Design of Hybrid Ontologies for Mediation System Applied to the E-learning Platform

8/8/2019 Design of Hybrid Ontologies for Mediation System Applied to the E-learning Platform

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(IJCSIS) International Journal of Computer Science and Information Security,

Vol. 8, No. 9, 2010

Design of Hybrid Ontologies for Mediation System

Applied to the E-learning Platform

Otman ABDOUN Jaber EL BOUHDIDI Mohamed GHAILANI

Abdelhadi FENNAN

Laboratory LIST,ERIT Laboratory LIST Laboratory LIST Laboratory LIST FST – Tangier FST - Tangier FST - Tangier FST – Tangier Tangier, Morocco Tangier, Morocco Tangier, Morocco Tangier, Morocco [email protected] [email protected] [email protected] [email protected]

Abstract — This work falls within the scope of E-learning is

important for several reasons. First, resources are structured

(educational needs) and therefore easier to annotate. Second,

there is a curriculum (or Education Plan) that ensures the

semantic integration of resources. Third, services are available

to the teacher and learner. And finally, post evaluation of knowledge acquired by the learner, to verify the adequacy of

resources presented to the learner, and indirectly the

appropriateness of teaching strategies implemented to follow

up resources and services. First of all, it describes the problems

of integrating multiple sources of educational and placed in the

ontology integration process, then treated mediation services,

and their contribution on an E-learning platform.

Keywords- E-learning; Mediation Services; Hybrid Ontologies.

I. INTRODUCTION

Today, the E-learning platforms and educational

information systems use different systems to store and viewdata. Competition, growth in technology, distribution andevolution of the inevitable decentralization contribute to thisplurality. These resources are designed independently of each other, with models and languages that are different, andindependent owners. Most of them were not created to beinteroperable. To achieve this interoperability, systemsintegration data are available.

The basic difficulties for integration and heterogeneity of educational resources belong to two concepts: structural andsemantic. Using a Mediator Agent ensures translation of responses from different data sources and solves the obstacleof the heterogeneous physical and logical sources or services

by providing a uniform access interface. But the semanticheterogeneity remains, even if it requires different sources, tobe in a consistent format. One solution involves the use of one or more ontologies as a tool for the integration of educational resources.

II. INTEGRATION APPROACHES

A data integration system can be characterized by itsarchitecture and integration model. We will distinguish twobasic skeletons for data integration.

A. Mediator Approach

The mediator approach is based on defining mappings forquery translation: a request set by the user in terms of globalschema is translated into one or more subqueries that areevaluated on resources or services [2]. The answers areordered and processed to be compatible with the overallpattern and conform to the query posed by the user (Fig. 1).

Figure 1. Mediator architecture

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Vol. 8, No. 9, 2010

B. Data Warehouse Approach

The warehouse approach applies the principle of the

views and integrates data sources in accordance with the

overall patterns [7]. The result is a data warehouse that can

be directly examined through a suitable language (Fig. 2).

Figure 2. Mediator Warehouse

III. DATA INTEGRATION BASED ON ONTOLOGY

To achieve semantic interoperability in heterogeneous

information, system requires that the semantics of

information exchanged is understood throughout the system.

The Ontology gives the names and descriptions of entities

in a specific field by using the attributes that represent the

relationship between these entities.

There are many advantages in the use of ontologies for

data integration. The ontology provides a rich vocabulary

and predefined concept that interfaces stable access to

databases, and is independent of database schemas.Knowledge represented by the ontology is sufficiently

complete to support the appropriate translation of all sources

of information [1]. The ontology supports compliance

management and identification of conflicting data.

The use of ontologies for the interpretation of implicit

and hidden knowledge is one possible approach to

overcome the problem of semantic heterogeneity. Many

approaches to integration based on ontologies have been

developed to achieve interoperability.

In almost all approaches to integration based on

ontologies, they are used for the explicit description of the

semantics of information sources. But how to use these

ontologies can be different. Three different directions are

identified as follows:

A. Approach with a Single Ontology

The approach with a single ontology which uses a globalontology that provides a shared vocabulary for the

specification of the semantics of data sources (Fig. 3). All

data sources are linked to a global ontology. This can also

be a combination of specialized ontologies. We can apply

this approach to integration problems where all information

sources to integrate provide almost the same view on a

domain.

Figure 3. Approach with a single ontology

This approach has a major drawback when adding or

removing data sources. Indeed, the conceptualization of the

domain represented in the ontology may require changes.

This led to the development of approaches with multiple

ontologies.

B. Approach Based on Multiple Ontologies

In the approach with several ontologies, each source is

described by its own ontology (Fig. 4). The advantage of

this approach is that ontology has no need for commitment

to a common minimum global ontology. Each source of

ontology can be developed without the need to meet or findother sources and ontologies. This architecture can

significantly simplify the task of integrating and supporting

the change (adding and removing sources). However, the

lack of common vocabulary makes it difficult to compare

between different source ontologies.

