Discovering and Analysing Ontological Models from Big RDF Data

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 understan...

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Detalles Bibliográficos
Autores: Rivero, Carlos R., Hernández Salmerón, Inmaculada Concepción, Ruiz Cortés, David, Corchuelo Gil, Rafael
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2015
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/105068
Acceso en línea:https://hdl.handle.net/11441/105068
https://doi.org/10.4018/JDM.2015040104
Access Level:acceso abierto
Palabra clave:Ontological models
Web of Data
RDF
SPARQL 1.1
Descripción
Sumario: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 article, 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 subproperties. Our experiments with millions of triples prove that our technique is suitable to deal with Big RDF Data. 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.