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Journal articles on the topic 'Dewey Classification'

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Published: 4 June 2021
Last updated: 16 February 2022

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1

Comaromi, John P., and Mohinder Partap Satija. "Revising the Dewey Decimal Classification." KNOWLEDGE ORGANIZATION 15, no. 1 (1988): 17–20. http://dx.doi.org/10.5771/0943-7444-1988-1-17.

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2

Fountain, Joanna F. "Dewey Decimal Classification, 21st edition." Library Collections, Acquisitions, and Technical Services 25, no. 2 (June 2001): 236. http://dx.doi.org/10.1016/s1464-9055(00)00199-8.

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Fountain, Joanna F. "Dewey Decimal Classification, 21st edition." Library Collections, Acquisitions, & Technical Services 25, no. 2 (June 2001): 236. http://dx.doi.org/10.1080/14649055.2001.10765769.

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4

Taglienti, Paolina. "Dewey Decimal Classification, 22nd Edition." Library Collections, Acquisitions, & Technical Services 30, no. 3-4 (September 2006): 251. http://dx.doi.org/10.1080/14649055.2006.10766133.

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5

Kuhn, Tamara J. "Classifying Newspapers Using Dewey Decimal Classification." Library Resources & Technical Services 43, no. 2 (April 1, 1999): 106–13. http://dx.doi.org/10.5860/lrts.43n2.106.

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6

Yi, Hong, and Zhang Jin. "The Dewey Decimal Classification in China." KNOWLEDGE ORGANIZATION 23, no. 4 (1996): 213–15. http://dx.doi.org/10.5771/0943-7444-1996-4-213.

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7

Wursten, Richard B., Melvil Dewey, John P. Comaromi, Julianne Beall, Winton E. Matthews, Gregory R. New, Russell Sweeney, and John Clews. "Dewey Decimal Classification and Relative Index." Notes 48, no. 1 (September 1991): 143. http://dx.doi.org/10.2307/941824.

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8

Fountain, Joanna F. "Learn Dewey Decimal Classification (edition 21)." Library Collections, Acquisitions, and Technical Services 25, no. 2 (June 2001): 240–41. http://dx.doi.org/10.1016/s1464-9055(00)00206-2.

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9

Taylor, Arlene G. "Teaching the Dewey Decimal Classification System." Cataloging & Classification Quarterly 42, no. 3-4 (August 2006): 97–117. http://dx.doi.org/10.1300/j104v42n03_03.

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Fountain, Joanna F. "Learn Dewey Decimal Classification (edition 21)." Library Collections, Acquisitions, & Technical Services 25, no. 2 (June 2001): 240–41. http://dx.doi.org/10.1080/14649055.2001.10765774.

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11

Brattli, Tore. "Why Build Dewey Numbers? The Remediation of the Dewey Decimal Classification System." Nordlit 16, no. 2 (October 23, 2012): 189. http://dx.doi.org/10.7557/13.2383.

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Correct Dewey classification is demanding and time consuming. Many of the challenges with the Dewey system are related to locating and interpreting notes (i.e. classification guidelines), and number building.Today’s Dewey structure is a result of more than 100 years of optimizing a comprehensive classification system to the printed book medium. In order to limit the system into a “manageable” size, facets and facet-like subjects are represented only once and instead referred to from relevant classes for number building. A similar technique is used to reduce the number of notes.With the remediation of Dewey from printed to computer media, space is not limited and there is no need to compress the classification system. Number building can be eliminated, and all relevant notes attached to each class. Despite the fact that the system now has been available in electronic form for almost 20 years, it is still largely a copy of the printed version.This article first investigates how the Dewey system may be presented for users without number building, in order to make it more immediate and user-friendly. We first analyze the Dewey structure, and then look at different representations of the structure suited for computer media. Finally, some ideas for a new presentation without number building are proposed.
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Pacey, Philip. "The Classification of Literature in the Dewey Decimal Classification." Cataloging & Classification Quarterly 9, no. 4 (May 16, 1989): 101–7. http://dx.doi.org/10.1300/j104v09n04_08.

