Adding value to Linked Open Data using a multidimensional model approach based on the RDF Data Cube vocabulary
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http://hdl.handle.net/10045/97097
Título: | Adding value to Linked Open Data using a multidimensional model approach based on the RDF Data Cube vocabulary |
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Autor/es: | Escobar Esteban, María Pilar | Candela, Gustavo | Trujillo, Juan | Marco Such, Manuel | Peral, Jesús |
Grupo/s de investigación o GITE: | Lucentia | Transducens |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos |
Palabras clave: | Linked Open Data | Multidimensional modelling | Conceptual modelling | RDF Data | Cube vocabulary | Semantic web | Big data |
Área/s de conocimiento: | Lenguajes y Sistemas Informáticos |
Fecha de publicación: | feb-2020 |
Editor: | Elsevier |
Cita bibliográfica: | Computer Standards & Interfaces. 2020, 68: 103378. doi:10.1016/j.csi.2019.103378 |
Resumen: | 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. |
Patrocinador/es: | This work was supported in part by the Spanish Ministry of Science, Innovation and Universities through the Project ECLIPSE-UA under grant RTI2018-094283-B-C32. |
URI: | http://hdl.handle.net/10045/97097 |
ISSN: | 0920-5489 (Print) | 1872-7018 (Online) |
DOI: | 10.1016/j.csi.2019.103378 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2019 Elsevier B.V. |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1016/j.csi.2019.103378 |
Aparece en las colecciones: | INV - TRANSDUCENS - Artículos de Revistas INV - LUCENTIA - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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2020_Escobar_etal_CompStandInterfaces_final.pdf | Versión final (acceso restringido) | 3,36 MB | Adobe PDF | Abrir Solicitar una copia |
2020_Escobar_etal_CompStandInterfaces_preprint.pdf | Preprint (acceso abierto) | 736,28 kB | Adobe PDF | Abrir Vista previa |
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