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      Evaluating the quality of linked open data in digital libraries

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          Abstract

          Cultural heritage institutions have recently started to share their metadata as Linked Open Data (LOD) in order to disseminate and enrich them. The publication of large bibliographic data sets as LOD is a challenge that requires the design and implementation of custom methods for the transformation, management, querying and enrichment of the data. In this report, the methodology defined by previous research for the evaluation of the quality of LOD is analysed and adapted to the specific case of Resource Description Framework (RDF) triples containing standard bibliographic information. The specified quality measures are reported in the case of four highly relevant libraries.

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          • Record: found
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          DBpedia: A Nucleus for a Web of Open Data

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            Beyond Accuracy: What Data Quality Means to Data Consumers

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              Data quality assessment

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                Author and article information

                Contributors
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                (View ORCID Profile)
                Journal
                Journal of Information Science
                Journal of Information Science
                SAGE Publications
                0165-5515
                1741-6485
                February 2022
                August 03 2020
                February 2022
                : 48
                : 1
                : 21-43
                Affiliations
                [1 ]Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Spain
                Article
                10.1177/0165551520930951
                f9c579b3-8269-45c9-8c14-4e6fe1733011
                © 2022

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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