Conceptual Aspects: How Landmarks Can Be Described in Data Models - Landmarks: GIScience for Intelligent Services - page 118

The property of landmarkness can also be mapped on a list of landmarks, by
calling all entities that have some landmarkness under a given context a landmark :
class Landmarks e where
collect :: [e] -> Cid - > [e]
instance Landmarks Entity where
collect el c =
[e|e < - el, hasLns e c ]
Also, with access to the geometric description of entities in the spatial database,
an operation can be defined to select all context-related landmarks within an area of
interest, for example within a buffer zone around a route.
With some more effort such an operator can even be extended for lifting
the landmarkness property from entities to types. For example, if all entities
of a type turn out to have some landmarkness then the type could be said to
have landmarkness. Accordingly, one of the fuzzy membership functions we will
introduce in the next section is based on type landmarkness, generalizing instance
properties of landmarkness.
Admittedly some properties of landmarks that we had discussed in the previous
chapter are not yet captured in this formal model: hierarchies of salience, hierarchies
of spatial granularities, and qualitative spatial relations in some flexible spatial
frames of reference. The reason why these (necessary) properties are not put into the
model here is that they are expected to appear from the general structure of a spatial
database in their current forms. Entities in spatial databases have a type, a thematic
description, and a geometric description in a spatial frame of reference [ 40 ] . The
database itself comes with a taxonomy. Especially for integration of different
databases, where taxonomies typically clash, taxonomies can be created in an ad-
hoc manner, for example based on similarity computed from affordance [ 29 , 30 ] .
Taxonomies of entity types provide a specialization hierarchy, or an is-a hierarchy .
Specialization, especially when described by affordance, will be a key of context-
dependent choice of landmarks, in addition to our formal model's capacity to
assign different landmarkness measures to each entity depending on context.
Some methods of landmark identification are solely type-based (see Chap. 5 ) .
Hierarchies of spatial granularity ( part-of or containment hierarchies) are expected
to result from the geometric description of the entities. And qualitative spatial
relations between landmarks, or relata, are intertwined with the selection process of
landmarks (Chap. 6 ) , which use either the geometric descriptions of entities again,
or use one of the qualitative spatial calculi [ 62 ] . Thus, the presented model should
be sufficient so far.