Modeling and Querying Data Warehouses on the Semantic Web Using QB4OLAP

  • Lorena Etcheverry
  • Alejandro Vaisman
  • Esteban Zimányi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8646)


The web is changing the way in which data warehouses are designed and exploited. Nowadays, for many data analysis tasks, data contained in a conventional data warehouse may not suffice, and external data sources, like the web, can provide useful multidimensional information. Also, large repositories of semantically annotated data are becoming available on the web, opening new opportunities for enhancing current decision-support systems. Representation of multidimensional data via semantic web standards is crucial to achieve such goal. In this paper we extend the QB4OLAP RDF vocabulary to represent balanced, recursive, and ragged hierarchies. We also present a set of rules to obtain a QB4OLAP representation of a conceptual multidimensional model, and a procedure to populate the result from a relational implementation of the multidimensional model. We conclude the paper showing how complex real-world OLAP queries expressed in SPARQL can be posed to the resulting QB4OLAP model.


Resource Description Framework Data Cube SPARQL Query Resource Description Framework Data Resource Description Framework Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Lorena Etcheverry
    • 1
  • Alejandro Vaisman
    • 2
  • Esteban Zimányi
    • 3
  1. 1.Universidad de la RepúblicaUruguay
  2. 2.Instituto Tecnológico de Buenos AiresArgentina
  3. 3.Université Libre de BruxellesBelgium

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