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concerns itself with inland topographic mapping. The digital products produced by
such agencies can be roughly divided into four types:
Digital topographic maps, the modern equivalent of a paper map.
Gazetteers, geocoded lists of places and addresses. These are like indexes
to the landscape: They enable services to locate the position on Earth's sur-
face of a place or an address; conversely, someone can use them to find the
place or address at a particular location.
Terrain models. These are digital models of Earth's surface.
Photography and other sensor data such as Lidar-typically derived from
either aircraft or satellites.
These data form the basis for other organizations to build on by either adding
additional information or using the data to perform geographic analysis related to
their business, such as a retail chain using GI to work out ideal store locations or an
insurance company working out insurance risk for areas prone to flooding. Thus,
an important element of any modern mapping organization is to deliver data to its
customers in a form that is easy for the customers to accept and use. This need in
particular is why mapping organizations are one type of many organizations today
looking at Linked Data and the Semantic Web as better ways to perform their role.
1.5 CONVENTIONS USED IN THE TOPIC
The later chapters of this topic contain many examples, and to make these examples
easier to understand, we have used a number of conventions to represent the nature
of elements of these examples.
In diagrams, we have adopted the convention that concepts or classes (abstract
categories that real things can be placed into such as car, building, and river) as
rectangular boxes with rounded edges and instances or individuals (i.e., actual things
such as your car, the White House in Washington, and the Amazon River) as ellipses.
Relationships between classes and individuals are shown using directed arrows.
These conventions are shown in Figure 1.1 .
So, using these conventions we can say unambiguously that the White House
(an individual) is a Building (a class) and so on. The topic also illustrates points
using “code.” The code represents an example in one of a number of different com-
puter languages and syntaxes: RDF and RDFS using RDF/XML (eXtensible Markup
Language) and Turtle syntaxes and OWL using OWL/XML, Manchester Syntax,
and Rabbit. We have used different syntaxes because a number of different syn-
taxes currently exist, and there is no ideal for showing all the examples consistently:
RDF/XML and OWL/XML are able to express all the examples but are verbose and
difficult to understand, whereas Turtle, Manchester Syntax, and Rabbit are much
easier to understand but cannot express all the examples. As a general principle, we
have usually chosen to use the most understandable syntax. We have also adopted the
principle of showing Manchester Syntax and Rabbit side by side as although Rabbit
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