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Oct 21, 2013 (4 years and 8 months ago)





International Journal of Science, Engineering and Technology Research (IJSETR)

Volume 2, I
ssue 1, January 2013


All Rights
Reserved © 2013 IJSETR


Ontology is an emerging term which is used to
share the common understanding of information structure.
This information’s can be shared and reused among people
and software agents and it is mainly developed to enable the
reuse of domain know
ledge. By reusing we can save the effort
and we can interact with the tools that use other ontology.
Ontology mapping is a technique which is used to map
different ontologies or schemas to each other in order to
determine that the information available in
ontologies is
similar even though the syntax or structure is different. In
order to achieve Semantic interoperability ontology matching
is used. Ontology matching is performed at compile time and
the resulting ontology alignment is applied in design time a
run time.

Index Terms

Ontology, Ontology Mapping, Ontology



Ontology is defined as a study of grouping of things that
exist or may not exist in some domain. The product of such
study is called as ontology and it will li
st the types of things
that are assumed to exist in a domain of interest from the
view of person who uses some language for the purpose of
domain. Ontology is a set


concept definitions and it
represents the concepts, relations, predicates, word sense
s or
relation types of language for the given domain. Ontology is
defied as a formal representation of concepts within a
domain and it will express the relationship which exists in
the domain. It is used to describe the properties of domain
and it also def
ine the domain. An informal ontology is
specified by a catalog of types that are either defined or
undefined by using natural languages. A formal ontology is
specified by collection of names for concept and relation
types organized in a partial ordering b
y the type

relation. Ontologies are used in several applications such as
Semantic Web, Software Engineering, Biomedical
Informatics, Library Sciences and Artificial Intelligence.
There are different types of ontologies and they are
categorized ac
cording to their granularity, formality,
generality and computational capability.

Ontology Mapping is a technique which is used to amp
different ontologies or schema's to each other in order to
determine that the information available in ontologies are
milar even though the syntax or structure is different. It is
done by analyzing various attributes such as syntax,

Manuscript received Jan 5 , 2013

Thanga Uma.EL
, ME Software Engineering,SN
S College of
Coimbatore, Tamil Nadu.

NS Col
lege of
,Coimbatore, Tamil Nadu.

NS College of Technology
Tamil Nadu.

semantic and structure. An ontology is defined as a pair
OM= (OS, OA), where OS is an Ontology Signature and

OA is the ontology Axiom, thes
e specify the intended
interpretation of a particular domain.


is a family of World Wide Web Consortium
designed as a meta data model. It is a method used to
provide the description or modeling of information that is
implemented in web resources by usi
ng different syntax. It
is mainly used to define the structure of data. This model is
similar to entity relationship or class diagram which
provides detailed description of an entity. the RDF is also
known as a triples because it expresses the resources in

form of subject


object. the design of RDF
contains a simple data model, formal semantics, provable
inference, extensible URI based vocabulary and XML based


Semantic Web is a large environment and it allows the

to be shared and reused between applications. A single
ontology is no longer enough to support the tasks predicted
by a distributed environment. In order to achieve inter
interoperability between different ontologies ontology
mapping is developed.

ra and G.Aghila [3] describes a method to find the
similarity between various ontologies through the
component concepts, relation, attributes and values by using
various patterns. By using these patterns, the errors can be
reduced and it will make the mapp
ing more concise and
understandable. Different mapping patterns are constructed
for ontology mapping such as concept
concept, attribute

attribute, attribute relation and relation attribute, concept
relation and relation concept, concept value and value
oncept, relation value and value relation [3].Here the
author considered the concept

concept mapping and the
mapping is done by using three similarity measures such as
[1] Syntactic Similarity [2]Semantic Similarity [3]
Structural Similarity.

in web the information’s and sources are
continuously growing and it requires improved accessibility
and data representation interoperability. The Web is an open
environment and different parties use their own concept
definition when publishing data. They
use different
ontology structure and those ontology structures differ for
each person. So in order to achieve interoperability the
different ontologies should be matched.

Balthasar Schopman et al.,[2] proposes a method called
Instance Based ontology match
ing which uses the
extensions of concepts in which the instances are directly
associated with the concepts, to identify whether the pair of
concepts is related or not. The IBOM needs the instances to

EL.Thanga Uma
, S.Rajaranganathan
, Dr.S.Karthik




International Journal of Science, Engineering and Technology Research (IJSETR)

Volume 2, Issue 1, January 2013


All Rights Reserved © 2013 IJSETR

be present with the concept of both ontologies. Normally

instances are associated with single ontology. But here the
author considered two disjoint set and IBOM is applied on
it. It is achieved by enriching instances of each dataset with
the conceptual annotated instance.

