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Abstract

In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects. Design/methodology/approach This study's analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians' theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures' suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness. Findings This study's results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity. Originality/value The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study's results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.

Theme

Semantic Web

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Date

22. 5.2021 12:43:05

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Abstract

Manuscripts are a crucial form of evidence for research into all aspects of premodern European history and culture, and there are numerous databases devoted to describing them in detail. This descriptive information, however, is typically available only in separate data silos based on incompatible data models and user interfaces. As a result, it has been difficult to study manuscripts comprehensively across these various platforms. To address this challenge, a team of manuscript scholars and computer scientists worked to create "Mapping Manuscript Migrations" (MMM), a semantic portal, and a Linked Open Data service. MMM stands as a successful proof of concept for integrating distinct manuscript datasets into a shared platform for research and discovery with the potential for future expansion. This paper will discuss the major products of the MMM project: a unified data model, a repeatable data transformation pipeline, a Linked Open Data knowledge graph, and a Semantic Web portal. It will also examine the crucial importance of an iterative process of multidisciplinary collaboration embedded throughout the project, enabling humanities researchers to shape the development of a digital platform and tools, while also enabling the same researchers to ask more sophisticated and comprehensive research questions of the aggregated data.

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Content

Inhalt: Editorial - Michael Franke-Maier, Anna Kasprzik, Andreas Ledl und Hans Schürmann Qualität in der Inhaltserschließung - Ein Überblick aus 50 Jahren (1970-2020) - Andreas Ledl Fit for Purpose - Standardisierung von inhaltserschließenden Informationen durch Richtlinien für Metadaten - Joachim Laczny Neue Wege und Qualitäten - Die Inhaltserschließungspolitik der Deutschen Nationalbibliothek - Ulrike Junger und Frank Scholze Wissensbasen für die automatische Erschließung und ihre Qualität am Beispiel von Wikidata - Lydia Pintscher, Peter Bourgonje, Julián Moreno Schneider, Malte Ostendorff und Georg Rehm Qualitätssicherung in der GND - Esther Scheven Qualitätskriterien und Qualitätssicherung in der inhaltlichen Erschließung - Thesenpapier des Expertenteams RDA-Anwendungsprofil für die verbale Inhaltserschließung (ET RAVI) Coli-conc - Eine Infrastruktur zur Nutzung und Erstellung von Konkordanzen - Uma Balakrishnan, Stefan Peters und Jakob Voß Methoden und Metriken zur Messung von OCR-Qualität für die Kuratierung von Daten und Metadaten - Clemens Neudecker, Karolina Zaczynska, Konstantin Baierer, Georg Rehm, Mike Gerber und Julián Moreno Schneider Datenqualität als Grundlage qualitativer Inhaltserschließung - Jakob Voß Bemerkungen zu der Qualitätsbewertung von MARC-21-Datensätzen - Rudolf Ungváry und Péter Király Named Entity Linking mit Wikidata und GND - Das Potenzial handkuratierter und strukturierter Datenquellen für die semantische Anreicherung von Volltexten - Sina Menzel, Hannes Schnaitter, Josefine Zinck, Vivien Petras, Clemens Neudecker, Kai Labusch, Elena Leitner und Georg Rehm Ein Protokoll für den Datenabgleich im Web am Beispiel von OpenRefine und der Gemeinsamen Normdatei (GND) - Fabian Steeg und Adrian Pohl Verbale Erschließung in Katalogen und Discovery-Systemen - Überlegungen zur Qualität - Heidrun Wiesenmüller Inhaltserschließung für Discovery-Systeme gestalten - Jan Frederik Maas Evaluierung von Verschlagwortung im Kontext des Information Retrievals - Christian Wartena und Koraljka Golub Die Qualität der Fremddatenanreicherung FRED - Cyrus Beck Quantität als Qualität - Was die Verbünde zur Verbesserung der Inhaltserschließung beitragen können - Rita Albrecht, Barbara Block, Mathias Kratzer und Peter Thiessen Hybride Künstliche Intelligenz in der automatisierten Inhaltserschließung - Harald Sack