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Chapter 9
Multidimensional Data
Analysis Based on Links:
Models and Languages
ABSTRACT
Analytical processing (OLAP) tools typically only deal with relational data. Hence, the analytical pro-
cessing systems on XML data do not have all the functionality provided by OLAP tools to traditional data
(i.e. relational). In addition, current commercial and academic OLAP tools do not process XML data that
contains XLink. Therefore, there is a need to develop a solution for OLAP systems in order to assist in
the strategic analysis of the organizational data represented in XML format. Aiming at overcoming this
issue, this chapter proposes an analytical system composed by LMDQL (Link-Based Multidimensional
Query Language), an analytical query language; XLDM (XLink Data Metamodel), a metamodel given
to model cubes of XML documents with XLink and to deal with syntactic, semantic, and structural het-
erogeneities commonly found in XML documents; and XLPath (XLink Path Language), a navigation
language for XML documents connected by XLink. As current W3C query languages for navigating in
XML documents do not support XLink, XLPath is discussed in this chapter to provide features for the
LMDQL query processing and a prototype system enabling OLAP queries over XML documents linked
by XLink and XML schema. This prototype includes a driver, named sql2xquery, which performs the
mapping of SQL queries into XQuery in a relational OLAP server. In order to validate the proposed
system, a case study and its performance evaluation are presented to analyze the impact of analytical
processing over XML/XLink documents.
INTRODUCTION
The current software applications usually have
to deal with multiple sources and data formats.
To minimize this problem, XML - eXtensible
Markup Language (XML, 1998) was adopted as
a way to integrate the data into a standard format.
The use of XML as an alternative to integration
of heterogeneous data sources has become this
technology a de facto standard for data exchange
on the Internet. XML documents are a rich source
of information for organizational decision mak-
Paulo Caetano da Silva
Salvador University, Brazil
DOI: 10.4018/978-1-4666-6098-4.ch009