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13

McAllister-Harper, Desretta. "Dewey Decimal Classification in the Online' Environment:." Cataloging & Classification Quarterly 11, no. 1 (June 7, 1990): 45–58. http://dx.doi.org/10.1300/j104v11n01_05.

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14

Mitchell, Joan S. "Options in the Dewey Decimal Classification System:." Cataloging & Classification Quarterly 19, no. 3-4 (July 6, 1995): 89–103. http://dx.doi.org/10.1300/j104v19n03_08.

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15

Lessard, Sophie. "Pour la documentation en entomologie : LCC ou DDC ?" Documentation et bibliothèques 39, no. 1 (February 13, 2015): 7–10. http://dx.doi.org/10.7202/1028595ar.

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Les insectes, largement étudiés dans la documentation, occupent une place importante au sein des systèmes de classification de Dewey et de la Library of Congress. Bien que la classification de la Library of Congress (LCC) soit davantage développée en ce qui a trait à la taxinomie entomologique, l’arrangement de la classification Dewey (DDC) s’avère plus logique et plus conforme à la classification évolutive. DDC permet également un plus grand nombre de possibilités en ce qui concerne la distribution géographique des insectes et les différents aspects sous lesquels ils sont abordés.
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16

Jenkins, Charlotte, Mike Jackson, Peter Burden, and Jon Wallis. "Automatic classification of Web resources using Java and Dewey Decimal Classification." Computer Networks and ISDN Systems 30, no. 1-7 (April 1998): 646–48. http://dx.doi.org/10.1016/s0169-7552(98)00035-x.

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17

Green, Rebecca. "See-also relationships in the Dewey Decimal Classification." NASKO 3, no. 1 (November 2, 2011): 41. http://dx.doi.org/10.7152/nasko.v3i1.12789.

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This paper investigates the semantics of topical, associative see-also relationships in schedule and table entries of the Dewey Decimal Classification (DDC) system. Based on the see-also relationships in a random sample of 100 classes containing one or more of these relationships, a semi-structured inventory of sources of see-also relationships is generated, of which the most important are lexical similarity, complementarity, facet difference, and relational configuration difference. The premise that see-also relationships based on lexical similarity may be language-specific is briefly examined. The paper concludes with recommendations on the continued use of see-also relationships in the DDC.
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18

Wang, Jun. "An extensive study on automated Dewey Decimal Classification." Journal of the American Society for Information Science and Technology 60, no. 11 (November 2009): 2269–86. http://dx.doi.org/10.1002/asi.21147.

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19

Stann, Patsy Haley. "Dewey decimal classification and relative index. Edition 20." Information Processing & Management 26, no. 6 (January 1990): 806. http://dx.doi.org/10.1016/0306-4573(90)90056-8.

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20

Mohamad, Rotmianto. "Observing Optional Number in DDC Edition 23." Record and Library Journal 1, no. 1 (January 2, 2018): 48. http://dx.doi.org/10.20473/rlj.v1-i1.2015.48-58.

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Dewey Decimal Classification is a most popular classification system in the world because of its completeness and most up-to-date. There are many optional number in this classification system, although it rarely to be discussed even it is important to known well about that optional number, especially for a librarian as classifier. This paper is a literature study about Dewey Decimal Classification Edition 23, to describe about optional numbers, particularly the number in relationship with Indonesia’s subject and discipline. This paper is to avoid misunderstanding in interpreted about optional number among librarians, especially for who that does not understand well about optional numbers.
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Rotmianto, Mohamad. "Observing Optional Number in DDC Edition 23." Record and Library Journal 1, no. 1 (April 29, 2015): 48. http://dx.doi.org/10.20473/rlj.v1i1.78.

