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Towards Semantic Assessment of Summarizability in Self-service Business Intelligence

  • Luis-Daniel Ibáñez
  • Jose-Norberto MazónEmail author
  • Elena Simperl
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 767)

Abstract

Traditional Business Intelligence solutions allow decision makers to query multidimensional data cubes by using OLAP tools, thus ensuring summarizability, which refers to the possibility of accurately computing aggregation of measures along dimensions. With the advent of the Web of Open Data, new external sources have been used in Self-service Business Intelligence for acquiring more insights through ad-hoc multidimensional open data cubes. However, as these data cubes rely upon unknown external data, decision makers are likely to make meaningless queries that lead to summarizability problems. To overcome this problem, in this paper, we propose a framework that automatically extracts multidimensional elements from SPARQL query logs and creates a knowledge base to detect semantic correctness of summarizability.

Keywords

OLAP Data cube Summarizability Open data 

Notes

Acknowledgments

Jose-Norberto Mazón is funded by grant number JC2015-00284 under “José Castillejo” research program from Spanish Government (Ministerio de Educación, Cultura y Deporte en el marco del Programa Estatal de Promoción del Talento y su Empleabilidad en I+D+i, Subprograma Estatal de Movilidad, del Plan Estatal de Investigación Científica y Técnica y de Innovación 2013–2016). This work is also funded by research project TIN2016-78103-C2-2-R from Spanish Government (Ministerio de Economía, Industria y Competitividad).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Luis-Daniel Ibáñez
    • 1
  • Jose-Norberto Mazón
    • 2
    Email author
  • Elena Simperl
    • 1
  1. 1.University of SouthamptonSouthamptonUK
  2. 2.DLSIUniversidad de AlicanteAlicanteSpain

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