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Collective Cubing Platform towards Definition and Analysis of Warehouse Cubes

  • Duong Thi Anh Hoang
  • Ngoc Sy Ngo
  • Binh Thanh Nguyen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7654)

Abstract

Multidimensional data analysis, as supported by OLAP (online analytical processing), requires the computation of many aggregate functions over a large volume of historically collected data. Meanwhile, a recent trend in data communities has been the presence of dynamic, interdisciplinary data communities in which users can find and select data from a wide range of data providers. Using this approach, we have designed the Cubing service platform, which allows rapid retrieval of warehouse cubes in a way that would be familiar to any online shopper. In such an open marketplace, cubing services play a role as a metadata layer that maps cube definitions to the underlying schema and defines how the published cubes will be queried. The proposed platform couples an efficient cube selection mechanism with semantic reasoning capabilities, capable of processing large data sources, which expressed in a variety of formalisms, into a collection of warehouse datasets that expose the native metadata in a uniform manner. Thus, the platform is easily extensible and robust to updates of both data and metadata in the warehouse datasets.

Keywords

Data cube OLAP Open data Linked data 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Duong Thi Anh Hoang
    • 1
  • Ngoc Sy Ngo
    • 1
  • Binh Thanh Nguyen
    • 1
  1. 1.Information Technology CenterHue UniversityHueVietnam

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