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Dewey Decimal Classification is a most popular classification system in the world because of its completeness and most up-to-date. There are many optional number in this classification system, although it rarely to be discussed even it is important to known well about that optional number, especially for a librarian as classifier. This paper is a literature study about Dewey Decimal Classification Edition 23, to describe about optional numbers, particularly the number in relationship with Indonesia’s subject and discipline. This paper is to avoid misunderstanding in interpreted about optional number among librarians, especially for who that does not understand well about optional numbers.
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22

Cripps, Jill. "Dewey and the visual arts: some thoughts on the scheme and its application." Art Libraries Journal 36, no. 4 (2011): 5–12. http://dx.doi.org/10.1017/s0307472200017132.

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The Dewey Decimal Classification system, frequently used to arrange arts collections, has a number of commendable aspects but also some significant shortcomings. Evidence suggests that visual arts library users can further their creative ideas by browsing library shelves, and the author considers this should inform classification practice. Dewey, approached from a user perspective and applied with attention to the scheme’s potential, can provide a shelf order that promotes browsing. The common perception that Dewey is most suited to general library collections is perhaps not entirely justified. Within the visual arts, it possibly accommodates specialist resources rather better than is sometimes imagined, particularly with judicious adaptation. A number of modifications are easy enough to achieve and may be applied across a range of visual arts resources.
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23

Rosita, Yesy Diah, and Yanuarini Nur Sukmaningtyas. "LSTM Network and OCR Performance for Classification of Decimal Dewey Classification Code." Record and Library Journal 6, no. 1 (April 13, 2020): 45. http://dx.doi.org/10.20473/rlj.v6-i1.2020.45-56.

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Background of the study: Giving book code by a librarian in accordance with the Decimal Dewey Classification system aims to facilitate the search for books on the shelf precisely and quickly. Purpose: The first step in giving code to determine the class of books is the principal division which has 10 classes.Method: This study proposed Optical Character Recognition to read the title text on the book cover, preprocessing the text, and classifying it by Long Short-Term Memory Neural Network. Findings: In general, a librarian labeled a book by reading the book title on the book cover and doing book class matching with the book guide of DDC. Automatically, the task requires time increasingly. We tried to classify the text without OCR and utilize OCR which functions to convert the text in images into text that is editable. BY the experimental result, the level of classification accuracy without utilizing OCR is higher than using OCR. Conclusion: The magnitude of the accuracy is 88.57% and 74.28% respectively. However, the participation of OCR in this classification is quite efficient enough to assist a beginner librarian to overcome this problem because the accuracy difference is less than 15%.
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24

Tomoyose, Kazumi, and Ana Carolina Simionato Arakaki. "Classification on the Web: an analysis of Dewey Linked Data." Palabra Clave (La Plata) 9, no. 2 (April 10, 2020): e092. http://dx.doi.org/10.24215/18539912e092.

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With the availability of information in the World Wide Web its access and retrieval by the users is facilitated, and the Library and Information Science (LIS) field’s knowledge and techniques can be applied to this environment in order to help with the process. The present study is descriptive, qualitative and exploratory, based on bibliographical sources, in which it was explored how the Classification discipline interacts with Linked Data, focusing on the analysis of Dewey Linked Data. From four catalogs analyzed, referred to in the literature as adhering to Dewey Linked Data, only two actually has links in their records redirecting to the system. Despite this, its presence in The Linked Open Data Cloud appears as a positive factor in its dissemination, since it boosts its visibility. It is concluded that the Classification discipline allows the thematic standardization of information resources, so that there is uniformity in the Web environment and quality retrieval of information, while promoting interoperability between data in the Linked Data context. The standardization of metadata values using classifications optimizes the representation of information and its retrieval in the Web, while also providing the reuse of data. In addition, studies that align the area of Library and Information Science with the Semantic Web and its technologies can provide new perspectives for the area, as well as contemplate the users’ always changing needs, thus, fulfilling the objective of the field.
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25

Hill, Janet Swan. "Melvil Dewey: The Man and the Classification (Book Review)." College & Research Libraries 46, no. 1 (January 1, 1985): 87–88. http://dx.doi.org/10.5860/crl_46_01_87.

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26

Landry, Patrice. "Dewey Decimal Classification (DDC) at the Swiss National Library." Cataloging & Classification Quarterly 42, no. 3-4 (August 2006): 135–45. http://dx.doi.org/10.1300/j104v42n03_05.

