7
A Quality-enabled Spatial Integration System
Omar Boucelma, Mehdi Essid, and Yassine Lassoued
Universit´ e Paul C´ ezanne, Marseille (France)
7.1 Introduction
The proliferation of spatial data on the Internet is beginning to allow a much larger
audience to share data currently available in various geographical information systems (GIS). As spatial data increases in importance, many public and private organizations need to disseminate and have access to the latest data at a minimum (right)
cost and as fast as possible. In order to move to a real Web-based spatial data system,
we need to provide flexible and powerful GIS data integration solutions. Indeed, GIS
are highly heterogeneous: not only do they differ in their data representation, but they
also offer radically different query languages. The main problems resulting from data
integration are the data modeling (how to integrate different source schemas) and
their querying (how to answer correctly to the queries posed on the global schema).
The first issue addressed in this chapter is related to geographical data integration.
The second important issue we address in this chapter is spatial data quality. Indeed, data quality descriptions are crucial for the development of GIS, since they
play a central role in many fields: environmental hazards, risk prevention, and so
on. Note that quality is an issue for general purpose information systems (IS). As
an example, the IS research community has addressed several aspects such as data
cleaning [15], quality estimation [28], or quality assessment [33], to cite a few. The
GIS community has been very proactive in metadata quality modeling: several quality models have been suggested such as ISO/TC 211 [22], FGDC [13], IGN [11], or
more recently the ISO 19115 quality model [21].
In this chapter, we will describe how we tackled both issues and will present
our solution, that is a quality-enabled geographical integration system. The chapter
is organized as follows. We first discuss some related work in Sect. 7.2 then, in
Sect. 7.3, we present a motivating example that will be used all along this chapter.
In Sect. 7.4 we discuss the schema mapping process, while in Sect. 7.5 the query
rewriting process is detailed. Section 7.6 discusses the design of a quality-enabled
geographical mediator, and the processing of quality queries is described in Sect. 7.7.
Finally we conclude in Sect. 7.8.
A Quality-enabled Spatial Integration System
Omar Boucelma, Mehdi Essid, and Yassine Lassoued
Universit´ e Paul C´ ezanne, Marseille (France)
7.1 Introduction
The proliferation of spatial data on the Internet is beginning to allow a much larger
audience to share data currently available in various geographical information systems (GIS). As spatial data increases in importance, many public and private organizations need to disseminate and have access to the latest data at a minimum (right)
cost and as fast as possible. In order to move to a real Web-based spatial data system,
we need to provide flexible and powerful GIS data integration solutions. Indeed, GIS
are highly heterogeneous: not only do they differ in their data representation, but they
also offer radically different query languages. The main problems resulting from data
integration are the data modeling (how to integrate different source schemas) and
their querying (how to answer correctly to the queries posed on the global schema).
The first issue addressed in this chapter is related to geographical data integration.
The second important issue we address in this chapter is spatial data quality. Indeed, data quality descriptions are crucial for the development of GIS, since they
play a central role in many fields: environmental hazards, risk prevention, and so
on. Note that quality is an issue for general purpose information systems (IS). As
an example, the IS research community has addressed several aspects such as data
cleaning [15], quality estimation [28], or quality assessment [33], to cite a few. The
GIS community has been very proactive in metadata quality modeling: several quality models have been suggested such as ISO/TC 211 [22], FGDC [13], IGN [11], or
more recently the ISO 19115 quality model [21].
In this chapter, we will describe how we tackled both issues and will present
our solution, that is a quality-enabled geographical integration system. The chapter
is organized as follows. We first discuss some related work in Sect. 7.2 then, in
Sect. 7.3, we present a motivating example that will be used all along this chapter.
In Sect. 7.4 we discuss the schema mapping process, while in Sect. 7.5 the query
rewriting process is detailed. Section 7.6 discusses the design of a quality-enabled
geographical mediator, and the processing of quality queries is described in Sect. 7.7.
Finally we conclude in Sect. 7.8.