123859 20230706131755.0 doi 10.3233/SW-200368 sideral 131855 ART-2020-131855 eng Bobed, C. Universidad de Zaragoza (orcid)0000-0003-4239-8785 Data-driven assessment of structural evolution of RDF graphs 2020 Access copy available to the general public Unrestricted Since the birth of the Semantic Web, numerous knowledge bases have appeared. The applications that exploit them rely on the quality of their data through time. In this regard, one of the main dimensions of data quality is conformance to the expected usage of the vocabulary. However, the vocabulary usage (i.e., how classes and properties are actually populated) can vary from one base to another. Moreover, through time, such usage can evolve within a base and diverges from the previous practices. Methods have been proposed to follow the evolution of a knowledge base by the observation of the changes of their intentional schema (or ontology); however, they do not capture the evolution of their actual data, which can vary greatly in practice. In this paper, we propose a data-driven approach to assess the global evolution of vocabulary usage in large RDF graphs. Our proposal relies on two structural measures defined at different granularities (dataset vs update), which are based on pattern mining techniques. We have performed a thorough experimentation which shows that our approach is scalable, and can capture structural evolution through time of both synthetic (LUBM) and real knowledge bases (different snapshots and updates of DBpedia). info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Maillot, P. Cellier, P. Ferré, S. 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 11, 5 (2020), 831-853 Semantic Web 2210-4968 704675 http://zaguan.unizar.es/record/123859/files/texto_completo.pdf Postprint 2139420 http://zaguan.unizar.es/record/123859/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:123859 articulos driver 2023-07-06-12:25:27 ARTICLE