Observing LOD Using Equivalent Set Graphs: It Is Mostly Flat and Sparsely Linked

Luigi Asprino*, Wouter Beek, Paolo Ciancarini, Frank van Harmelen, Valentina Presutti

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

5 Downloads (Pure)


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.

Original languageEnglish
Title of host publicationThe Semantic Web – ISWC 2019
Subtitle of host publication18th International Semantic Web Conference, Auckland, New Zealand, October 26–30, 2019, Proceedings, Part 1
EditorsChiara Ghidini, Olaf Hartig, Maria Maleshkova, Vojtech Svátek, Isabel Cruz, Aidan Hogan, Jie Song, Maxime Lefrançois, Fabien Gandon
Number of pages18
ISBN (Electronic)9783030307936
ISBN (Print)9783030307929
Publication statusPublished - 2019
Event18th International Semantic Web Conference, ISWC 2019 - Auckland, New Zealand
Duration: 26 Oct 201930 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11778 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th International Semantic Web Conference, ISWC 2019
Country/TerritoryNew Zealand


  • Empirical semantics
  • Linked Open Data
  • Semantic Web


Dive into the research topics of 'Observing LOD Using Equivalent Set Graphs: It Is Mostly Flat and Sparsely Linked'. Together they form a unique fingerprint.

Cite this