The Linked Data Principles defined by Tim-Berners Lee promise that a large portion of Web Data will be usable as one big interlinked RDF database. Today, with more than one thousand of Linked Open Data (LOD) sources available on the Web, we are assisting to an emerging trend in publication and consumption of LOD datasets. However, the pervasive use of external resources together with a deficiency in the definition of the internal structure of a dataset causes many LOD sources are extremely complex to understand. In this paper, we describe a formal method to unveil the implicit structure of a LOD dataset by building a (Clustered) Schema Summary. The Schema Summary contains all the main classes and properties used within the datasets, whether they are taken from external vocabularies or not, and is conceivable as an RDFS ontology. The Clustered Schema Summary, suitable for large LOD datasets, provides a more high level view of the classes and the properties used by gathering together classes that are object of multiple instantiations.

Exposing the Underlying Schema of LOD Sources / Benedetti, Fabio; Bergamaschi, Sonia; Po, Laura. - 1:(2016), pp. 301-304. (Intervento presentato al convegno International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM tenutosi a Singapore nel 6-9 December 2015) [10.1109/WI-IAT.2015.99].

Exposing the Underlying Schema of LOD Sources

BENEDETTI, FABIO;BERGAMASCHI, Sonia;PO, Laura
2016

Abstract

The Linked Data Principles defined by Tim-Berners Lee promise that a large portion of Web Data will be usable as one big interlinked RDF database. Today, with more than one thousand of Linked Open Data (LOD) sources available on the Web, we are assisting to an emerging trend in publication and consumption of LOD datasets. However, the pervasive use of external resources together with a deficiency in the definition of the internal structure of a dataset causes many LOD sources are extremely complex to understand. In this paper, we describe a formal method to unveil the implicit structure of a LOD dataset by building a (Clustered) Schema Summary. The Schema Summary contains all the main classes and properties used within the datasets, whether they are taken from external vocabularies or not, and is conceivable as an RDFS ontology. The Clustered Schema Summary, suitable for large LOD datasets, provides a more high level view of the classes and the properties used by gathering together classes that are object of multiple instantiations.
2016
2015
International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM
Singapore
6-9 December 2015
1
301
304
Benedetti, Fabio; Bergamaschi, Sonia; Po, Laura
Exposing the Underlying Schema of LOD Sources / Benedetti, Fabio; Bergamaschi, Sonia; Po, Laura. - 1:(2016), pp. 301-304. (Intervento presentato al convegno International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM tenutosi a Singapore nel 6-9 December 2015) [10.1109/WI-IAT.2015.99].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1082937
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