Ontology is basically a formal
specification of conceptualization and that is shared. In semantic web ontology
consider as a major pillar the major reason for this is a sense of knowledge of
Ontology mapping can be define as the integration and
merging of ontology. Integration of ontology means that design a new ontology which
use again other available ontologies and merging of ontology means
collaboration of different ontologies into a single one make union of them.
Mapping of ontology is based on some factors which play a vital role. First of
all considering number of different properties of ontologies like as syntax,
semantics and structure. Even many researchers’ works in this area, ontology
mapping techniques are not still perfect and there is possibility for the improvement
in this. While the major purpose of the ontology mapping is allows different schemas or ontologies to
determine information that is same although it is based on different schematic
syntax or a structure. In this just discuss few of them.
ARTEMIS (Analysis and
Reconciliation Tool Environment for Multiple Information Sources).It is used to
manage the access as well as the availability of dynamic collections of the
data sources along this it also provide the supports of the creation of queries
step-by-step for user. The major aim of this is solving the problem of independent data stores.
According to (Castano
et al., 2001) it involves three key steps:
1. Analysis of
2. Clustering of
of global views
European Commission FP6 funded ARTEMIS Project and developed a framework
AMEF stands for Artemis Message Exchange Framework. It is used to provide the
meaningful information. The initial task of this is mapping of source ontology
into target message ontology through a mapping tool which produces a mapping
definition and then this used to convert the source ontology message into
target message automatically.
order to represent the matching between source and target classes based ontologies,
here defined four mapping mechanism which are:
classes that are indistinguishable and mapped through EquivalentTo mechanism
and SimilarTo mechanism involves that classes which have overlapping the
property mapping mechanism, similar classes are further related through their
data type properties and object. HL7 version 2 ontology is defined to be similar to HL7 version3
ontology. Using “ObjectPropertyTransform” mechanism to define the mapping of “hasValue”
and “hasQuantity” object properties. While “IntersectionOf” creates the
corresponding instances of the target class as the intersection of the declared
class instances and “UnionOf” is similar.
Using KIF “KnowledgeInterchangeFormat” to define the instances of the
source ontology that makes instances of the target ontology. OWLmt shows the
path of classes that are linked by the object properties in such a way that each
and every time a path defined in the source ontology means inputPath is
encountered in the source ontology instance, the path which is defined for
target ontology means outputPath is generated in the target ontology instance.
Paths can be define as triples in KIF format and executed through the
Assuming the path that is define in the source ontology
In the target ontology following path correspondence
OWLmt constructs the specified paths among the instances of the target
ontology in the execution step based on the paths defined among the instances
of the source ontology.
COMA stands for combined matching. Authors present
the COMA mapping technique in (Do and Rahm, 2001), this is a system for combining
different ontology mapping methods which is based on the different situation
and source schemas. In 2005 COMA++ was introduced in which re-implementation of
the original COMA design due to this improve performance, functionality and along
with this it also provides a GUI that simplifies the definition of match strategies.
In COMA Match Process