Escobar Esteban, María Pilar, Candela, Gustavo, Trujillo, Juan, Marco Such, Manuel, Peral, Jesús
Adding value to Linked Open Data using a multidimensional model approach based on the RDF Data Cube vocabulary
Computer Standards & Interfaces. 2020, 68: 103378. doi:10.1016/j.csi.2019.103378
URI: http://hdl.handle.net/10045/97097
DOI: 10.1016/j.csi.2019.103378
ISSN: 0920-5489 (Print)
Abstract: 
Most organisations using Open Data currently focus on data processing and analysis. However, although Open Data may be available online, these data are generally of poor quality, thus discouraging others from contributing to and reusing them. This paper describes an approach to publish statistical data from public repositories by using Semantic Web standards published by the W3C, such as RDF and SPARQL, in order to facilitate the analysis of multidimensional models. We have defined a framework based on the entire lifecycle of data publication including a novel step of Linked Open Data assessment and the use of external repositories as knowledge base for data enrichment. As a result, users are able to interact with the data generated according to the RDF Data Cube vocabulary, which makes it possible for general users to avoid the complexity of SPARQL when analysing data. The use case was applied to the Barcelona Open Data platform and revealed the benefits of the application of our approach, such as helping in the decision-making process.
Keywords:Linked Open Data, Multidimensional modelling, Conceptual modelling, RDF Data, Cube vocabulary, Semantic web, Big data
Elsevier
info:eu-repo/semantics/article