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27

Godby, C. Jean. "Enhancing the Indexing Vocabulary of the Dewey Decimal Classification." Journal of Library Administration 34, no. 1-2 (December 2001): 191–98. http://dx.doi.org/10.1300/j111v34n01_29.

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28

Silva, Maria Stella Vercesi. "Adaptation of dewey s decimal classification for physical education." Revista Paulista de Educação Física 3, no. 4 (June 20, 1989): 47. http://dx.doi.org/10.11606/issn.2594-5904.rpef.1989.138826.

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29

COMAROMI, JOHN P., and MOHINDER PARTAP SATIJA. "History of the Indianization of the Dewey Decimal Classification." Libri 35, no. 1 (1985): 1–20. http://dx.doi.org/10.1515/libr.1985.35.1.1.

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30

Golub, Koraljka, Johan Hagelbäck, and Anders Ardö. "Automatic Classification of Swedish Metadata Using Dewey Decimal Classification: A Comparison of Approaches." Journal of Data and Information Science 5, no. 1 (April 22, 2020): 18–38. http://dx.doi.org/10.2478/jdis-2020-0003.

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AbstractPurposeWith more and more digital collections of various information resources becoming available, also increasing is the challenge of assigning subject index terms and classes from quality knowledge organization systems. While the ultimate purpose is to understand the value of automatically produced Dewey Decimal Classification (DDC) classes for Swedish digital collections, the paper aims to evaluate the performance of six machine learning algorithms as well as a string-matching algorithm based on characteristics of DDC.Design/methodology/approachState-of-the-art machine learning algorithms require at least 1,000 training examples per class. The complete data set at the time of research involved 143,838 records which had to be reduced to top three hierarchical levels of DDC in order to provide sufficient training data (totaling 802 classes in the training and testing sample, out of 14,413 classes at all levels).FindingsEvaluation shows that Support Vector Machine with linear kernel outperforms other machine learning algorithms as well as the string-matching algorithm on average; the string-matching algorithm outperforms machine learning for specific classes when characteristics of DDC are most suitable for the task. Word embeddings combined with different types of neural networks (simple linear network, standard neural network, 1D convolutional neural network, and recurrent neural network) produced worse results than Support Vector Machine, but reach close results, with the benefit of a smaller representation size. Impact of features in machine learning shows that using keywords or combining titles and keywords gives better results than using only titles as input. Stemming only marginally improves the results. Removed stop-words reduced accuracy in most cases, while removing less frequent words increased it marginally. The greatest impact is produced by the number of training examples: 81.90% accuracy on the training set is achieved when at least 1,000 records per class are available in the training set, and 66.13% when too few records (often less than 100 per class) on which to train are available—and these hold only for top 3 hierarchical levels (803 instead of 14,413 classes).Research limitationsHaving to reduce the number of hierarchical levels to top three levels of DDC because of the lack of training data for all classes, skews the results so that they work in experimental conditions but barely for end users in operational retrieval systems.Practical implicationsIn conclusion, for operative information retrieval systems applying purely automatic DDC does not work, either using machine learning (because of the lack of training data for the large number of DDC classes) or using string-matching algorithm (because DDC characteristics perform well for automatic classification only in a small number of classes). Over time, more training examples may become available, and DDC may be enriched with synonyms in order to enhance accuracy of automatic classification which may also benefit information retrieval performance based on DDC. In order for quality information services to reach the objective of highest possible precision and recall, automatic classification should never be implemented on its own; instead, machine-aided indexing that combines the efficiency of automatic suggestions with quality of human decisions at the final stage should be the way for the future.Originality/valueThe study explored machine learning on a large classification system of over 14,000 classes which is used in operational information retrieval systems. Due to lack of sufficient training data across the entire set of classes, an approach complementing machine learning, that of string matching, was applied. This combination should be explored further since it provides the potential for real-life applications with large target classification systems.
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31

O'Neill, Edward T., Martin Dillon, and Diane Vizine-Goetz. "Class dispersion between the Library of Congress Classification and the Dewey Decimal Classification." Journal of the American Society for Information Science 38, no. 3 (May 1987): 197–205. http://dx.doi.org/10.1002/(sici)1097-4571(198705)38:3<197::aid-asi8>3.0.co;2-2.

