Post on 12-Jan-2016
Intelligent E-Commerce System Lab.
Survey of Ontology Engineering Methodologies
22071062 Aettie Ji
Intelligent E-Commerce System Lab.
OUTLINE Part 1 – Review of Chap. 9 in “Semantic Web
Technologies”, Davies, J., R. Studer and P. Warren, WILEY Introduction The Methodology Focus Past and Current Research DILIGENT Methodology Discussion and Next Step
Part 2 - Brief Introduction of NeOn Methodology, NeON Project, http://www.neon-project.org
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Part1 - Ontology Engineering Methodologies
Sure, Y., C. Tempich and D. Vrandecic
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Introduction Methodologies of traditional knowledge
management systems(KMS) Centralized Approach Domain experts who provide the model for the
knowledge Ontology engineers who structure and formalize it
Decentralized knowledge management systems Methodologies based on traditional, centralized KMS are no longer feasible.
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Methodology Focus Ontology Engineering Methodology
Ontology management activities Scheduling of the ontology engineering task Control mechanism and quality assurance steps.
Ontology development activities Procedures to specify, conceptualize, formalize, and
implement ontology (which is defined for environment and feasibility study)
Guidance for the maintenance, population, use, and evolution of the ontology.
Ontology support activities Knowledge acquisition, evaluation, integration, merging
and alignment, and configuration management.
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Methodology Focus Documentation
Results of each activities Sometime the decision making process itself
Evaluation Means to measure the quality of the created
ontology Difficult!! in most cases, modeling decisions are
subjective. Measures derived from statistical data or
philosophical principles. OntoClean (Guarino and Welty, 2002)
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Past and Current Research Methodologies
UPON, (Nicole et al., 2005) HCONE (Kotis et al., 2004) OTK Methodology (Sure, 2003) OntoWeb project, (Leger et al., 2002) CommonKADS, (Schreiber et al., 1999) DOGMA, (Jarrar and Meersman , 2002) The Enterprise Ontology, (Uschod and King, 1995) The KACTUS, (Bernaras et al., 1996) METHODOLOGY, (Fernandez-Lopez et al., 1999) Etc.
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Past and Current Research Discussion and Open Issues
1. Ontology maintenance support.2. Distributed ontology engineering.3. Fine-grained guidelines for all phases.4. Representation of multiple views.5. Agreement support under conflicting interests.6. Best practices.7. Ontology engineering with the help of automated
methods.8. Process definition by single process step
combination.9. Integration into business process model.10. Cost estimation and pricing.
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Past and Current Research
Ontology Engineering Tools KAON OImodeller (Bozsak et al., 2002; Motika et
al., 2002) Protégé (Noy et al., 2000) WebODE (Arptrez et al., 2001) OntoEdit(=OntoStudio) (Sure et al., 2002, 2003)
Open Issues Support for an arbitrary process Inter-operability Technical solution to support versioning, ontology
learning or distributed engineering of ontologies
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DILIGENT Methodology Assumptions
The users: Several experts involved in collaboratively building
the same ontology who are also users. Much larger community of users than the community of
experts. Birds-eye view:
Users are free to use and modify an initial ontology locally.
A central board maintains and assures the quality of the core ontology.
The board is responsible for updating the core ontology.
The board only loosely controls the process.
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DILIGENT Methodology Main Steps
Build An initial ontology doesn’t have to be complete, It should be relatively small for easy access.
Local adaptation Users work with the core ontology and adopt it locally
to their own needs. They are not allowed to directly change the shared
ontology. The control board collects changes requests to it and
logs local adaptation.
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DILIGENT Methodology Main Steps
Analysis The board analyses the local ontologies and the
requests for changes and tries to identify similarities in users’ ontologies.
Deciding which changes are going to be introduced in the next version of the shared ontology is crucial activity of the board.
Revision The board should regularly revise the shared ontology
realigning users needs and gaining higher acceptance, ‘sharedness’ and less local differences.
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DILIGENT Methodology Main Steps
Revision Users can be involved in ontology development and
evaluate the ontology from an usability point of view. Domain experts evaluates it from a domain point of
view. Knowledge engineers evaluates it from a domain
and technical point of view. Ontology engineers are responsible for technical
evaluation, including analyzing and balancing arguments, and updating the ontology.
Local Update User can update their own local ontologies to better
use the knowledge represented in the new version.
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DILIGENT Methodology
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DILIGENT Methodology Argumentation Support
The exchange of arguments should be embedded into a general argumentation framework. Facilitating the ontology engineering and evaluation process. Offering more fine-grained guidance to achieve agreement.
The creation of a shared conceptualization without any guidance is almost impossible, or time consuming.
Argumentation model of DILIGENT Two virtual chat room, one for providing topics for discussion,
hand raising and voting and the other one for exchanging arguments.
