%0 Journal Article
%T Characterising RDF data sets
%A Claudio Guti¨¦rrez
%A Javier D Fern¨¢ndez
%A Miguel A Mart¨ªnez-Prieto
%A Pablo de la Fuente Redondo
%J Journal of Information Science
%@ 1741-6485
%D 2018
%R 10.1177/0165551516677945
%X The publication of semantic web data, commonly represented in Resource Description Framework (RDF), has experienced outstanding growth over the last few years. Data from all fields of knowledge are shared publicly and interconnected in active initiatives such as Linked Open Data. However, despite the increasing availability of applications managing large-scale RDF information such as RDF stores and reasoning tools, little attention has been given to the structural features emerging in real-world RDF data. Our work addresses this issue by proposing specific metrics to characterise RDF data. We specifically focus on revealing the redundancy of each data set, as well as common structural patterns. We evaluate the proposed metrics on several data sets, which cover a wide range of designs and models. Our findings provide a basis for more efficient RDF data structures, indexes and compressors
%K Linked data
%K RDF features
%K RDF metrics
%K RDF structure
%U https://journals.sagepub.com/doi/full/10.1177/0165551516677945