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.
;
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.
2019
The Semantic Web – ISWC
57
74
Asprino L.; Beek W.; Ciancarini P.; van Harmelen F.; Presutti V.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/722907
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