Title
Discovering and Analysing Ontological Models From Big RDF Data
Abstract
We are witnessing an increasing popularity of the Web of Data, which exposes a large variety of web sources that provide their data using RDF. Ontological models are used as the schema to organize this data. These models are usually shared by several communities and, to devise them, there is usually an agreement amongst those communities. As a result, it is common to have more than one ontological model to understand some RDF data; therefore, there might be a gap between the ontological models and the RDF data, which is not negligible in practice. In this article, the authors present a technique to automatically discover ontological models from raw RDF data. It is based on the intensive usage of a set of SPARQL 1.1 structural queries that are generic and independent from the RDF data. The final result of the authors' technique is an ontological model that is derived from the RDF data, and includes types and properties, subtypes, domains and ranges of properties and subproperties. The authors have conducted experiments with millions of triples that prove that their technique is suitable to deal with Big RDF Data. As far as they know, this is the first technique to discover such ontological models in the context of RDF data and the Web of Data.
Year
DOI
Venue
2015
10.4018/JDM.2015040104
J. Database Manag.
Keywords
Field
DocType
Linked Open Data,Ontological Models,RDF,SPARQL 1.1,Web of Data
Data mining,RDF query language,Information retrieval,Computer science,Cwm,Linked data,SPARQL,Simple Knowledge Organization System,RDF/XML,RDF Schema,RDF
Journal
Volume
Issue
ISSN
26
2
1063-8016
Citations 
PageRank 
References 
1
0.38
23
Authors
4
Name
Order
Citations
PageRank
Carlos R. Rivero111116.25
Inma Hernández27610.72
David Ruiz315220.62
Rafael Corchuelo438949.87