Abstract
This paper proposes a novel perspective of research on the challenging issue of modeling Spatial Data Warehouses (SDW) that nicely contributes to improve state-of-the-art proposals. This conveys in the so-called Spatial Data Warehouse Metamodel (SDWM) that allow us to enhance both coverage and expressive power of SDW modeling by means of the following amenities: (i) separating the conceptual SDW modeling from the conceptual (spatial) OLAP modeling; (ii) supporting the modeling of complex constructs in SDW; and (iii) stereotyping attributes and measures as spatial objects directly. All these contributions finally depict a novel perspective of research in the investigated scientific field, which breaks the actual trend of state-of-the-art initiatives, by pinpointing their limitations. We complete our analytical contribution by means of a real-life application implemented via SDWM, which highlights the benefits deriving from applying SDWM in contrast with traditional SDW modeling methodologies.
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Cuzzocrea, A., do N. Fidalgo, R. (2012). Enhancing Coverage and Expressive Power of Spatial Data Warehousing Modeling: The SDWM Approach. In: Cuzzocrea, A., Dayal, U. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2012. Lecture Notes in Computer Science, vol 7448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32584-7_2
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DOI: https://doi.org/10.1007/978-3-642-32584-7_2
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