Towards Discovering Ontological Models from Big RDF Data

Abstract

The Web of Data, which comprises web sources that provide their data in RDF, is gaining popularity day after day. Ontological models over RDF data are shared and developed with the consensus of one or more communities. In this context, there usually exist more than one ontological model to understand RDF data, therefore, there might be a gap between the models and the data, which is not negligible in practice. In this paper, we present a technique to automatically discover ontological models from raw RDF data. It relies on a set of SPARQL 1.1 structural queries that are generic and independent from the RDF data. The output of our technique is a model that is derived from these data and includes the types and properties, subtypes, domains and ranges of properties, and minimum cardinalities of these properties. Our technique is suitable to deal with Big RDF Data since our experiments focus on millions of RDF triples, i.e., RDF data from DBpedia 3.2 and BBC. As far as we know, this is the first technique to discover such ontological models in the context of RDF data and the Web of Data.