a competency location system based ontology presentation

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Authors: Leila ZEMMOUCHI-GHOMARI, [email protected] Abdessamed Réda GHOMARI, [email protected] Keltoum Benlahareche, [email protected] LMCS Laboratory ESI, national Superior School of Computer Science, www.esi.dz Algiers, ALGERIA Colloque sur l'Optimisation et les Systèmes d'Information COSI'2014, 8-10 Juin 2014, Béjaia, Algérie Université Abderrahmane Mira - Béjaia

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it is our presentation at COSI'2014 (Colloque sur l'Optimisation et les Systèmes d'Information), 8-10 June 2014, Béjaia, Algérie

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Page 1: A competency location system based ontology presentation

Authors: Leila ZEMMOUCHI-GHOMARI, [email protected]

Abdessamed Réda GHOMARI, [email protected]

Keltoum Benlahareche, [email protected]

LMCS Laboratory

ESI, national Superior School of Computer Science, www.esi.dz

Algiers, ALGERIA

Colloque sur l'Optimisation et les Systèmes d'Information

COSI'2014, 8-10 Juin 2014, Béjaia, Algérie

Université Abderrahmane Mira - Béjaia

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Motivation

Right Person A given Task

Organization

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Competency location system objectives:

1. Improve the quality of work: Identification of the

most competent person to perform a task

2. Improve the productivity: Reduce the time

required to perform a task

3. Improve the management of the human capital:

Global vision of the available skills

in the Organization

Motivation

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Motivation

Our current CLS has some

shortcomings:

• Input through free text: possibility

of spelling errors, use of synonyms

and ineffective information search

• Exclusive use of tags to describe

the stored data, which leads to a

lack of semantics

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in order to address these shortcomings, the system

has to be enhanced with an application ontology

for the location of intra organizational skills

Expected ontology benefits:

• Use of a controlled vocabulary: same vocabulary

for all members of the organization

• Enrichment of terms with semantics, efficient

skills research and a better management skills

Proposed Solution

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The new architecture of the competency location system

Proposed Solution

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Ontology Building Process

We adopted NeOn methodology [Suárez-Figueroa,

2012] to build ECAO ontology, "ESI Competence

Application Ontology"

We combined two scenarios(from 9 scenarios):

1. Development from scratch (scenario 1):

specification, conceptualization and formalization

2. Reuse and Reengineering of ontological resources

(scenario 4)

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Ontology Building Process

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Phase 1: Specification

• Produce Ontology Requirements Specification

Document (ORSD) Purpose, scope, intended

users, intended uses, Implementation Language,

list of competency questions (ontology

requirements)

• Extract relevant terms from Competency questions

and their answers Glossary of terms

Ontology Building Process

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ECAO Competeny Questions

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Ontology Building Process

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Phase 2: Ontology Selection

- Discovery in repositories and SW search engines:

25 candidate ontologies

- Evaluation & comparison: are the requirements

(CQs) covered by these ontologies?

- Selection of O24:

URI: www.institutepupin.com/skills.owl

label: skills.owl, version: 2011

classes, properties ans instances: 22/17/123

Ontology Building Process

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Ontology Building Process

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Phase 3: Reverse Engineering

Ontology Building Process

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Ontology Building Process

The conceptual model of the selected ontology/Extracted terms

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Ontology Building Process

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1. Glossary of terms of the selected ontology

2. Glossary of terms obtained from competency

questions and their answers

3. Data dictionary of the first version of the

database of “ESI Clever Network”

Ontology Building Process

Phase 4: Restructuring

Fusion of the terms of the following glossaries

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Ontology Building Process

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Phase 5: Forward Engineering

Phase 5.1: Conceptualization

Consists of organizing and structuring relevant terms

Ontology Building Process

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Typical competencies to be modeled in our domain are:

• Technical abilities, such as programming languages,

database management systems, operating systems or

optimization tools

• Engineering competences, such as networking, computer

architecture, human-computer interaction or knowledge

management

• Social competences, such as coaching, collaboration or

communication

• Language skills such as writing, reading or speaking

• Business competences such as auditing, management or

selling

ECAO Ontology

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Ontology Building Process

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Ontology Building Process

Phase 5.2: Formalization

Formal ontology must include axioms using formal

language to constrain the possible interpretations of

the ontology components

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Available at:

https://sourceforge.net/projects/competenyapplicationontology/

and at:

http://datahub.io/fr/dataset/competency-application-ontology

ECAO ontology has been implemented in

produced by Neon Toolkit editor

ECAO Ontology

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Ontology Building Process

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The integration of ECAO ontology in the competence location

system includes:

• Update the CLS Database according to the new conceptual

schema, such as adding missing tables and programming the

new constraints on the database

• Update the CLS program according to the ontology

constraints, such as to replace the free text input fields with

extensible lists of predefined values

… New CLS based Ontology

Phase 6: Integration (ongoing work)

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What We did:

• we designed a new architecture of our current

competency location system (add the semantic

perspective)

• we developed a competency application ontology

(best practices of ontology development) to be

integrated in the CLS

What remains to be done:

• To Integrate the developed ontology in the CLS

• To Evaluate the new CLS

Conclusion & future work

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