LCSH tree of a science and engineering collection

Constructing a true LCSH tree of a science and engineering collection

The coverage of information science and knowledge organization in theLibrary of Congress Subject Headings

Evaluating classification schema and classification decisions

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