-
Hider, P.; Coe, M.: Academic disciplines in the context of library classification : mapping university faculty structures to the DDC and LCC schemes (2022)
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- Abstract
- We investigated the extent to which the Dewey Decimal Classification (DDC) and the Library of Congress Classification reflect the organizational structures of Australian universities. The mapping of the faculty structures of ten universities to the two schemes showed strong alignment, with very few fields represented in the names of the organizational units not covered at all by either bibliographic scheme. This suggests a degree of universality and "scientific and educational consensus" with respect to both the schemes and academic disciplines. The article goes on to discuss the concept of discipline and its application in bibliographic classification.
- Source
- Cataloging and classification quarterly. 60(2022) no.2, p.194-213
-
Binding, C.; Gnoli, C.; Tudhope, D.: Migrating a complex classification scheme to the semantic web : expressing the Integrative Levels Classification using SKOS RDF (2021)
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- Abstract
- Purpose The Integrative Levels Classification (ILC) is a comprehensive "freely faceted" knowledge organization system not previously expressed as SKOS (Simple Knowledge Organization System). This paper reports and reflects on work converting the ILC to SKOS representation. Design/methodology/approach The design of the ILC representation and the various steps in the conversion to SKOS are described and located within the context of previous work considering the representation of complex classification schemes in SKOS. Various issues and trade-offs emerging from the conversion are discussed. The conversion implementation employed the STELETO transformation tool. Findings The ILC conversion captures some of the ILC facet structure by a limited extension beyond the SKOS standard. SPARQL examples illustrate how this extension could be used to create faceted, compound descriptors when indexing or cataloguing. Basic query patterns are provided that might underpin search systems. Possible routes for reducing complexity are discussed. Originality/value Complex classification schemes, such as the ILC, have features which are not straight forward to represent in SKOS and which extend beyond the functionality of the SKOS standard. The ILC's facet indicators are modelled as rdf:Property sub-hierarchies that accompany the SKOS RDF statements. The ILC's top-level fundamental facet relationships are modelled by extensions of the associative relationship - specialised sub-properties of skos:related. An approach for representing faceted compound descriptions in ILC and other faceted classification schemes is proposed.
-
Ahmed, M.; Mukhopadhyay, M.; Mukhopadhyay, P.: Automated knowledge organization : AI ML based subject indexing system for libraries (2023)
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- Abstract
- The research study as reported here is an attempt to explore the possibilities of an AI/ML-based semi-automated indexing system in a library setup to handle large volumes of documents. It uses the Python virtual environment to install and configure an open source AI environment (named Annif) to feed the LOD (Linked Open Data) dataset of Library of Congress Subject Headings (LCSH) as a standard KOS (Knowledge Organisation System). The framework deployed the Turtle format of LCSH after cleaning the file with Skosify, applied an array of backend algorithms (namely TF-IDF, Omikuji, and NN-Ensemble) to measure relative performance, and selected Snowball as an analyser. The training of Annif was conducted with a large set of bibliographic records populated with subject descriptors (MARC tag 650$a) and indexed by trained LIS professionals. The training dataset is first treated with MarcEdit to export it in a format suitable for OpenRefine, and then in OpenRefine it undergoes many steps to produce a bibliographic record set suitable to train Annif. The framework, after training, has been tested with a bibliographic dataset to measure indexing efficiencies, and finally, the automated indexing framework is integrated with data wrangling software (OpenRefine) to produce suggested headings on a mass scale. The entire framework is based on open-source software, open datasets, and open standards.
