This paper presents an empirical study aiming at understanding the modeling style and the overall semantic structure of Linked Open Data. We observe how classes, properties and individuals are used in practice. We also investigate how hierarchies of concepts are structured, and how much they are linked. In addition to discussing the results, this paper contributes (i) a conceptual framework, including a set of metrics, which generalises over the observable constructs; (ii) an open source implementation that facilitates its application to other Linked Data knowledge graphs.
Observing LOD Using Equivalent Set Graphs: It Is Mostly Flat and Sparsely Linked / Asprino L.; Beek W.; Ciancarini P.; van Harmelen F.; Presutti V.. - ELETTRONICO. - 11778:(2019), pp. 57-74. (Intervento presentato al convegno 18th International Semantic Web Conference, ISWC 2019 tenutosi a nzl nel 2019) [10.1007/978-3-030-30793-6_4].
Observing LOD Using Equivalent Set Graphs: It Is Mostly Flat and Sparsely Linked
Asprino L.
;Ciancarini P.
;Presutti V.
Supervision
2019
Abstract
This paper presents an empirical study aiming at understanding the modeling style and the overall semantic structure of Linked Open Data. We observe how classes, properties and individuals are used in practice. We also investigate how hierarchies of concepts are structured, and how much they are linked. In addition to discussing the results, this paper contributes (i) a conceptual framework, including a set of metrics, which generalises over the observable constructs; (ii) an open source implementation that facilitates its application to other Linked Data knowledge graphs.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.