This is our presentation at International Conference of Data Mining and Knowledge Engineering "ICDMKE 13'" held at London, UK, 03-05 July 2013. the paper is available at: http://www.iaeng.org/publication/WCE2013/WCE2013_pp1595-1600.pdf

1. The 2013 International Conference of
Data Mining and Knowledge Engineering, ICDMKE'13
3-5 July, 2013, London, U.K.
Process of Building
Reference Ontology
for Higher Education
Leila ZEMMOUCHI-GHOMARI, l_ghomari@umbb.dz
UMBB, M’hamed Bouguerra University Boumèrdes, www.umbb.dz
Boumèrdes, ALGERIA
&
Abdessamed Réda GHOMARI, a_ghomari@esi.dz
LMCS Laboratory
ESI, national Superior School of Computer Science, www.esi.dz
Algiers, ALGERIA

2. OUTLINE
Introduction

Reference Ontology

University Ontologies

Ontology Building Process


Selected Scenarios

Building phases
Ontology Evaluation
o
Structural Evaluation
o
Functional Evaluation
o

ICMKE'13 London, UK

Usability Issues
Conclusion
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3. INTRODUCTION
Context: Semantic Web
Issue: ontology applications specifity  Weak use and
ICMKE'13 London, UK
Reuse
Proposition: Use of Reference ontology instead of
Domain or Application ontology
Case Study: Reference Ontology for Higher Education
knowledge Domain
Main Purpose: Explain the Process of Building a
Reference Ontology for a given Domain
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4. REFERENCE ONTOLOGY
Definition
“ Domain Reference ontologies represent knowledge about a
ICMKE'13 London, UK
particular part of the world in a way that is independent
from specific objectives, through a theory of the domain”
[Burgun, 2006]
Features [Ghomari & Ghomari, 2009]
 Reference Ontology is a core ontology
(central concepts)
 Reference Ontology is a heavyweight ontology
(rich axiomatic theory)
 Reference ontology is consensual domain ontology
(not an application ontology)
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5. UNIVERSITY ONTOLOGIES
Limitations
University ontology
(Heflin, Lehigh University, 2000)
No inference rules are defined
Univ-Bench ontology
(Lehigh university, 2004)
Intended to be a benchmark for
performance evaluation of
semantic web repositories
AIISO, Academic Institution
Internal Structure Ontology
(Styles and Shabir, 2008)
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Ontology
Focus on structural perspective of
the university domain
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6. ONTOLOGY BUILDING PROCESS
HERO Ontology: Higher Education Reference
Ontology (http://sourceforge.net/projects/heronto/?source=directory)
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Ontology
engineering
methodology:
NeOn
methodology (Networked ontologies) [Suarez-Figueroa &
al, 2008] proposes nine (9) scenarios
Selected Scenarios:
 Development from scratch (scenario 1)
 Reuse of non ontological resources (scenario 2)
Classifications (eg: Carnegie Classification)
 Academic reports, higher education websites


Reuse of ontological resources (scenario 3)
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7. ONTOLOGY BUILDING PROCESS
ICMKE'13 London, UK
Building Phases:
1. Specification: Ontology Requirement Specification
Document (ORSD):
Purpose, Scope, Implementation Language,
Intended End-Users, Intended Uses, Ontology
Requirements: Competency Questions Technique
[Gruninger & Fox, 1995]
Five categories: [ACE, 2007]
 Faculty, appointments and research area
 Student and their life
 Administration
 Degrees and Curriculum Programs
 Finance
 Governance
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8. CQ03. Must a university
teacher be a researcher?
CQ29.What is a campus?
CQ33.What higher
education admission
criteria are required?
15 CQs
27 CQs
CQ4. What is expected from
university teachers?
4. Degrees
and
Curriculum
Program
University
Domain
competency
questions
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CQ38.What roles and
responsibilities have a dean?
CQ53. What high
education degrees exist?
CQ55.How is organized
the academic year?
1Faculty,
appointments
and research
area
2. Students
and their life
3.
Administration
14 CQs
CQ41.Why universities are
organized into departments?
33 CQs
CQ73. What average size and
duration have governing board ?
CQ76. What is the role of
the accreditation?
6. Governance
11 CQs
CQ77. Who are
accreditors?
5. Finance
08CQs
CQ74. What financial incomes
have higher education
institutions?
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9. ONTOLOGY BUILDING PROCESS
Specification (suite): Extraction of relevant terms from
competency questions and their answers  Glossary of
terms (nouns, verbs)
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2. Conceptualization: organization of ontology entities
with regard to each other by means of inetermediate
representations (data dictionary, hierarchy of concepts,
hierarchy of attributes and table of relations between
concepts)
3. Formalization: restrictions on ontology primitives are
defined and the ontology is generated in a formal
language via the ontology editor (NeOn Toolkit)
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10. ONTOLOGY BUILDING PROCESS
Specification (suite): Extraction of relevant terms from
competency questions and their answers  Glossary of
terms (nouns, verbs)
ICMKE'13 London, UK
2. Conceptualization: organization of ontology entities
with regard to each other by means of inetermediate
representations (data dictionary, hierarchy of concepts,
hierarchy of attributes and table of relations between
concepts)
3. Formalization: restrictions on ontology primitives are
defined and the ontology is generated in a formal
language via the ontology editor (NeOn Toolkit)
10