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32

Green, Rebecca, and Giles Martin. "A Rosid Is a Rosid Is a Rosid . . . or Not." Advances in Classification Research Online 23, no. 1 (January 30, 2013): 9. http://dx.doi.org/10.7152/acro.v23i1.14228.

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The current structure of 583 Magnoliopsida (Dicotyledons) and 584 Liliopsida (Monocotyledons) in the Dewey Decimal Classification (DDC) system reflects changes made when the life sciences were thoroughly revised in 1996. Since that time, considerable progress has been made in the phylogenetic classification of angiosperms (flowering plants). In particular, APG III, the 2009 version of the classification developed by the Angiosperm Phylogeny Group, is finding use as a tool to organize both botanical information and botanical collections. The Dewey Editorial Office has received a request to revise 583–584 in light of this taxonomy ―as appropriate‖; relevant revisions would be likely to include both structural and terminological changes. In deciding how to provide accommodation for APG III, the Dewey editorial team must address many issues: Is APG III now stable enough and accepted broadly enough to be adopted as the basis for a major revision of the DDC? Should revisions in 583–584 be coordinated with parallel revisions in other parts of the life sciences? What revision strategies can be considered in revising 583-584 to accommodate APG III? What are their various strengths and weaknesses? How have other major classification schemes (e.g., the UDC) accommodated APG III? Discussion of these issues is guided by the principles (―editorial rules‖) that govern development of the DDC.
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Green, Rebecca, and Michael Panzer. "The Interplay of Big Data, WorldCat, and Dewey." Advances in Classification Research Online 24, no. 1 (January 9, 2014): 51. http://dx.doi.org/10.7152/acro.v24i1.14677.

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As the premier example of big data in the bibliographic world, WorldCat has the potential to support knowledge discovery in many arenas. After giving evidence for a big data characterization of WorldCat, the paper explores this knowledge discovery potential from two perspectives related to the Dewey Decimal Classification (DDC) system: (1) how WorldCat data can inform development of the DDC (classification analytics) and (2) how DDC-classified content in WorldCat can shed light on the bibliographic world itself (collection analytics). In the realm of classification analytics, WorldCat data support decisions to modify the DDC by expanding or reducing the number of classes, adding topical coverage, or adding subject access points; data analysis can support recognition of (1) trending topics and (2) the faceted structure of subject domains. In the realm of collection analytics, the paper considers as possible applications the use of the DDC in the topical "fingerprinting" of categorized content in WorldCat or in performing a bibliographic gap analysis.
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34

Cours, Isabelle de. "Choosing a classification scheme for the Inha library in Paris." Art Libraries Journal 27, no. 1 (2002): 23–26. http://dx.doi.org/10.1017/s0307472200019945.

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The library of the Institut national d’histoire de l’art in Paris has recently conducted detailed research into the classification which will be used for the large amount of stock which will be on open access to its users. A working group was established which, after rejecting the idea of a specially created scheme, looked at what other systems were available, comparing those currently in use in the largest art and archaeology libraries in France and abroad. They also studied the two encyclopaedic classifications – Dewey and UDC. The final recommendation was adoption of the Library of Congress Classification and work to implement this decision is now under way.
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35

Tjiparuro, Zeundjua, and Shadreck Mumbiana Situmbeko. "Managing Hardcopy Drawings." International Journal of Engineering Research in Africa 7 (September 2012): 41–53. http://dx.doi.org/10.4028/www.scientific.net/jera.7.41.

