Conceptual Aspects: How Landmarks Can Be Described in Data Models - Landmarks: GIScience for Intelligent Services - page 110

4.2 Towards a Landmark Model

In order to capture the semantics of landmarks in a formal, machine readable
format we take an ontological approach [ 21 ] . An ontology is “a formal, explicit
specification of a shared conceptualization” ([ 54 ] , p. 184). This definition only
slightly extends Gruber's most frequently cited one by adding 'explicit' [ 20 ] .
Traditional ontological engineering chooses a first order language to produce
explicit specifications (e.g., [ 16 , 19 ] ). Instead we choose a second order language.
Second order languages were propagated by Frank and Kuhn for specifying formal
semantics of geographic concepts (e.g., [ 11 , 12 , 14 , 15 ] ) roughly in parallel to the
emergence of ontological engineering in computer science.
A second order language permits an algebraic approach to specifying a formal
model of landmarks. The presented algebra, however, will stay incomplete. The
purpose of this advance lies solely in a least ambiguous language to share formal
concepts. The algebra stays incomplete by skipping some details (in particular, as
mentioned, on modelling context), but also as it does not link to other, especially
upper level ontologies. In this regard the hypernyms listed in Sect. 1.1 would have
potential for further development [ 16 ] . Thus, the formal code can also be understood
as groundwork for future completion. In principle such a specification is executable
and can be tested for consistency.

4.2.1 Properties

Before the model (a formal, explicit specification in a machine readable format) can
be presented and discussed let us consider the properties of object s 2 a landmark

model must be able to reflect.
If landmarks are not a type, but a property, then any entity in the spatial database
(any instance of any type) will have to have this property to some degree, or to some
level of agreement. Considerations for this landmarkness are:

￿ There will be objects represented in the database that everybody will experience

as so outstanding in the environment that this experience is linked with the
location and stored in mental spatial representations.

￿ There will also be objects represented in the database that have meaning only

for some people. They have landmarkness mostly for semantic reasons, such as
my home . The spatial database may or may not know about the semantics, just
like other people may know or not know where I live or work. In the mobile

2 Smith encourages ontology engineers to give up the fuzzy term concept (or conceptualization ).
Instead, “ontologies [...]should be understood as having as their subject matter not concepts, but
rather the universals and particulars which exist in reality and are captured in scientific laws” ( [ 52 ] ,
p. 73).