A.Mohammed et al., [4] presented an on
tology based
access control in order to support the semantic web service.
In order to specify the concepts and terms the security
ontologies are constructed. The OBAC model contains
several features and it provides high reasoning ability for
taking decisio
ns. By using ontology we can easily search the
information, we can query the information and we can
discover information more quickly. We can obtain high
interoperability when compared to other approaches. This
OBAC model is context sensitive and it contai
ns several
types of context conditions.

This model is designed by using Web Ontology
Language and Web Ontology Language for Service(OWL
S defines an upper ontology for representing the
properties and capabilities of web service in OWL. It
the users and agents to automatically discover,
invoke, compose and monitor when resources offering
services but it is based on some conditions. Thus semantic
Web provides security based on context conditions,
heterogeneous of subject and resources based o
n the role

Ordinary web is based on context based search. There
will be no relation among label or pages and the web
considers only location and it will display the information,
so we cannot obtain satisfactory results.

Yufei Li et al., [7] p
roposed a prototype relation based
search engine ―Ontolook‖. The user enters the keyword
when they want to search some information, by obtaining
the keyword the search engine will make the keyword
combination and submits it. The relationship between
ds will be known only to the users, but not to the
system. The web page considers only the keywords and it
does not consider any relationship between keywords. So
we cannot obtain exact results and the web page is called as
keyword isolated pages. To avoid

this problem Ontolook is
proposed. It is a relation based search engine. The Ontolook
excludes the keyword isolated pages from the result set
obtained. When Ontolook obtains keywords, not only the
keywords are processed, the relationships between

are also processed. By using this relationship
within the keyword pages are displayed to the user and the
pages without the relationship are discarded. When the
keywords are submitted, the Ontolook records all the
relations between the keywords by using o
ntology database.
Next it will assemble these relations and corresponding
keyword into a property

keyword pair candidate set and in
the next step it submits the candidate set to the database to
retrieve the result.

Alfred Ka yui Wong

et al.,

[1] present
ed an ontology
mapping approach that support approximate matching on
formally represented ontologies. Ontology mapping is
defined as the matching of every concept from one ontology
to corresponding concept from the other ontology. The
mapping can be done i
n two ways: exact or similarity based.
The approximate matching and reasoning is often required
in dynamic environment. For this purpose the similarity and
logic based approach for ontology mapping is proposed. It
is based on similarity function and it use
s SLD resolution in
order to measure the semantic likeness between concepts.
This mapping methodology is used in network security
domain and the area is selected as Intrusion detection which
requires approximate matching .In intrusion detection the
ral and structural semantics are considered. In
behavioral the security event is defined in terms of state
transition and in structural the security event is defined in
terms of its composite components.

Semantic Integration is used in various disciplines

such as
database, information integration and ontologies.

Natalya F.Noy [5] provides a survey on semantic
integration approaches in ontology community. The
semantic integration can be done in three ways: (1)
Mapping discovery (2) Declarative formal repre
sentation of
mappings (3) Reasoning with mappings. In order to
discover mapping two approaches are used. The first
approach is to facilitate the knowledge sharing (ie) the use
of shared ontology. The second approach is the use of
heuristics based or machin
e learning techniques. Secondly
representation of mapping involves several representations:
first is the use instance, next is to define the bridging axioms
in first order logic to define the transformations and finally
using views to describe the mapping
from global to local
ontologies. Reasoning with mapping involves the onto
merge system which is used to perform several tasks related
to ontology transformations. Here we are considering two
ontology namely source and target and we translate the
instance t
hat conforms to another ontology. The mapping is
done by onto merge which creates a merged ontology that
includes source, target and mapping and it will generate
ontology extensions.

Savithri Godugula [6] describes the concepts of ontology
mapping. Ontolo
gy mapping is defined as a method which
is useful for matching ontologies or schemas that are
designed independently to each other. When the different
ontologies are mapped, applications can query data from a
multi dimensional data sources transparently

mapping is done by analysing various properties of
ontologies such as syntax, semantics and structure in order
to deduce alternate semantics that may apply to other
ontology and it will creates mappings



y deals with questions concerning what entities
exist or can be said to exist, and how such entities can be
grouped, related within a hierarchy, and subdivided
according to similarities and differences.


