Enabling Spatial OLAP Over Environmental and Farming Data with QB4SOLAP

  • Nurefşan GürEmail author
  • Katja Hose
  • Torben Bach Pedersen
  • Esteban Zimányi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10055)


Governmental organizations and agencies have been making large amounts of spatial data available on the Semantic Web (SW). However, we still lack efficient techniques for analyzing such large amounts of data as we know them from relational database systems, e.g., multidimensional (MD) data warehouses and On-line Analytical Processing (OLAP). A basic prerequisite to enable such advanced analytics is a well-defined schema, which can be defined using the QB4SOLAP vocabulary that provides sufficient context for spatial OLAP (SOLAP). In this paper, we address the challenging problem of MD querying with SOLAP operations on the SW by applying QB4SOLAP to a non-trivial spatial use case based on real-world open governmental data sets across various spatial domains. We describe the process of combining, interpreting, and publishing disparate spatial data sets as a spatial data cube on the SW and show how to query it with SOLAP operators.


Spatial Data Data Cube SPARQL Query Link Open Data Livestock Unit 
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.



This research is partially funded by “The Erasmus Mundus Joint Doctorate in Information Technologies for Business Intelligence Doctoral College (IT4BI-DC)”.


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Nurefşan Gür
    • 1
    Email author
  • Katja Hose
    • 1
  • Torben Bach Pedersen
    • 1
  • Esteban Zimányi
    • 2
  1. 1.Department of Computer ScienceAalborg UniversityAalborgDenmark
  2. 2.Department of Computer and Decision EngineeringUniversité Libre de BruxellesBruxellesBelgium

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