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This Paper Presents a Classification System for Managing and Indexing Hardcopy Engineering Drawings, Referred to, in this Paper, as Drawings Library Management System (DLMS), Developed for an Appropriate Technology Research Centre in Botswana. the System Is Akin to Common Library Cataloguing and Classification Systems such as the Dewey Decimal Classification (DDC), Universal Decimal Classification and Others, which, though Are Well-Known and Have Been around for many Years, Are yet to Be Exploited for the Classification and Management of Paper Drawings. in Fact, Hardcopy Drawings Appear to Be Neglected Compared to the Softcopy Type, for which Various Scholarly Articles Have Been Done on their Classification, Retrieval and Management. this Is Unfortunate as, Invariably, it Is Hardcopy/paper Drawings that Are Mostly Used in Production, Especially in Developing Countries where the Power of CAD/CAM Is yet to Be Fully Harnessed. Accordingly, the DLMS, a Model Successfully Used in a Research Centre in Botswana for over Ten Years Is Proposed.The System Was Further Analysed against and Compared to Three Main Library Classification Systems, Namely, the Dewey Decimal, the Universal Decimal and the Library of Congress Systems. Results Show that the DLMS Is a Better Classification System for Managing Hardcopy Drawings.
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Fields, Anne M., and Tschera Harkness Connell. "Classification and the Definition of a Discipline: The Dewey Decimal Classification and Home Economics." Libraries & the Cultural Record 39, no. 3 (2004): 245–59. http://dx.doi.org/10.1353/lac.2004.0058.

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37

Curwen, Anthony G. "Book Review: Dewey decimal classification and relative index. Edition 21." Journal of Librarianship and Information Science 29, no. 3 (September 1997): 169–71. http://dx.doi.org/10.1177/096100069702900314.

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38

Khoo, Michael John, Jae-wook Ahn, Ceri Binding, Hilary Jane Jones, Xia Lin, Diana Massam, and Douglas Tudhope. "Augmenting Dublin Core digital library metadata with Dewey Decimal Classification." Journal of Documentation 71, no. 5 (September 14, 2015): 976–98. http://dx.doi.org/10.1108/jd-07-2014-0103.

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Purpose – The purpose of this paper is to describe a new approach to a well-known problem for digital libraries, how to search across multiple unrelated libraries with a single query. Design/methodology/approach – The approach involves creating new Dewey Decimal Classification terms and numbers from existing Dublin Core records. In total, 263,550 records were harvested from three digital libraries. Weighted key terms were extracted from the title, description and subject fields of each record. Ranked DDC classes were automatically generated from these key terms by considering DDC hierarchies via a series of filtering and aggregation stages. A mean reciprocal ranking evaluation compared a sample of 49 generated classes against DDC classes created by a trained librarian for the same records. Findings – The best results combined weighted key terms from the title, description and subject fields. Performance declines with increased specificity of DDC level. The results compare favorably with similar studies. Research limitations/implications – The metadata harvest required manual intervention and the evaluation was resource intensive. Future research will look at evaluation methodologies that take account of issues of consistency and ecological validity. Practical implications – The method does not require training data and is easily scalable. The pipeline can be customized for individual use cases, for example, recall or precision enhancing. Social implications – The approach can provide centralized access to information from multiple domains currently provided by individual digital libraries. Originality/value – The approach addresses metadata normalization in the context of web resources. The automatic classification approach accounts for matches within hierarchies, aggregating lower level matches to broader parents and thus approximates the practices of a human cataloger.
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SALES, Rodrigo de, Daniel MARTÍNEZ-ÁVILA, and José Augusto GUIMARÃES. "Dialogical elements in Harris, Dewey, Cutter, Otlet, Kaiser, and Ranganathan: Theoretical convergences in the history of Knowledge Organization." Transinformação 30, no. 3 (December 2018): 348–62. http://dx.doi.org/10.1590/2318-08892018000300007.