Web ontology language is an
international standard for
encoding and exchanging ontologies and is designed to
support the semantic web. OWL is an ontology language
developed for web and it is based on description logics.
Description logics are a family of logics that are decidable
gments of first order predicate logic. This logic focuses
on describing classes and roles and has a set theoretic





International Journal of Science, Engineering and Technology Research (IJSETR)

Volume 2, I
ssue 1, January 2013


All Rights
Reserved © 2013 IJSETR

OWL defines two types of properties. They are object
property and data type property. Object property specifie
relationship between pair of resources. Data type property
specifies relation between a resource and a data type value


Resource Description framework is used to define the
structure of the data. It is designed a
s a meta data model. It
is similar to classic conceptual modeling approaches such as
entity relationship or class diagrams, as it is based upon the
idea of making statements about resources in the form of
object expressions[10].


RDF is a data model, it does not have any significant
semantics. RDF schema is used to define a vocabulary for
use in RDF models. In particular it allows you to define the
classes used to type resources and to define the properties
that resources can h
ave. RDF schema document is simply a
set of RDF statements[10].


Knowledge base is a database for knowledge
management. A knowledge base provides a means for
information to be collected, organized, shared, searched and


Ontology describes the domain of discourse, intended for
sharing among different applications and it is expressed in a
language that can be used for reasoning. By using different
algorithms the efficiency can be improved for searching the

By using the different ontology techniques
we can map or match different ontologies.


The authors would like to thank the Editor
Chief, the
Associate Editor and anonymous Referees for their


[1]Alfred Ka Tui Wong, Nandan paramesh, Pradeep Kumar Ray,
―Similarity and Logic Based Ontology Mapping for Security Management‖
University of New South Wales, Australia.

[2] Balthasar Schopman, Shenghui Wang, Antonie Isaac, Stefan Schl
―Instance Based Ontology Matching by Instance Enrichment‖, Journal on
Data Semantics Concepts and Ideas for Building Knowledgeable Systems,
31 July 2012.

[3] S.Chitra, G.aghila, ―SOMREP: Mapped Meta Information (MMI) for
Semantic Web using Ontology

Mapping Patterns‖, International Journal of
Computer Applications‖, Vol.14 No.5, January 2011.

Jeff Heflin,‖An Introduction to the OWL Web Ontology Language‖,
Lehigh University.

A.Mohammad, G.Kannan,T.Khdour, S.Bani
Ahmad ―Ontology

s Control Model for Semantic Web Services‖ , Journal of Information
and Computing Science, Vol.6, No.3, 2011, pp 177


Natalya F.Noy,―Semantic Integration: A survey of Ontology

Approaches‖, SIGMOD Record, Vol.33,No.4, December 2004.


Savithri Godugula, ―Survey of Ontology mapping Techniques‖,
Software Quality and Assurance, Aug 1,. 2008.

[8] Yufei Li, Yuan Wang, and Xiaotao Huang, ―A Relation

Based Search
Engine in Semantic Web‖, IEEE Transaction on Knowledge and data
ol.19, No.2, February 2007.

Yannis, K. and S. Marco, ―Ontology mapping: The state, of the art‖,
The Knowledge Engineering Review, 18: p: 1

31, 2003.

Yves R.Jean
Marya , E.Patrick Shironoshitaa, Mansur, R.Kabuk,
―Ontology Matching with Semantic

verification‖ Web Semantics: Science,
Services and Agents on the WWW, Vol: 7, p: 235


EL.Thanga Uma

received B.Tech degree in Information
Technology from Anna University, Chennai, Tamilnadu,
INDIA in 2007 and pursuing M.E Software

Engineering in
SNS College of Technology affliated to Anna University
Chennai. Her Research includes Database,, Data Mining.

S.Raja Ranganathan

has completed his MCA Degree in
Computer Science

from SNSCT, in Anna University,
Chennai in year 2008.He ob
tained his Master’s Degree in
Computer Science and Engineering from SNSCT in Anna
University, Coimbatore in year 2010. His research interest
focuses on Web mining and Semantic web. He has
presented more than three papers in national conferences. At
, He is an Assistant Professor of Computer Science
and Engineering in SNS College of Technology, Anna
University, Coimbatore.

He is pursuing part time Ph.D. in
Anna University of technology Coimbatore.

rofessor Dr.S.Karthik

is presently Professor & Dean

the Department of Computer Science & Engineering, SNS
College of Technology, affiliated to Anna University

Coimbatore, Tamilnadu, India. He received the M.E degree
from the Anna University Chennai and Ph.D degree from
Ann University of Technology, Co
imbatore. His research
interests include network security, web services and
wireless systems. In particular, he is currently working in a
research group developing new Internet security
architectures and active defense systems against DDoS
attacks. Dr.S.Ka
rthik published more than 35 papers in
refereed international journals and 25 papers in conferences
and has been involved many international conferences as
Technical Chair and tutorial presenter. He is an active
member of IEEE, ISTE, IAENG, IACSIT and Indi
Computer Society.