Evaluation of metadata representations in RDF stores

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, Johannes^{a; *} | Müller, Kay^a | Hellmann, Sebastian^a | Rahm, Erhard^b | Vidal, Maria-Esther^c

Affiliations: [a] AKSW/KILT Competence Center, InfAI, Leipzig University & DBpedia Association, Germany. E-mails: [email protected], [email protected], [email protected]; URL: http://aksw.org/Groups/KILT.html | [b] Database group, Leipzig University, Germany. E-mail: [email protected]; URL: http://dbs.uni-leipzig.de | [c] TIB Leibniz Information Centre for Science and Technology & Fraunhofer IAIS, Germany. E-mail: [email protected]; URL: https://www.tib.eu/en/research-development/scientific-data-management/staff/

Correspondence: [*] Corresponding author. E-mail: [email protected].

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