Spatial Data Warehouse Modelling

Spatial Data Warehouse Modelling

Maria Luisa Damiani (Università di Milano, Italy and Ecole Polytechnique Fédérale, Switzerland) and Stefano Spaccapietra (Ecole Polytechnique Fédérale de Lausanne, Switzerland)
DOI: 10.4018/978-1-60566-232-9.ch014
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This chapter is concerned with multidimensional data models for spatial data warehouses. Over the last few years different approaches have been proposed in the literature for modelling multidimensional data with geometric extent. Nevertheless, the definition of a comprehensive and formal data model is still a major research issue. The main contributions of the chapter are twofold: First, it draws a picture of the research area; second it introduces a novel spatial multidimensional data model for spatial objects with geometry (MuSD – multigranular spatial data warehouse). MuSD complies with current standards for spatial data modelling, augmented by data warehousing concepts such as spatial fact, spatial dimension and spatial measure. The novelty of the model is the representation of spatial measures at multiple levels of geometric granularity. Besides the representation concepts, the model includes a set of OLAP operators supporting the navigation across dimension and measure levels.
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A topic that over recent years has received growing attention from both academy and industry concerns the integration of spatial data management with multidimensional data analysis techniques. We refer to this technology as spatial data warehousing, and consider a spatial data warehouse to be a multidimensional database of spatial data. Following common practice, we use here the term spatial in the geographical sense, i.e., to denote data that includes the description of how objects and phenomena are located on the Earth. A large variety of data may be considered to be spatial, including: data for land use and socioeconomic analysis; digital imagery and geo-sensor data; location-based data acquired through GPS or other positioning devices; environmental phenomena. Such data are collected and possibly marketed by organizations such as public administrations, utilities and other private companies, environmental research centres and spatial data infrastructures. Spatial data warehousing has been recognized as a key technology in enabling the interactive analysis of spatial data sets for decision-making support (Rivest et al., 2001; Han et al., 2002). Application domains in which the technology can play an important role are, for example, those dealing with complex and worldwide phenomena such as homeland security, environmental monitoring and health safeguard. These applications pose challenging requirements for integration and usage of spatial data of different kinds, coverage and resolution, for which the spatial data warehouse technology may be extremely helpful.

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Editorial Advisory Board
Table of Contents
David Taniar
Chapter 1
Laila Niedrite, Maris Solodovnikova Treimanis, Liga Grundmane
There are many methods in the area of data warehousing to define requirements for the development of the most appropriate conceptual model of a data... Sample PDF
Development of Data Warehouse Conceptual Models: Method Engineering Approach
Chapter 2
Stefano Rizzi
In the context of data warehouse design, a basic role is played by conceptual modeling, that provides a higher level of abstraction in describing... Sample PDF
Conceptual Modeling Solutions for the Data Warehouse
Chapter 3
Hamid Haidarian Shahri
Entity resolution (also known as duplicate elimination) is an important part of the data cleaning process, especially in data integration and... Sample PDF
A Machine Learning Approach to Data Cleaning in Databases and Data Warehouses
Chapter 4
Maurizio Pighin, Lucio Ieronutti
Data Warehouses are increasingly used by commercial organizations to extract, from a huge amount of transactional data, concise information useful... Sample PDF
Interactive Quality-Oriented Data Warehouse Development
Chapter 5
Dirk Draheim, Oscar Mangisengi
Nowadays tracking data from activity checkpoints of unit transactions within an organization’s business processes becomes an important data resource... Sample PDF
Integrated Business and Production Process Data Warehousing
Chapter 6
Jorge Loureiro, Orlando Belo
OLAP queries are characterized by short answering times. Materialized cube views, a pre-aggregation and storage of group-by values, are one of the... Sample PDF
Selecting and Allocating Cubes in Multi-Node OLAP Systems: An Evolutionary Approach
Chapter 7
Jorge Loureiro, Orlando Belo
Globalization and market deregulation has increased business competition, which imposed OLAP data and technologies as one of the great enterprise’s... Sample PDF
Swarm Quant' Intelligence for Optimizing Multi-Node OLAP Systems
Chapter 8
Franck Ravat, Olivier Teste, Ronan Tournier
With the emergence of Semi-structured data format (such as XML), the storage of documents in centralised facilities appeared as a natural adaptation... Sample PDF
Multidimensional Anlaysis of XML Document Contents with OLAP Dimensions
Chapter 9
Hanene Ben-Abdallah, Jamel Feki, Mounira Ben Abdallah
Despite their strategic importance, the wide-spread usage of decision support systems remains limited by both the complexity of their design and the... Sample PDF
A Multidimensional Pattern Based Approach for the Design of Data Marts
Chapter 10
Concepción M. Gascueña, Rafael Guadalupe
The Multidimensional Databases (MDB) are used in the Decision Support Systems (DSS) and in Geographic Information Systems (GIS); the latter locates... Sample PDF
A Multidimensional Methodology with Support for Spatio-Temporal Multigranularity in the Conceptual and Logical Phases
Chapter 11
Francisco Araque, Alberto Salguero, Cecilia Delgado
One of the most complex issues of the integration and transformation interface is the case where there are multiple sources for a single data... Sample PDF
Methodology for Improving Data Warehouse Design using Data Sources Temporal Metadata
Chapter 12
Shi-Ming Huang, John Tait, Chun-Hao Su, Chih-Fong Tsai
Data warehousing is a popular technology, which aims at improving decision-making ability. As the result of an increasingly competitive environment... Sample PDF
Using Active Rules to Maintain Data Consistency in Data Warehouse Systems
Chapter 13
Marcin Gorawski, Wojciech Gebczyk
This chapter describes realization of distributed approach to continuous queries with kNN join processing in the spatial telemetric data warehouse.... Sample PDF
Distributed Approach to Continuous Queries with kNN Join Processing in Spatial Telemetric Data Warehouse
Chapter 14
Maria Luisa Damiani, Stefano Spaccapietra
This chapter is concerned with multidimensional data models for spatial data warehouses. Over the last few years different approaches have been... Sample PDF
Spatial Data Warehouse Modelling
Chapter 15
Jérôme Darmont
Performance evaluation is a key issue for designers and users of Database Management Systems (DBMSs). Performance is generally assessed with... Sample PDF
Data Warehouse Benchmarking with DWEB
Chapter 16
Lars Frank, Christian Frank
A Star Schema Data Warehouse looks like a star with a central, so-called fact table, in the middle, surrounded by so-called dimension tables with... Sample PDF
Analyses and Evaluation of Responses to Slowly Changing Dimensions in Data Warehouses
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