Figure 4. Approach based on multiple ontologies

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To overcome this problem, an additional, formal

representation defining the mapping between ontologies is

necessary. The mapping between ontologies semantically

identifies the correspondence of terms of different

ontologies.

C. Hybrid Approach

To overcome the drawbacks of the first two approaches, hybrid approaches have been developed (Fig. 5). This

approach describes the semantics of each source by its own

ontology as with the approach to multiple ontologies. But to

make the local ontologies comparable to each other, they are

built from a global shared vocabulary.

Figure 5. Hybrid approach for the description of data sources

It contains the basic terms is an area that can be combined

with local ontologies to describe a more complex semantics.

Sometimes the shared vocabulary can be an ontology.

The advantage of the hybrid approach is the fact that new

sources can easily be added without the need for change.

Also, this approach supports the acquisition and

development of ontologies. But the major drawback of

hybrid approaches is that existing ontologies cannot easily

be reused, but must be rebuilt.

The state of the art in data integration architecture

showed that the hybrid approach allows for greaterscalability and extension. Indeed, this architecture allowsadding new sources to ensure certain independence.

The mediation system must manage the independence of data sources and their distribution. In addition, the systemmust manage the interaction between the global ontologyand local ontologies in creating queries.

IV. MEDIATION ARCHITECTURE ADAPTED FOR A

PLATFORM FOR DISTANCE LEARNING

E-learning application is online through the use of the

Web. Given the diversity and the exponential growth of

learning resources used in a training type E-learning, it isincreasingly difficult to find relevant teaching materials [8].

E-learning application is sharing the same problem of

relevance with the Web when learners want to access

knowledge at their disposal.

A. The Modeling of a Mediation System Based on

Ontologies for E-Learning Platform

We agree to use a mediation system based on ontologies.Local and global ontologies provide a common set of termsthat can be applied to any resource, which allowsorganizations to describe and search their resources [11].

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Figure 6. Proposed mediation architecture

Q Q uueerryy EEnnggiinnee

User’s request

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Facing the rapidly changing media and communication in

the field of machine learning, a critical mass of educational

resources is produced across many universities. Reuse of

learning objects, thus produced locally, is low and even non-

existent among universities. This can be explained, in

particular by the lack of knowledge on the part of teachers

on existing resources. We propose a model for integrating

data sources that aims to overcome this deficit. This is amediation system resources distributed based on the

description by the local ontology and a global ontology, this

scenario is described in the above (Fig. 6).

The local ontology contains the description of sources.

And a global ontology represents a domain ontology

learning resources (Fig. 7).

We assume in our approach that each university has its

own ontology, a description of learning resources and their

semantic description. Domain ontologies and descriptors of

each source are, then, used to build knowledge on

distributed objects, like a catalog accessible to all.

B. Scenario for Integration of Educational Resources

An actor system (Student, Professor, ...) calls for ateaching aid while specifying a number of criteria that

describe it (Speciality, Material, Level, Type of document

format). The mediator agent (MA) when he receives the

request, he dissected to extract the specialty that will be

sought in the global ontology to index academic institutions

responding to the request. Then, AM makes a request for it

includes in addition to the Specialty Material Level, Type

and Format document and send it to agents Wrapper

institutions indexed. Each wrapper agent sends the request

received after his translation to make it understandable by

the agent resources. The latter consults the ontology to

search for local media requested, and sends the result to find

the agent wrapper, which in turn will translate and send theresponse to the mediator agent. AM generates a page for the

user, indexing all media found. The figure 8 describes the

sequence diagram for the processing steps of the integration

of educational resources.

Consult the Global Ontology

Indexing institutions to interrogate

Formulate a subquery

Consult local ontology

Search for media requested

Ask for an educational support

Translate the query into a language understandable by A.S

Send the translated q uery to A.Ş.

Extract the informati on requested

Send the results found

Translate responses in a language understandable by AM

Send Response translated

Page indexing all the supports found

Send a subquery

Analyze the query

Put together the results

Actor system Mediator Agent M.A Agent Wrapper Agent resources : A.S

Global Ontology : G.O Local Ontology : L.O

Consult the Global Ontology

Indexing institutions to interrogate

Formulate a subquery

Consult local ontology

Search for media requested

Ask for an educational support

Translate the query into a language understandable by A.S

Send the translated q uery to A.Ş.