11. ONTOLOGY BUILDING PROCESS
Specification (suite): Extraction of relevant terms from
competency questions and their answers  Glossary of
terms (nouns, verbs)
ICMKE'13 London, UK
<owl :Class rdf :about= »http://www.UniversityReferenceOntology.org/HERO#Laboratory »>
<owl :equivalentClass>
<owl :Restriction>
2. Conceptualization: organization of ontology entities
<owl :onProperty rdf :resource= »http://www.UniversityReferenceOntology.org/HERO#Contains »/>
with regard to each other by means of inetermediate
<owl :onClass rdf :resource= »http://www.UniversityReferenceOntology.org/HERO#ResearchGroup
»/>
representations (data dictionary, hierarchy of concepts,
<owl :minQualifiedCardinalityrdf :datatype=http://www.w3.org/2001/XMLSchema#nonNegativeInteger
>1hierarchy of attributes and table of relations between
</owl:minQualifiedCardinality>
</owl:Restriction>
concepts)
3. Formalization: restrictions on ontology primitives are
defined and the ontology is generated in a formal
language via the ontology editor (NeOn Toolkit)
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12. ONTOLOGY EVALUATION
Structural Evaluation: verification of consistency and
coherence of the ontology via logical reasoners, such
as: Pellet (PlugIns of ontology editors)
1.
Functional Evaluation: « how well the ontology meets
the requirements of the developers/the users ? »
1.
Evaluation by domain experts: via an online questionnaire
[Zemmouchi-Ghomari & Ghomari, 2013a]
2.
2.
Evaluation via competency questions technique: translation
of natural language competency questions into SPARQL
queries, [Zemmouchi-Ghomari & Ghomari, 2013b]
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1.
Usability issues: depends on the level of annotation
of the evaluated ontology. In the case of HERO
ontology: 97 annotations (definitions, comments and
labels)
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13. CONCLUSION
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HERO Ontology has been built according to rigorous
ontology building principles
however it is not yet
a reference ontology for higher education
large
consensus of domain experts not yet reached
several evaluation rounds are necessary to improve
the quality of the ontology
Some recommendations in order to build a
reference ontology for a given domain:
 Give priority to reuse of available resources (non
ontological and ontological)
 Make
emphasis on specification (knowledge
acquisition) and evaluation (according to several
perspectives) in the ontology engineering process
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14. REFERENCES






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
[ACE, 2007], ACE, American Council on Education, “A brief guide to us higher
education system”, 2004.
[Burgun, 2006], Burgun A., “Desiderata for domain reference ontologies in
biomedicine”, Journal of Biomedical Information, Vol. 39, N° 3, 2006, pp. 307-313.
[Ghomari & Ghomari, 2009], Zemmouchi-Ghomari L., Ghomari A. R., “Reference
Ontology”, International IEEE Conference on Signal-Image Technologies and
Internet-Based System, Marrakech, Morocco, 2009.
[Gruninger & Fox, 1995], Gruninger M., Fox M. S., “Methodology for the design and
evaluation of ontologies”, Workshop on Basic Ontological Issues in Knowledge
Sharing, Montreal, Canada, 1995, pp. 6.1–6.10.
[Suarez-Figueroa & al, 2008], Suarez-Figueroa M., Dellschaft K., Montiel-Ponsada
E., Villazon-Terrazas B., Yufei Z., Agyado-Decea G, Garcia A., Fernandez-Lopez M.,
Gomez-Perez A., Espinoza, Sabou M., “NeOn Methodology for Building
Contextualized Ontology Networks”, (NeOn Deliverable D5.4.1.), FP7 NeOn Project,
2008.
[Zemmouchi-Ghomari & Ghomari, 2013a], Zemmouchi-Ghomari L., Ghomari A. R.,
“A New Approach for Human Assessment of Ontologies”, the third international
conference of information systems and technologies, ICIST’2013, Tangier, Morocco,
2013.
[Zemmouchi-Ghomari & Ghomari, 2013b], Zemmouchi-Ghomari L., Ghomari A. R.,
“Translating Natural Language Competency Questions into SPARQL Queries: a
Case Study”, The First International Conference on Building and Exploring Web
Based Environments, Seville, Spain, 2013.
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15. QUESTIONS & COMMENTS
ARE WELCOME
ICMKE'13 London, UK
THANK YOU
l_ghomari@umbb.dz
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