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Abstract In this paper, we study the theoretical intersections and dialogues between some foundational authors on classification and indexing of the nineteenth and twentieth centuries that helped developing the theoretical-methodological framework of knowledge organization. More specifically, we highlight and analyze the theoretical convergences of Harris, Dewey, Cutter, Otlet, Kaiser, and Ranganathan as they can provide a clearer picture of the historical and theoretical contributions to the epistemological foundations of knowledge organization. Our methodology follows a critical-descriptive approach to the analysis of the main contributions of the authors and the critical reflections of some specialists and biographers. We continue with a discussion of the links between bibliographic classifications and knowledge organization drawing on the ideas of Bliss; then, we divide our historical narrative between the theoretical contributions during the nineteenth-century (Harris, Dewey, and Cutter) and the twentieth century (Otlet, Kaiser, and Ranganathan); and finally, we present a discussion of the history of knowledge organization from the point of view of the theoretical and methodological development of classification and indexing at the turn of the nineteenth century to the twentieth century. We conclude with some remarks on their main contributions to the development of the knowledge organization field.
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40

Choi, Inkyung. "Visualizations of cross-cultural bibliographic classification: comparative studies of the Korean Decimal Classification and the Dewey Decimal Classification." NASKO 6, no. 1 (September 12, 2017): 39–55. http://dx.doi.org/10.7152/nasko.v6i1.15229.

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41

Fox, Melodie J. "Legal Discourse’s Epistemic Interplay with Sex and Gender Classification in the Dewey Decimal Classification System." Library Trends 64, no. 4 (2016): 687–713. http://dx.doi.org/10.1353/lib.2016.0016.

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42

Patterson, Jordan. "Dewey Decimal Classification Trending Downward in U.S. Academic Libraries, but Unlikely to Disappear Completely." Evidence Based Library and Information Practice 14, no. 3 (September 12, 2019): 156–58. http://dx.doi.org/10.18438/eblip29592.

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A Review of: Lund, B., & Agbaji, D. (2018). Use of Dewey Decimal Classification by academic libraries in the United States. Cataloging and Classification Quarterly, 56(7), 653-661. https://doi.org/10.1080/01639374.2018.1517851 Abstract Objective – To determine the current use of Dewey Decimal Classification in academic libraries in the United States of America (U.S.). Design – Cross-sectional survey using a systematic sampling method. Setting – Online academic library catalogues in the U.S. Subjects – 3,973 academic library catalogues. Methods – The researchers identified 3,973 academic libraries affiliated with degree-granting post-secondary institutions in the U.S. The researchers searched each library’s online catalogue for 10 terms from a predetermined list. From the results of each search, the researchers selected at least five titles, noted the classification scheme used to classify each title, and coded the library as using Dewey Decimal Classification (DDC), Library of Congress Classification (LCC), both DDC and LCC, or other classification schemes. Based on the results of their data collection, the researchers calculated totals. The totals of this current study’s data collection were compared to statistics on DDC usage from two previous reports, one published in 1975 and one in 1996. The researchers performed statistical analyses to determine if there were any discernible trends from the earliest reported statistics through to the current study. Main Results – Collections classified using DDC were present in 717 libraries (18.9%). Adjusting for the increase in the number of academic libraries in the U.S. between 1975 and 2017, DDC usage in academic libraries has declined by 56% in that time frame. The number of libraries with only DDC in evidence is unreported. Conclusion – The previous four decades have seen a significant decrease in the use of DDC in U.S. academic libraries in favour of LCC; however, the rate at which DDC has disappeared from academic libraries has slowed dramatically since the 1960s. There is no clear indication that DDC will disappear from academic libraries completely.
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Fox, Megan. "Tentative Supplement to (the History of) Classification." IJournal: Graduate Student Journal of the Faculty of Information 4, no. 3 (September 25, 2019): 21–27. http://dx.doi.org/10.33137/ijournal.v4i3.33076.

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As interdisciplinarity becomes more ubiquitous within academia, information professionals are grappling with how to renegotiate reductive and oppressive classification structures. Librarians of color, however, have been altering these structures since their implementation to better serve their communities. This paper highlights two examples of such renegotiations, and explores the implications for implementing their methodologies into mainstream library praxis. Dorothy Porter’s supplement to the Dewey Decimal System and the Brian Deer Classification system both offer operationalizable solutions to concerns contemporary information science has with cultivating useful and equitable classification systems. Keywords: Libraries, curation, black librarianship, indigenous librarianship, classification theory
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Kim, Jeong-Hyen, and Ji-Hyun Moon. "A Study on the Development of the Abridged Dewey Decimal Classification." Journal of the Korean Society for Library and Information Science 43, no. 3 (September 30, 2009): 379–97. http://dx.doi.org/10.4275/kslis.2009.43.3.379.