Extract the informati on requested

Send the results found

Translate responses in a language understandable by AM

Send Response translated

Page indexing all the supports found

Send a subquery

Analyze the query

Put together the results

Figure 8. A Sequence Diagram for the processing steps for integration of educational resources

Root

Tutorials

Courses

Works practiceExercises

Correction of work practice

Exam

Slides

Professor

Learner

Instructional Designer

Educational Resources

Actors

Figure 7. Ontology for a local educational resource


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Vol. 8, No. 9, 2010

CONCLUSION

In this paper work, we presented a new mediation

architecture with an objective to build up an environment

for integrating various educational sources / services,

achieve interoperability and heterogeneity between these

sources, and consult and look for educational materials.

The concepts of data integration and services based onontologies, and several approaches to use them in the

integration of data sources, were presented. We showed the

provision of mediation systems to E-learning, referring to

some mediation projects, which have been made based on

ontologies.

REFERENCES

[1] J. El Bouhdidi, M. Ghailani, O. Abdoun, A. Fennan, A NewApproach based on a Multi-ontologies and Multi-agentsSystem to Generate Customized Learning Paths in an E-Learning Platform, International Journal of ComputerApplications, 2010.

[2] Kalpana Nigam, Monica Mehrotra, Ontology Mediation withMachine Learning, IJCSIC, 2010

[3] J. Euzenat and P. Shvaiko. Ontology Matching. Springer,2007.

[4] A. Gangemi. Ontology design patterns for semantic Webcontent. In Y. Gil, E. Motta, V. Richard Benjamins, and M.A.Musen, editors, International Semantic Web Conference,volume 3729 of Lecture Notes in Computer Science, pages262 – 276. Springer, 2005.

[5] A. Coulet, M. Smaïl-Tabbone, A. Napoli, and M.D. Devignes.Role Assertion Analysis : a proposed method for ontologyrefinement through assertion learning. In Proceedings of theFourth Starting AI Researchers’ Symposium (STAIRS 2008),pages 47 – 58. IOS Press, 2008.

[6] Mohand-Saïd Hacid et Chantal Reynaud : L’intégration de

sources de données, Thèse, LIRIS, UFR InformatiqueUniversité Claude Bernard Lyon 1, 2009

[7] T. Adams,J. Dullea,P. Clark, S. Sripada, T.Barrett. SemanticIntegration of Heterogeneous Information.SourcesUsing aKnowledge-Based System.In Proc 5th IntConf on CS andInformatics (CS&I’2000),2005, pages

[8] S. Barlow. Data Integration.University of Passau.July 24,2006,

[9] Abel MH., Dieng-Kuntz R., Hérin D., Lenne D., Moulin C.,Pompidor P. Langages pour le Web Sémantique et pour le E-Learning. Journée thématique AFIA : Web sémantique pourle e-Learning. Plateforme AFIA. Nice, 30 mai. pp. 97-122,2005.

[10] S. Cohen-Boulakia, O. Biton, S.B. Davidson, and C.Froidevaux. BioGuideSRS : querying multiple sources with auser-centric perspective. Bioinformatics, 23(10) :1301 – 1303,2007.

[11] Y. An, J. Mylopoulos, and A. Borgida. Building semanticmappings from databases to ontologies. In AAAI. AAAIPress, 2006.

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AUTHORS PROFILE

Otman ABDOUN. Born in KSAR EL KEBIR, Morocco. He received the“Master of Sciences and Technologies” in Computer Engineering and the

“Magister in Computer Sciences Systems and Networks” degree from theUniversity of Abdelmalek Essaadi, Tangier, Morocco. He is currentlyworking toward the Ph.D. degree with the Computing and

Telecommunications Research Group at Abdelmalek Essaadi University,

Tangier, Morocco. His research interests include Mediation and semanticweb in E-Learning.

Jaber EL BOUHDIDI. Born in Chefchaouen, Morocco. He received the“Master of Sciences and Technologies” in Computer Engineering and the

“Magister in Computer Sciences Systems and Networks” degree from the

University of Abdelmalek Essaadi, Tangier, Morocco. He is currentlyworking toward the Ph.D. degree with the Computing and

Telecommunications Research Group at Abdelmalek Essaadi University,

Tangier, Morocco. His research interests include semantic web and Multi-agents Systems in E-Learning.

Mohamed GHAILANI. Born in Larache, Morocco. He received the“Master of Sciences and Technologies” in Computer Engineering and the

“Magister in Computer Sciences Systems and Networks” degree from theUniversity of Abdelmalek Essaadi, Tangier, Morocco. He is currently

working toward the Ph.D. degree with the Computing and

Telecommunications Research Group at Abdelmalek Essaadi University,Tangier, Morocco. His research interests include web semantic, ontology in

E-Learning.

Abdelhadi FENNAN. is pHD doctor and professor of computer science at

Faculty of Sciences and technology of Tangier in Morocco. He is part of

many boards of international journals and international conferences. He has

published several articles on E-learning.


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Design of Hybrid Ontologies for Mediation System Applied to the E-learning Platform