UML diagram for a point object following the ISO UML standard.
Courtesy of Michael Lutz.
number and street name). The second level requires that each value of a
record is dependent on the key value of the record (e.g., the name of the per-
son). In the third level, no fields depend on nonkey fields (e.g., a “years at
residence” field must be related to the name of the addressed person, not
the street number).
Data Modeling, Geographic Representation,
and Cartographic Representation
The consideration, inclusion, and representation of the complex spatiotemp-
oral relationships in a database pose a number of challenges that require a
thoroughgoing engagement with geographic representation and carto-
graphic representation. If David Sinton's matrix (see Chapter 2) provides a
means to conceptualize the observation, measurement, and storage of data
from a single geographic thing or event, the data modeling for a database
must consider multiple things and events as well as the relationships. In addi-
tion to these issues of geographic representation, data modeling takes carto-
graphic representation into account in varying degrees. The type of media,
the projection, the coordinate system, and symbolization all inf luence data-
modeling decisions. Relational database have several advantages for f lexibly
and reliability in addressing these issues. The relations between tables can
ref lect different relationships between things and events and multiple rela-
tionships, representations, and types of communication can be part of the
data model. Of course, challenges exist when developing new geographic
information when some geographic information already exists and when
geographic information from different sources should be combined.