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Issue title: Special Issue on Benchmarking Linked Data
Guest editors: Axel-Cyrille Ngonga Ngomo, Irini Fundulaki and Anastasia Krithara
Article type: Research Article
Authors: Frey, Johannesa; * | Müller, Kaya | Hellmann, Sebastiana | Rahm, Erhardb | Vidal, Maria-Estherc
Affiliations: [a] AKSW/KILT Competence Center, InfAI, Leipzig University & DBpedia Association, Germany. E-mails: frey@informatik.uni-leipzig.de, kay.mueller@informatik.uni-leipzig.de, hellmann@informatik.uni-leipzig.de; URL: http://aksw.org/Groups/KILT.html | [b] Database group, Leipzig University, Germany. E-mail: rahm@informatik.uni-leipzig.de; URL: http://dbs.uni-leipzig.de | [c] TIB Leibniz Information Centre for Science and Technology & Fraunhofer IAIS, Germany. E-mail: Maria.Vidal@tib.eu; URL: https://www.tib.eu/en/research-development/scientific-data-management/staff/
Correspondence: [*] Corresponding author. E-mail: frey@informatik.uni-leipzig.de.
Abstract: The maintenance and use of metadata such as provenance and time-related information is of increasing importance in the Semantic Web, especially for Big Data applications that work on heterogeneous data from multiple sources and which require high data quality. In an RDF dataset, it is possible to store metadata alongside the actual RDF data and several possible metadata representation models have been proposed. However, there is still no in-depth comparative evaluation of the main representation alternatives on both the conceptual level and the implementation level using different graph backends. In order to help to close this gap, we introduce major use cases and requirements for storing and using diverse kinds of metadata. Based on these requirements, we perform a detailed comparison and benchmark study for different RDF-based metadata representations, including a new approach based on so-called companion properties. The benchmark evaluation considers two datasets and evaluates different representations for three popular RDF stores.
Keywords: Metadata, RDF, evaluation, reification
DOI: 10.3233/SW-180307
Journal: Semantic Web, vol. 10, no. 2, pp. 205-229, 2019
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