Due to the stricter procedural rule agreement is reached more quickly and a much wider consensus is reached.
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Conclusion and Next Steps With DILIGENT methodology, some of open issues are
tackled and proposed a methodology which allows continuous improvement of the underlying ontology in distributed setting.
The methodology is still under development to cover The improved quality of the results of current ontology learning
methods. A more fine-grained process model. Criteria to identify proper ontology evaluation scheme. Tools for a more automatic appliance of such evaluation
technique. Integration the process model into a knowledge management
business model. The estimation of costs incurred by the building process. Capturing experiences and describing best practices from
application.
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Part 2 – Brief Introduction of NeOn Methodology
NeOn Projecthttp://www.neon-project.org
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Comparison of Presented Methodologies
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Comparison of Presented Methodologies Regarding NeOn dimensions,
In the collaboration dimension, none of the methodologies consider distributed ontology engineering. (DILIGENT does it, but it only provides a rich argumentation framework.)
In context dimension, none of them treat with it. None of them provide guidelines for treating the
dynamic and evolution of the ontology. None of them provide detailed guidelines for
the process or activities. None of them are described targeted to
software developers and ontology practitioners.
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Aim within the NeOn Project Creation of the NeOn methodology for
building ontology networks covering the drawbacks of the three methodologies and benefiting from the advantages included in such methodologies.
NeOn methodology will include the benefits provided by DILGENT about collaboration.
Furthermore, it will take into account the proposal of METHONTOLOGY and On-To-Knowledge about the use of competency questions for the ontology specification activity.
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When do Ontologies become Ontology Network? If there is a requirement or it is advisable to
express meta relationship, for example priorVersionOf useImports extendingBy composedByModules haveMapping
Ontology permits a fluent knowledge sharing and an easy enrichment of the network.
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NeOn Ontology Development Process Consensus reaching process
For the identification and definition of the activities involved in the ontology network development process.
NeOn glossary of activities Definitions of the activities involved in ontology
network construction, which have been collaboratively built and consensuated by all NeOn partners, by means of the consensus reaching process.
NeOn Table of “Recommended and If-Applicable” A classification of the activities required for the
development of ontology networks and those that are applicable, but not required, and, therefore, they are non-essential or dispensable.
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O. DiagnosisO. Repair
O. ExtensionO. Specialization
O. ModularizationO. Module ExtractionO. Partitioning
O. SpecificationO. ConceptualizationO. FormalizationO. Implementation
O. Assessment
O. UpdateO. Upgrade
Development
Activities
Maintenance
Activities
Use Activities
NeOn Ontology Development Process
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O. Documentation
Knowledge AcquisitionO. ElicitationO. Learning
O. EvaluationO. ValidationO. Verification
O. Pruning
O. Enrichment
Environment StudyFeasibility Study
O. IntegrationO. MappingO. Merging
O. Combining
O. TranslatingO. Population
O. Transforming
O. Evolution
O. VersioningO. Summarization
O. AlignmentO. Configuration Management
O. ReuseO. SearchingO. Selection
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Scenarios for Building Ontology Networks 9 identified NeOn scenarios for building
ontology network. Scenario 1: Building ontology networks from
scratch without reusing existing knowledge resources.
Scenario 2: Building ontology networks by reusing and reengineering non ontological resources.
Scenario 3: Building ontology networks by reusing ontological resources.
Scenario 4: Building ontology networks by reusing and reengineering ontological resources.
Scenario 5: Building ontology networks by reusing and merging ontological resources.
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Scenarios for Building Ontology Networks 9 identified NeOn scenarios for building
ontology network. Scenario 6: Building ontology networks by reusing,
merging and reengineering ontological resources. Scenario 7: Building ontology networks by reusing
ontology design patterns. Scenario 8: Building ontology networks by
restructuring ontological resources. Scenario 9: Building ontology networks by
localizing ontological resources.
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Scenarios in the Ontology Life Cycle
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Life Cycle of Ontology Networks NeOn Life Cycle Models
Waterfall Ontology Network Life Cycle Model Incremental Ontology Network Life Cycle Model Iterative Ontology Network Life Cycle Model Evolving Prototyping Ontology Network Life Cycle
Model Spiral Ontology Network Life Cycle Model
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Conclusions and References Which one are the activities involved in the
ontology development process? Which one is the goal of each activity?
NeOn Glossary of Activities NeOnTable of “Recommended and If-Applicable” NeOn Development Process
When should I carry out each activity? Where is the relationship of one activity with
the others? Ontology Network Life Cycle models
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Conclusions and References Where can I find ontologies with the goal of
reusing them? Ontology Metadata Vocabulary Ontology Registries
How can I build the ontology for my application?
Do I need a single ontology or an ontology network? Several examples from NeOn deliverables 5.3.1
and 5.4.1.
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