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. © 2012 Springer-Verlag.

Enhancing coverage and expressive power of spatial data warehousing modeling: The SDWM approach

Cuzzocrea Alfredo;
2012

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. © 2012 Springer-Verlag.
2012
Inglese
Data Warehousing and Knowledge Discovery - 14th International Conference, DaWaK 2012, Vienna, Austria, September 3-6, 2012. Proceedings
DAWAK 2012
7448 LNCS
15
29
9783642325830
http://www.scopus.com/record/display.url?eid=2-s2.0-84866685316&origin=inward
Sì, ma tipo non specificato
Data Models
Spatial Data Warehouses
Spatial Databases
1
none
Cuzzocrea, Alfredo; Do, Robson
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/281182
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