Information Technology Reference
In-Depth Information
The results of the evaluation confirm that most of the programs achieved satisfactory basic
cartographic functions. Nine programs achieved more than 50 from the maximum possible
score (100%). Tested programs were ArcGIS, MapInfo, Geomedia, GRASS, TopoL,
AutoCAD Map, Kristýna GIS, MISYS and OCAD. Commercial programs are among the best
because they are being developed for a long time, and thus have the chance to meet the
requirements of expert cartographic outputs. The ArcGIS program was the bets in
evaluation.
Evaluation of programs also revealed some weak or missing cartographic functions. They
are missing of some compound line (motivated line) and point symbol in symbol libraries.
Programs also have insufficiencies in creating point and area diagram map (chart diagrams).
Multi-parameters totalizing diagrams, comparative diagrams and dynamic diagrams are
missing. Cartograms methods (anamorphosis) are very seldom implemented.
Functionality of setting colours is acceptable. It is possible to select the color from a palette
in different color models (RGB, HSV). Some color schemes (ramps) are, however, missing, in
particular bipolar, gradation or hypsometric color schemes. Possibility to create, save and re-
use custom color schemes is very rare.
GIS software is not only aimed for creation of cartographic outputs. Cartographic outputs
are in the end of GIS analyses. The overlay analyses of spatial data (spatial clip, symmetrical
difference, spatial union etc.) bring new results and new spatial data e.g. for urban planning
(Dobesova, Krivka, 2011). Another example of spatial analysis is the field of the spreading of
diseases (Absalon, Slesak, 2011). The results of analyses are necessary correctly express in
the map. The process of analyzing and cartographic outputs can be automated by data flow
diagrams or by programming language (Dobesova, 2011 a, b).
4. Cartographical ontology
In fact, there is significant convergence of artificial intelligence and geographic information
systems recently (Vozenilek, 2009). Artificial Intelligence (AI) takes many forms such as
expert systems (ES), fuzzy logic, and neural networks (Ham, 1996). Two artificial
intelligence methods are widely used in GIS - artificial neural networks and fuzzy logic. The
position of cartographic expert system in computer science is on Fig. 5.
The development of intelligent (expert) system needs formalization of cartographical
knowledge for computers “to understand” the map making process. Humans understand
intuitively. On the contrary, computers need explicit coding. A design of ontology is way for
coding the formal cartographic knowledge. Ontology is a formal specification of a shared
understanding of a knowledge domain that facilitates accurate and effective communication
meaning (Gruber 1993).
Ontologies are defined for purposes of sharing and re-use of knowledge across information
systems. Specialized ontologies are aimed to design a common conceptual system -
thesaurus. Similarly, the cartographic ontology defines the basic conceptual system
(conceptualization) for the cartography. Cartographic concepts (classes) are formed as a
hierarchy of classes with simple constraints. The cartographic ontology had to capture also
the context and constraints of classes using description logic. The final target was not only
the creating of cartographical thesaurus but the usefulness of cartographic knowledge in the
