Database Reference
In-Depth Information
A prominent domain where these problems become more and more appar-
ent and pressing is in the geosciences. Geospatial data, that is, data that is
spatially referenced to Earth, have become ubiquitous. This is primarily due to
major advancements in remote-sensing technology, surveying techniques, and
computer-based simulations. As an example, the satellites operated by NASA
and NOAA generate dozens of terabytes of imagery and derived data prod-
ucts per day, leading to one of the fastest growing repositories with petabytes
of science data. In the year 2003, NOAA already maintained about 1,300
databases containing more than 2,500 environmental variables.
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The diverse
types of geospatial data collected by federal and local governments as well as
organizations in industry and academia play a significant role in developing
mission-critical spatial data infrastructures.
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,
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The use of geospatial data obtained through observations and simulations
and their management in spatial data infrastructures have become essential in
many application domains. These include environmental monitoring, climate
research, disaster prevention, natural resource management, transportation,
and decision support at various levels of local and state governments. The
types of geospatial data considered in these domains come in a variety of
types. Common types include maps and imagery from air and space-borne
instruments, vector data describing geographic objects and features, outputs
from simulations, and numerous types of real-time sensor data. In particular,
the latter are an emerging data source, driven by large-scale environmental
observation networks such as those envisioned by NEON.
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With such a proliferation of a wide range of geospatial data repositories,
many of which are readily accessible through the Web, it is imperative to
achieve a high degree of interoperability among these systems as a prerequisite
to facilitating data-integration tasks. By realizing this objective, geospatial
data that is managed in specialized repositories in support of specific domains
and tasks can serve whole communities and scientists in different disciplines.
In this chapter, we present the current trends and technologies in support
of developing interoperable geospatial data sources and management archi-
tectures that
enable the e
cient sharing, use, and integration of physically
distributed and heterogeneous geospatial data collections
. Our primary focus is
on emerging technologies that facilitate true interoperability among geospatial
data repositories, such as the development and implementation of standards
for geospatial content and services promoted by the Open Geospatial Consor-
tium (OGC).
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A key concept underlying this approach is (geospatial) Web
services, which realize a standard way to interoperate with diverse geospa-
tial data management infrastructures and to access heterogeneous forms of
geospatial data in a uniform and transparent fashion.
Such type of interoperability, of course, is only one ingredient in effective
data-integration approaches. Compared with data-integration techniques for
traditional relational databases, there are several special properties pertinent
to geospatial data. For example, a complicating factor in integrating geospa-
tial data is the variety of formats in which the data is managed, ranging from
