PAPER PRESENTATION ON

Course Registration Ontology for Students (A Case Study of Computer Science Department, University of Ibadan)

Ayorinde I. T. , Akinkunmi B. O. and Alao Y. M.Computer Science Department, University of Ibadan, Ibadan,

Nigeria

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AUGUST, 2014.

International Conference on Transition from Observation to Knowledge to Intelligence (TOKI) –

August 20-22, 2014.

Presentation IntroductionAim & ObjectivesMethods & MaterialsImplementationConclusionFuture DirectionReferences

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IntroductionOntology defines a set of representational primitives with which to model a domain of knowledge or discourse. The representational primitives are typically classes, attributes and relationships. (Gruber 2009).

The definitions of the representational primitives include information about their meaning and constraints on their logically consistent application.

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Introduction Contd.Ontology can be viewed as a level of

abstraction of data models, analogous to hierarchical and relational models, but intended for modeling knowledge about individuals, their attributes, and their relationships to other individuals.

Ontologies are typically specified in languages that allow abstraction away from data structures and implementation strategies; in practice, the languages of ontologies are closer in expressive power to first-order logic or descriptive logic than languages used to model databases (Gruber 1993).

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Introduction Contd.Ontologies are said to be at the

"semantic" level, whereas database schema are models of data at the "logical" or "physical" level.

Course registration is the act of registering students properly for different courses with respect to their levels.

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Aim & ObjectivesThe aim of this research work is to

build an ontology on course registration for students.

The objectives are: To forestall the perpetual mistakes

being made by the students during course registration at the beginning of every academic session.

To guide students on proper registration in order to have better CGPAs (Especially the weak ones).

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The ontology’s requirements were defined using the following competency questions:

What is the minimum number of course units to register for in a session?

What courses are to be taken in each of the levels?

What is the procedure for registration?

What necessary information does a student need from his/her level adviser?

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Methods and Materials

Conceptual Modeling of the DomainThe following steps were taking in building the

courseregistration ontology for students:defining classes in the ontology,arranging the classes in a taxonomic (subclass–

superclass) hierarchy,defining slots and describing allowed values for

these slots,filling in the values for slots for instances.defining relationships among the various entitiesWe used Protégé 4.1 (an ontology editor) to

model the class hierarchy.

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Methods and Materials Contd.

Relationships Between Entities.A STUDENT IS_IN a LEVEL A STUDENT OFFERS some COURSESSome COURSES are OFFERED in a LEVELSome COURSES have PREREQUISITES in Some

LEVELSSome COURSES are being OFFERRED BY a

STUDENT (This is an inverse functional requirement to “A STUDENT OFFERS some COURSES”

COURSE_CODE HAS TITLECOURSE_CODE HAS UNIT 9

Methods and Materials Contd.

Implementation

Fig. 1: Ontograph Showing the various steps needed for registration

Implementation Contd.

Fig. 2: Ontograpgh Showing the Basic Things to get from a Level Adviser

Implementation Contd.

Fig. 3: Result of a Query Showing 100 Level Courses

Implementation Contd.

Fig. 4: Ontograph of Relationship Between Student and Courses

CONCLUSIONThe relevant concepts which characterize the

domain of discourse has been identified, appropriately defined along with their binding relationships and slots, and has been classified based on the inherent concepts they describe.

The concept has been presented using a tree-like class hierarchy which shows the relationship between the super-class concept and the sub-class concepts.

Hence, an error free, reliable and efficient registration process that will guide the students on how to register their courses has been presented here.

This ontology is actually a Transition from Observation to Knowledge to Intelligence.

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Future DirectionsWe intend to expand the scope of this ontology to

all the departments in the University of Ibadan and also build more relationships among the entities.

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REFERENCESREFERENCES Gruber T. R. (1993). Toward Principles for the Design of

Ontologies Used for Knowledge Sharing. Knowledge Systems Laboratory (KSL), Stanford University, 1993).

Gruber T. R. (2009). “Ontology” (in the Encyclopedia of Database Systems, Ling Liu and M. Tamer Özsu (Eds.)), Springer-Verlag, 2009.

Farquhar A., Fikes R. and Rice J. (1997). “The Ontolingua Server: A Tool for Collaborative Ontology Construction.” International Journal of Human- Computer Studies, vol. 46, No. 6, June 1, 1997, pp. 707-727. 

Bateman, J. A. (1995). On the Relationship Between Ontology Construction and Natural Language: a Socio-Semiotic View. International Journal of Human-Computer Studies. Vol 9, No 3, pg 15-21.

Fikes R. , Farqhuar A. and Rice J. (1997). Tools for Assembling Modular Ontologies in Ontolingua, Tech. Report KSL-97-03, Knowledge Systems Laboratory, April, 1997, Stanford University.

Swartout, W., & Tate, A. (1999). Ontologies, Guest Editors' Introduction. IEEE Intelligent Systems 14(1), pg 18-19.

Genesereth M. R. and Nilsson N. J. (1987). Logical Foundation of Artificial Intelligence. Morgan Kaufmann, Los Altos, California.

 

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THANK YOU

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