2. Heterogeneity in Distributed GISs 
[Worboys, M., et al., 1991] classified semantic heterogeneity as generic and contextual. The earlier occurs 
when different GIS applications are using different generic models of the spatial information. For example 
one may use a layer-based approach and a second may use an object-based approach. The contextual 
heterogeneity occurs when the semantics of schemes depend upon the local conditions at particular GISs. 
For example two spatial databases holding two different objects that have two different meanings, though 
they refer to the same real world entity, e.g., agricultural fields in environmental database is different from 
that in a cadastral database. [Spaccapietra, S., et al., 1991] listed 4 classes of heterogeneity or conflicts: 
semantic conflict, descriptive conflict, data model conflict, and structural conflict. The semantic conflict 
occurs in the situation where set of objects from two schemes are representing sets of real world entities 
which are related by a set comparison operators other than equality. Descriptive conflict occurs when two 
database objects, representing the same real world entities, are described with different sets of properties. 
Data model conflict is the situation where two schemes are defined with different data models, e.g., 
relational and object oriented models. The situation where two related objects are represented using 
different data structures is called structural conflict. For example a designer represents a component X of 
an object O either by creating a new object type X or add it as a property of O. 
A relatively similar classification of types of database heterogeneity was presented by [Saltor et al., 1993]. 
They provided more comprehensive classification of heterogeneity to which we are more inclined. Their 
classification has three aspects: syntactic, schematic, and semantic. Descriptive and structural conflicts are 
equivalent to schematic heterogeneity, while the data model conflict is equivalent to syntactic conflict. 
1. Syntactic: each database may be implemented in a different DBMS with a different data model, e.g., 
relational model Vs object oriented model. Moreover, syntactic heterogeneity is also related to the 
geometric representation of geographic objects, e.g., raster and vector representations. 
2. Schematic: where objects in one database are considered as properties or metadata in the other, or 
object classes of the same real world entity have different hierarchies and descriptors in different 
databases. 
3. Semantic: a real world entity may have two different meanings in their underlying databases in order to 
serve various applications, giving as a consequence semantic conflicts. For example a road network in 
a GIS for transportation has different semantics from that in a GIS for topographic mapping. 
3. Heterogeneity And Spatial Objects 
Geographic object representation in a GIS contains both thematic and geometric information. For most 
applications the thematic information of terrain description and analysis are of prime importance. This 
means that the querying and processing will be organized and formulated primarily from a thematic 
perspective. The structuring and formulation of the analysis of the geometric aspects of the data will be 
secondary [Molenaar, M. 1995]. This statement leads to two important conclusions. Firstly, object 
identification in a heterogeneous database environment should not rely on its geometric representation. 
Secondly, resolving the geometric discrepancies between different GIS has to be solved independently 
from the thematic ones. 
There are two approaches for geographic object representation in GIS: 1) field approach in which the earth 
surface is presented as spatio-temporal continuum; 2) object-structured planar graph approach in which 
terrain features are defined by their geometry, shape and position (in addition to thematic descriptors). In 
addition to the above three types of heterogeneity, mentioned in section 2, there is also spatial