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Abstract

Named Entities (benannte Entitäten) - wie Personen, Organisationen, Orte, Ereignisse und Werke - sind wichtige inhaltstragende Komponenten eines Dokuments und sind daher maßgeblich für eine gute inhaltliche Erschließung. Die Erkennung von Named Entities, deren Auszeichnung (Annotation) und Verfügbarmachung für die Suche sind wichtige Instrumente, um Anwendungen wie z. B. die inhaltliche oder semantische Suche in Texten, dokumentübergreifende Kontextualisierung oder das automatische Textzusammenfassen zu verbessern. Inhaltlich präzise und nachhaltig erschlossen werden die erkannten Named Entities eines Dokuments allerdings erst, wenn sie mit einer oder mehreren Quellen verknüpft werden (Grundprinzip von Linked Data, Berners-Lee 2006), die die Entität eindeutig identifizieren und gegenüber gleichlautenden Entitäten disambiguieren (vergleiche z. B. Berlin als Hauptstadt Deutschlands mit dem Komponisten Irving Berlin). Dazu wird die im Dokument erkannte Entität mit dem Entitätseintrag einer Normdatei oder einer anderen zuvor festgelegten Wissensbasis (z. B. Gazetteer für geografische Entitäten) verknüpft, gewöhnlich über den persistenten Identifikator der jeweiligen Wissensbasis oder Normdatei. Durch die Verknüpfung mit einer Normdatei erfolgt nicht nur die Disambiguierung und Identifikation der Entität, sondern es wird dadurch auch Interoperabilität zu anderen Systemen hergestellt, in denen die gleiche Normdatei benutzt wird, z. B. die Suche nach der Hauptstadt Berlin in verschiedenen Datenbanken bzw. Portalen. Die Entitätenverknüpfung (Named Entity Linking, NEL) hat zudem den Vorteil, dass die Normdateien oftmals Relationen zwischen Entitäten enthalten, sodass Dokumente, in denen Named Entities erkannt wurden, zusätzlich auch im Kontext einer größeren Netzwerkstruktur von Entitäten verortet und suchbar gemacht werden können

Series

Bibliotheks- und Informationspraxis; 70

Source

Qualität in der Inhaltserschließung. Hrsg.: M. Franke-Maier, u.a

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Abstract

In 2015, the PCC Task Group on URIs in MARC was tasked to identify and address linked data identifiers deployment in the current MARC format. By way of a pilot test, a survey, MARC Discussion papers, Proposals, etc., the Task Group initiated and introduced changes to MARC encoding. The Task Group succeeded in laying the ground work for preparing library data transition from MARC data to a linked data, RDF environment.

Footnote

Beitrag in einem Themenheft: 'Program for Cooperative Cataloging (PCC): 25 Years Strong and Growing!'.

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Abstract

Drawing on the PCC's history with linked data and related work this article identifies and gives context to pressing areas PCC will need to focus on moving forward. These areas include defining plausible data targets, tractable implementation models and data flows, engaging in related tool development, and participating in the broader linked data community.

Footnote

Beitrag in einem Themenheft: 'Program for Cooperative Cataloging (PCC): 25 Years Strong and Growing!'.

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Abstract

Library Technical Services have benefited from numerous stimuli. Although initially looked at with suspicion, transitions such as the move from catalog cards to the MARC formats have proven enormously helpful to libraries and their patrons. Linked data and Artificial Intelligence (AI) hold the same promise. Through the conversion of metadata surrogates (cataloging) to linked open data, libraries can represent their resources on the Semantic Web. But in order to provide some form of controlled access to unstructured data, libraries must reach beyond traditional cataloging to new tools such as AI to provide consistent access to a growing world of full-text resources.

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Abstract

The mapping from BIBFRAME 2.0 to Resource Description and Access (RDA) is studied focusing on core entities, inherent relationships, and derivative relationships. The proposed mapping rules are evaluated with two gold datasets. Findings indicate that 1) core entities, inherent and derivative relationships may be mapped to RDA, 2) the use of the bf:hasExpression property may cluster bf:Works with the same ideational content and enable their mapping to RDA Works with their Expressions, and 3) cataloging policies have a significant impact on the interoperability between RDA and BIBFRAME datasets. This work complements the investigation of semantic interoperability between the two models previously presented in this journal.