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enabling performance-oriented environments. Nevertheless, the creation of
standards and methodologies for the creation of web-enabled open-source
systems in the geographical sciences remains an active research area [7, 17].
From an industrial perspective, Esri, a leading GIS vendor, has produced
a case study for its own proprietary software without much to say on how
to take advantage of platform as a service/software as a service (PaaS/SaaS)
for building GIS in an open, generic way [6]. GIS Cloud Limited seems to be
the only platform provider for building GIS in the cloud [9], but one can only
build using their application programming interface (API) and supported
tools and languages.
Arguably, additional research needs to be devoted to the efficient use of
Cloud-enabled GISs to develop specific applications quickly using off-the-shelf
components such as public maps and web services. Such a need has been
recently highlighted by different authors as part of the emerging trends in
interdisciplinary geographic processing on clouds [12, 13, 18].
RESEARCH GAP
It is therefore clear that there is a research gap in this area and the meth-
odology proposed in the topic chapter can be used to build GISs in the
cloud, on either infrastructure as a service (IaaS) or PaaS using map
services such as Bing Maps and Google Maps and deploying through
the use of software patterns. The remainder of this chapter provides a
systematic way to assemble a GIS in the cloud using public Cloud pro-
viders and off-the-shelf components that follow accepted best practices
in software engineering.
7.3 Methodology
The key elements required to build a typical web-based GIS are as follows:
• a database management system (DBMS);
• base maps;
• a web server with some storage, high-speed network connection
between the machines; and
• a secured Internet connection to provide service over the Internet.
Additional elements can be added, such as a mechanism to reduce failures
(e.g., replication servers or storage disk mirrors), load-balancing systems, and
a backup mechanism.
The DBMS ought to support geospatial data types, allow spatial indexes,
and perform various operations on geospatial data using built-in functions.
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