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Ontology engineering refers to a set of principles that are related to the development of an ontology in a specific domain. An ontology engineering methodology describes a pro-cess of constructing ontologies including requirements gathering, development, refinement, repository management and evaluation.

2.6.1 Skeletal Methodology

Skeletal Methodology is a generic model for ontology engineering suggested by Uschold and King [1995], that is used as a foundation in most ontology engineering methodologies. It describes ontology development steps as: (i) Identifying purpose and scope, (ii) Constructing the ontology in three phases of capturing, coding and integrating existing ontologies, (iii) Evaluation and (iv) Documentation.

2.6.2 Formal Method for Ontology Engineering

Formal method for ontology engineering is presented by Gr¨uninger and Fox [1995] which was used for building an enterprise model. Its process includes five phases that are described below.

1. Apply Motivation Scenarios: The requirements are gathered from analysis of the application scenarios.

2. Define Competency Questions: A set of competency questions from the given motivation scenarios are identified.

3. Formalise Ontology: The first order logic of the ontology and the related axioms are specified.

4. Apply Competency Questions: Competency questions for the evaluation purposes are applied.

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5. Verify Ontology Completeness: It is determined whether the ontology satisfies a given competency question using a set of instances as the ground literals.

Although formal method encourages the use of formal logic, there are, however, several limitations with this approach outlined by Yu et al. [2009] including:

1. Expertises are required with an ontology specification language for formal logic expres-sions.

2. This method is depended on the existence of a given set of instances for addressing the competency questions.

3. This method is also limited to the use of an evaluation method with a formal logic language only.

Despite these limitations, formal method provides a starting point of ontology evaluation through using a set of competency questions which is followed in other ontology engineering approach that are described next.

2.6.3 On-To-Knowledge Methodology

On-To-Knowledge is presented by Staab et al. [2001b] as an on ontology development for knowledge management applications. The methodology includes five steps as follows.

1. Feasibility Study identifies foreseeable problem areas and possible solutions prior to the ontology development process are identified.

2. Kickoff describes ontology requirements including goals, scope, users, use cases, com-petency questions and possible existing ontologies.

3. Refinement develops the ontology according to the specification document.

4. Evaluation tests the ontology against competency questions until the ontology reaches a level of satisfaction.

5. Maintenance reflects changes and accommodating updates after the ontology has been in use for a period of time.

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An advantage of this approach compared with the Skeletal methodology [Uschold and King, 1995] is that the documentation step is applied at the early stage of ontology devel-opment rather than near the end as the Skeletal methodology suggests. It is also used as the reference throughout the ontology engineering lifecycle. Furthermore, another benefit of this aspect is its cyclical process that allows reflecting changes and accommodating updates until a level of maturity is reached. The major limitation of this approach is that the on-tology engineer decides on the metrics or experiments to be used to evaluate the onon-tology.

This is problematic because it may vary from one application to another. Hence, there is no systematic or standardized method for determining metrics for evaluating and comparing ontologies.

2.6.4 SENSUS-based Ontology Methodology

Hovy [2002] develops an ontology engineering methodology based on the SENSUS ontology which excludes irrelevant concepts outside of a given domain and enables the output ontology to be extended and modelled additional domain knowledge. The steps are:

1. Identify seed terms.

2. Manually Link seed terms to SENUS ontology.

3. Add paths and roots to the ontology.

4. Add new domain terms to the ontology that are not already presented.

5. Add the complete subtree of new nodes for the extended model.

The advantage of this ontology is grounding domain ontologies with the SENSUS ontol-ogy. This method, however is not considered a complete procedure, as it does not discuss any steps for evaluation or documentation.

2.6.5 METHONTOLOGY

METHONTOLOGY is presented by G´omez-P´erez et al. [2004] for ontology development in the domain of chemicals. This method include three major steps as shown Figure 2.2:

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Control   Quality  Assurance   Specifica4on     • Iden&fying  purpose,   level  of  formality  and   scope  of  the  ontology   with  the  aid  of   Ontology   Requirement   Specifica&on   Document.  

Conceptualisa4on   • Building  the  Glossary  of   Terms  (GT)  consis&ng   of  concepts  (verbs),   proper&es  (aGributes)   and  instances  based  on   the  outcome  of   knowledge  acquisi&on   phase  from  support   ac&vi&es.  

Formalisa4on   • Choosing  the  most   appropriate  terms   and  defini&ons  for   the  GT  using  meta-­‐ ontologies  and   related  libraries.  

Implementa4on   • Selec&ng  a  suitable   environment  to   implement  the  GT  in  a   suitable  machine-­‐ processable  language.  

Maintenance   • Versioning  the   ontology   development   process  by  keeping   the  record  of   changes  in  design   decisions.   Knowledge  Acquisi4on   Integra4on   Evalua4on

   

Documenta4on   Configura4on  Management   Management     Ac4vi4es   Performing    interviews  with  experts  and  text  analysis  to  capture  the  key  informa&on  of  the  domain  knowledge.   Comparing  and  integra&ng  exis&ng  ontologies  used  in  similar  domains  with  the  GT  designed  in  the  conceptualiza&on  ac&vity.   Evalua&ng  the  ontology  using  varying  evalua&on  approaches  and  defining  specific  criteria  to  verify  the  ``correctness''  of  the  ontology.   Keeping  record  of  a  summary  of  design  principles,  challenges  and  refinement  aSer  comple&on  of  each  development  ac&vity.   Rela&ng  to  management  ac&vi&es  that  consists  of  arranging  different  seUngs  for  beGer  control  of  the  resources.    

Development     Ac4vi4es   Support     Ac4vi4es   Figure2.2:METHONTOLOGY[G´omez-P´erezetal.,2004]OverviewAdaptedfrom[Corchoetal.,2005]

Ontology Design Patterns 29

1. Management activities are conducted at the start of the ontology development pro-cess, to identify the tasks to be performed, and the time and the resources required for their completion. Examples in this phase include control and quality assurance activities.

2. Development activities shape the basis of the ontology. Ideally these are conducted through small incremental and iterative cycles. Under the detection of any changes or mistakes, it is possible to return to any previous activities and make modifications and refinements. The development activities are: Specification, Conceptualization, Formalization, Implementation and Maintenance.

3. Support activities are carried out simultaneously with the development process ac-tivities. These activities include Knowledge Acquisition, Evaluation, Documentation and Configuration.

We have chosen this method to develop the ontology for sustainability indicator sets in this thesis. Our rational for this choice are described in Section 3.1.1.