Multidimensionality in Statistical, OLAP and Scientific Databases

Multidimensionality in Statistical, OLAP and Scientific Databases

Arie Shoshani (Lawrence Berkeley National Laboratory, USA)
Copyright: © 2003 |Pages: 23
DOI: 10.4018/978-1-59140-053-0.ch002
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Abstract

The term “multidimensional databases” refers to data that can be viewed conceptually in a multidimensional space, where each dimension represents some attributes of the data. Viewing data in this form is natural for many applications, yet the concepts are not treated in a uniform way in the database literature. In this chapter, we show the commonality of concepts between three database areas: statistical, OLAP, and scientific databases. We show that these domains have two main structural concepts: the cross-product space of the dimensions, and the classification hierarchy structure associated with each dimension. In the first part of this chapter we describe how these structures are sed to represent data in statistical and OLAP databases and how summarization operators can be applied to them. Further, we discuss how these structures can be extended to represent related information using federated database concepts. In the second part of the chapter we show that these concepts are common to many scientific database applications. In particular, we discuss the importance of supporting classification structures and the difficulty in representing them as tables in relational databases. We also discuss data structures to support multidimensional databases, emphasizing space-time representation, clustering in multidimensional space, indexing in multidimensional space, and supporting classification structures. We conclude by arguing that the concepts of multidimensionality and classification structures as well as the operation over them should be elevated to “first class” object types. These object types should be visible by the application user explicitly in the conceptual schemas as well as exposing them in the user interfaces.

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Table of Contents
Preface
Maurizio Rafanelli
Chapter 1
Basic Notions  (pages 1-45)
Maurizio Rafanelli
This chapter presents the basic notions regarding multidimensional (aggregate) databases by referring to different definitions given for them in the... Sample PDF
Basic Notions
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Chapter 2
Arie Shoshani
The term “multidimensional databases” refers to data that can be viewed conceptually in a multidimensional space, where each dimension represents... Sample PDF
Multidimensionality in Statistical, OLAP and Scientific Databases
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Chapter 3
Riccardo Torlone
A variety of multidimensional data models have recently been proposed by both academic and industry communities. but consensus on formalism or even... Sample PDF
Conceptual Multidimensional Models
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Chapter 4
Hierarchies  (pages 91-115)
Elaheh Pourabbas, Maurizio Rafanelli
In this chapter we will focus on the rules of aggregation hierarchies in analysis dimensions of a cube. We give an overview of the related works on... Sample PDF
Hierarchies
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Chapter 5
Maurizio Rafanelli
In this chapter the author proposes the different approaches for defining operators able to manipulate this multidimensional structure. In... Sample PDF
Operators for Multidimensional Aggregate Data
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Chapter 6
Alberto O. Mendelzon, Alejandro A. Vaisman
In spite of the obvious importance of time in data warehousing and OLAP, current commercial systems do not support tracking the history of a data... Sample PDF
Time in Multidimensional Databases
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Chapter 7
Mirek Riedewald, Divyakant Agrawal, Amr El Abbadi
Data cubes are ubiquitous tools in data warehousing, online analytical processing, and decision support applications. Based on a selection of... Sample PDF
Dynamic Multidimensional Data Cubes
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Chapter 8
Stefano Paraboschi, Giuseppe Sindoni, Elena Baralis, Ernst Teniente
This chapter presents materialized views in the context of multidimensional databases (MDDBs). A materialized view is a view whose content is... Sample PDF
Materialized Views in Multidimensional Databases
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Chapter 9
Leonardo Tininini
A powerful and easy-to-use querying environment is certainly one of the most important components in a multidimensional database, and its... Sample PDF
Querying Multidimensional Data
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Chapter 10
Cirtis E. Dyreson, Torben Bach Pedersen, Christian S. Jensen
While incomplete information is endemic to real-world data, current multidimensional data models are not engineered to manage incomplete information... Sample PDF
Incomplete Information in Multidimensional Databases
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Chapter 11
Francesco M. Malvestuto, Marina Moscarini
When answering queries that ask for summary statistics, the query-system of a multidimensional database should guard confidential data, that is, it... Sample PDF
Privacy in Multidimensional Databases
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Chapter 12
Andrea Cali, Domenico Lembo, Maurizio Lenzerini, Riccardo Rosati
While the main goal of a data warehouse is to provide support for data analysis and management’s decisions, a fundamental aspect in design of a data... Sample PDF
Source Integration for Data Warehousing
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Chapter 13
Elaheh Pourabbas
The purpose of this chapter is to create cooperation between geographic databases (GDBs) and multidimensional databases (MDDBs), which are... Sample PDF
Cooperation with Geographic Databases
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About the Authors