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Rohman, Asep Saeful, Prijana Prijana, and Samson CMS. "Perluasan notasi Dewey Decimal Classification (DDC) tentang bahasa dan susastra Sunda." Jurnal Kajian Informasi dan Perpustakaan 5, no. 2 (May 31, 2018): 155. http://dx.doi.org/10.24198/jkip.v5i2.11014.

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Golub, Koraljka, Marianne Lykke, and Douglas Tudhope. "Enhancing social tagging with automated keywords from the Dewey Decimal Classification." Journal of Documentation 70, no. 5 (September 2, 2014): 801–28. http://dx.doi.org/10.1108/jd-05-2013-0056.

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Purpose – The purpose of this paper is to explore the potential of applying the Dewey Decimal Classification (DDC) as an established knowledge organization system (KOS) for enhancing social tagging, with the ultimate purpose of improving subject indexing and information retrieval. Design/methodology/approach – Over 11,000 Intute metadata records in politics were used. Totally, 28 politics students were each given four tasks, in which a total of 60 resources were tagged in two different configurations, one with uncontrolled social tags only and another with uncontrolled social tags as well as suggestions from a controlled vocabulary. The controlled vocabulary was DDC comprising also mappings from the Library of Congress Subject Headings. Findings – The results demonstrate the importance of controlled vocabulary suggestions for indexing and retrieval: to help produce ideas of which tags to use, to make it easier to find focus for the tagging, to ensure consistency and to increase the number of access points in retrieval. The value and usefulness of the suggestions proved to be dependent on the quality of the suggestions, both as to conceptual relevance to the user and as to appropriateness of the terminology. Originality/value – No research has investigated the enhancement of social tagging with suggestions from the DDC, an established KOS, in a user trial, comparing social tagging only and social tagging enhanced with the suggestions. This paper is a final reflection on all aspects of the study.
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Markey, Karen. "Searching and Browsing the Dewey Decimal Classification in an Online Catalog." Cataloging & Classification Quarterly 7, no. 3 (June 4, 1987): 37–68. http://dx.doi.org/10.1300/j104v07n03_05.

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Barkworth, M. E., and Von Bothmer R. "Twenty-one years later: the impact of Löve and Dewey’s genomic classification proposal." Czech Journal of Genetics and Plant Breeding 41, Special Issue (July 31, 2012): 3–9. http://dx.doi.org/10.17221/6125-cjgpb.

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Fox, Melodie. "Epistemic Contrast in Medical and Legal Gender Classifications and their Influences on the Dewey Decimal Classification." NASKO 5, no. 1 (September 12, 2017): 112–14. http://dx.doi.org/10.7152/nasko.v5i1.15184.

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Salem, Nahed Mohamad Basyoni. "The Logic Behind the Classification of Sciences in the Arab-Islamic Classification Systems: with the Modern Western Classification Systems An Analytical Comparative Reading." Journal of Arts and Social Sciences [JASS] 7, no. 3 (December 1, 2016): 69. http://dx.doi.org/10.24200/jass.vol7iss3pp69-78.

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This study aimed to explore the rules and principles adopted in the Arab-Islamic Classification Systems and tried to identify their scientific methods to determine the relations between sciences. The study followed the comparative analytical method to analyze and compare the Arab-Islamic Classification Systems with the Western modern ones represented in the Dewey Decimal Classification System and the Library of Congress Classification System. The research tries to explore the logic behind classification of sciences in the Arab-Islamic Classification Systems. The findings revealed that the Arab-Islamic Classification Systems follow the same rules and principles of modern classification systems and their types are represented in the types of modern Western classification systems. The study recommends the need to conduct research on the Arab-Islamic Classification Systems and introduce it.
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