Search (12 results, page 1 of 1)

  • × year_i:[2020 TO 2030}
  • × theme_ss:"Semantische Interoperabilität"
  1. Isaac, A.; Raemy, J.A.; Meijers, E.; Valk, S. De; Freire, N.: Metadata aggregation via linked data : results of the Europeana Common Culture project (2020) 0.06 
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    Abstract
    Digital cultural heritage resources are widely available on the web through the digital libraries of heritage institutions. To address the difficulties of discoverability in cultural heritage, the common practice is metadata aggregation, where centralized efforts like Europeana facilitate discoverability by collecting the resources' metadata. We present the results of the linked data aggregation task conducted within the Europeana Common Culture project, which attempted an innovative approach to aggregation based on linked data made available by cultural heritage institutions. This task ran for one year with participation of eleven organizations, involving the three member roles of the Europeana network: data providers, intermediary aggregators, and the central aggregation hub, Europeana. We report on the challenges that were faced by data providers, the standards and specifications applied, and the resulting aggregated metadata.
  2. Marcondes, C.H.: Towards a vocabulary to implement culturally relevant relationships between digital collections in heritage institutions (2020) 0.06 
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    Abstract
    Cultural heritage institutions are publishing their digital collections over the web as LOD. This is is a new step in the patrimonialization and curatorial processes developed by such institutions. Many of these collections are thematically superimposed and complementary. Frequently, objects in these collections present culturally relevant relationships, such as a book about a painting, or a draft or sketch of a famous painting, etc. LOD technology enables such heritage records to be interlinked, achieving interoperability and adding value to digital collections, thus empowering heritage institutions. An aim of this research is characterizing such culturally relevant relationships and organizing them in a vocabulary. Use cases or examples of relationships between objects suggested by curators or mentioned in literature and in the conceptual models as FRBR/LRM, CIDOC CRM and RiC-CM, were collected and used as examples or inspiration of cultural relevant relationships. Relationships identified are collated and compared for identifying those with the same or similar meaning, synthesized and normalized. A set of thirty-three culturally relevant relationships are identified and formalized as a LOD property vocabulary to be used by digital curators to interlink digital collections. The results presented are provisional and a starting point to be discussed, tested, and enhanced.
    Date
    4. 3.2020 14:22:41
  3. Candela, G.: ¬An automatic data quality approach to assess semantic data from cultural heritage institutions (2023) 0.05 
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    Abstract
    In recent years, cultural heritage institutions have been exploring the benefits of applying Linked Open Data to their catalogs and digital materials. Innovative and creative methods have emerged to publish and reuse digital contents to promote computational access, such as the concepts of Labs and Collections as Data. Data quality has become a requirement for researchers and training methods based on artificial intelligence and machine learning. This article explores how the quality of Linked Open Data made available by cultural heritage institutions can be automatically assessed. The results obtained can be useful for other institutions who wish to publish and assess their collections.
    Date
    22. 6.2023 18:23:31
  4. Gabler, S.: Vergabe von DDC-Sachgruppen mittels eines Schlagwort-Thesaurus (2021) 0.05 
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    Content
    Master thesis Master of Science (Library and Information Studies) (MSc), Universität Wien. Advisor: Christoph Steiner. Vgl.: https://www.researchgate.net/publication/371680244_Vergabe_von_DDC-Sachgruppen_mittels_eines_Schlagwort-Thesaurus. DOI: 10.25365/thesis.70030. Vgl. dazu die Präsentation unter: https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=web&cd=&ved=0CAIQw7AJahcKEwjwoZzzytz_AhUAAAAAHQAAAAAQAg&url=https%3A%2F%2Fwiki.dnb.de%2Fdownload%2Fattachments%2F252121510%2FDA3%2520Workshop-Gabler.pdf%3Fversion%3D1%26modificationDate%3D1671093170000%26api%3Dv2&psig=AOvVaw0szwENK1or3HevgvIDOfjx&ust=1687719410889597&opi=89978449.
    Imprint
    Wien / Library and Information Studies : Universität
  5. Peponakis, M.; Mastora, A.; Kapidakis, S.; Doerr, M.: Expressiveness and machine processability of Knowledge Organization Systems (KOS) : an analysis of concepts and relations (2020) 0.01 
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    Source
    International journal on digital libraries. 20(2020) no.4, S.433-452
  6. Kahlawi, A,: ¬An ontology driven ESCO LOD quality enhancement (2020) 0.01 
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    Abstract
    The labor market is a system that is complex and difficult to manage. To overcome this challenge, the European Union has launched the ESCO project which is a language that aims to describe this labor market. In order to support the spread of this project, its dataset was presented as linked open data (LOD). Since LOD is usable and reusable, a set of conditions have to be met. First, LOD must be feasible and high quality. In addition, it must provide the user with the right answers, and it has to be built according to a clear and correct structure. This study investigates the LOD of ESCO, focusing on data quality and data structure. The former is evaluated through applying a set of SPARQL queries. This provides solutions to improve its quality via a set of rules built in first order logic. This process was conducted based on a new proposed ESCO ontology.
  7. Folsom, S.M.: Using the Program for Cooperative Cataloging's past and present to project a Linked Data future (2020) 0.01 
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  8. Hider, P.; Coe, M.: Academic disciplines in the context of library classification : mapping university faculty structures to the DDC and LCC schemes (2022) 0.01 
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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.
  9. Ahmed, M.; Mukhopadhyay, M.; Mukhopadhyay, P.: Automated knowledge organization : AI ML based subject indexing system for libraries (2023) 0.01 
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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.
    Source
    DESIDOC journal of library and information technology. 43(2023) no.1, S.45-54
  10. Naun, C.C.: Expanding the use of Linked Data value vocabularies in PCC cataloging (2020) 0.01 
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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.
  11. Schreur, P.E.: ¬The use of Linked Data and artificial intelligence as key elements in the transformation of technical services (2020) 0.01 
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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.
  12. Steeg, F.; Pohl, A.: ¬Ein Protokoll für den Datenabgleich im Web am Beispiel von OpenRefine und der Gemeinsamen Normdatei (GND) (2021) 0.00 
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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).

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