-
Folsom, S.M.: Using the Program for Cooperative Cataloging's past and present to project a Linked Data future (2020)
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- Source
- Cataloging and classification quarterly. 58(2020) no.3/4, S.464-471
-
Naun, C.C.: Expanding the use of Linked Data value vocabularies in PCC cataloging (2020)
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- Source
- Cataloging and classification quarterly. 58(2020) no.3/4, S.449-457
-
Schreur, P.E.: ¬The use of Linked Data and artificial intelligence as key elements in the transformation of technical services (2020)
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- Source
- Cataloging and classification quarterly. 58(2020) no.5, S.473-485
-
Sfakakis, M.; Zapounidou, S.; Papatheodorou, C.: Mapping derivative relationships from BIBFRAME 2.0 to RDA (2020)
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- Source
- Cataloging and classification quarterly. 58(2020) no.7, S.603-631
-
Smith, A.: Simple Knowledge Organization System (SKOS) (2022)
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- Abstract
- SKOS (Simple Knowledge Organization System) is a recommendation from the World Wide Web Consortium (W3C) for representing controlled vocabularies, taxonomies, thesauri, classifications, and similar systems for organizing and indexing information as linked data elements in the Semantic Web, using the Resource Description Framework (RDF). The SKOS data model is centered on "concepts", which can have preferred and alternate labels in any language as well as other metadata, and which are identified by addresses on the World Wide Web (URIs). Concepts are grouped into hierarchies through "broader" and "narrower" relations, with "top concepts" at the broadest conceptual level. Concepts are also organized into "concept schemes", also identified by URIs. Other relations, mappings, and groupings are also supported. This article discusses the history of the development of SKOS and provides notes on adoption, uses, and limitations.
-
Lee, S.: Pidgin metadata framework as a mediator for metadata interoperability (2021)
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- Abstract
- A pidgin metadata framework based on the concept of pidgin metadata is proposed to complement the limitations of existing approaches to metadata interoperability and to achieve more reliable metadata interoperability. The framework consists of three layers, with a hierarchical structure, and reflects the semantic and structural characteristics of various metadata. Layer 1 performs both an external function, serving as an anchor for semantic association between metadata elements, and an internal function, providing semantic categories that can encompass detailed elements. Layer 2 is an arbitrary layer composed of substantial elements from existing metadata and performs a function in which different metadata elements describing the same or similar aspects of information resources are associated with the semantic categories of Layer 1. Layer 3 implements the semantic relationships between Layer 1 and Layer 2 through the Resource Description Framework syntax. With this structure, the pidgin metadata framework can establish the criteria for semantic connection between different elements and fully reflect the complexity and heterogeneity among various metadata. Additionally, it is expected to provide a bibliographic environment that can achieve more reliable metadata interoperability than existing approaches by securing the communication between metadata.
-
Steeg, F.; Pohl, A.: ¬Ein Protokoll für den Datenabgleich im Web am Beispiel von OpenRefine und der Gemeinsamen Normdatei (GND) (2021)
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- Abstract
- Normdaten spielen speziell im Hinblick auf die Qualität der Inhaltserschließung bibliografischer und archivalischer Ressourcen eine wichtige Rolle. Ein konkretes Ziel der Inhaltserschließung ist z. B., dass alle Werke über Hermann Hesse einheitlich zu finden sind. Hier bieten Normdaten eine Lösung, indem z. B. bei der Erschließung einheitlich die GND-Nummer 11855042X für Hermann Hesse verwendet wird. Das Ergebnis ist eine höhere Qualität der Inhaltserschließung vor allem im Sinne von Einheitlichkeit und Eindeutigkeit und, daraus resultierend, eine bessere Auffindbarkeit. Werden solche Entitäten miteinander verknüpft, z. B. Hermann Hesse mit einem seiner Werke, entsteht ein Knowledge Graph, wie ihn etwa Google bei der Inhaltserschließung des Web verwendet (Singhal 2012). Die Entwicklung des Google Knowledge Graph und das hier vorgestellte Protokoll sind historisch miteinander verbunden: OpenRefine wurde ursprünglich als Google Refine entwickelt, und die Funktionalität zum Abgleich mit externen Datenquellen (Reconciliation) wurde ursprünglich zur Einbindung von Freebase entwickelt, einer der Datenquellen des Google Knowledge Graph. Freebase wurde später in Wikidata integriert. Schon Google Refine wurde zum Abgleich mit Normdaten verwendet, etwa den Library of Congress Subject Headings (Hooland et al. 2013).
-
Candela, G.: ¬An automatic data quality approach to assess semantic data from cultural heritage institutions (2023)
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- Date
- 22. 6.2023 18:23:31
-
Marcondes, C.H.: Towards a vocabulary to implement culturally relevant relationships between digital collections in heritage institutions (2020)
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- Date
- 4. 3.2020 14:22:41
