| GeneralDescription
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A non-ontological resource holds a term-ba … A non-ontological resource holds a term-based thesaurus which follows the record-based model.
A thesaurus represents the knowledge of a domain with a collection of terms and a limited set of relations between them. The record-based data model is a denormalized structure, uses a record for every term with the information about the term, such as synonyms, broader, narrower and related terms. nyms, broader, narrower and related terms.,
The generated ontology will be based on th … The generated ontology will be based on the lightweight ontology architectural pattern (AP-LW-01). Each thesaurus term is mapped to a class. For the disambiguation of the semantics of the BT, NT and RT relations among thesaurus terms the pattern relies on an external resource. In the case of that the external resource does not provide any relation between two terms, the pattern takes advantage of the use of logical patterns for asserting the relation partOf, subClassOf or relatedClass. For the UF/USE relations we use
the logical pattern proposed by Corcho et al. suggested as best practice in the
context of this antipattern: the tendency to declare two classes equivalent when in fact their labels simply express synonym. fact their labels simply express synonym.,
1. Identify the records which contain thes … 1. Identify the records which contain thesaurus terms without a broader term.
2. For each one of the above identified thesaurus terms ti:
2.1. Create the corresponding ontology class, Ci class, if it is not created yet.
2.2. Identify the thesaurus terms, tj , which are narrower terms of ti. They are
referenced in the same record which contains ti.
2.3. For each one of the above identified thesaurus term tj :
2.3.1. Create the corresponding ontology class, Cj class, if it is not created yet.
2.3.2. Using the external resource identify the semantics of the relation between Cj and Ci, and set up the relation identified.
2.3.3. Repeat from step 2.2 for cj as a new ci
2.4. Identify the thesaurus terms, tr, which are related terms of ti. They are referenced in the same record which contains ti.
2.5. For each one of the above identified thesaurus terms tr:
2.5.1. Create the corresponding ontology class, Cr class, if it is not created yet.
2.5.2. Using the external resource identify the semantics of the relation between Cr and Ci, and set up the relation identified.
2.5.3. Repeat from step 2.4 for cr as a new ci
2.6. Identify the thesaurus terms, tq, which are equivalent terms of ti. They are referenced in the same record which contains ti.
2.7. For each one of the above identified thesaurus terms tq:
2.7.1. Use the logical pattern proposed by Corcho et al.
2.7.2. Repeat from step 2.6 for cq as a new ci. . Repeat from step 2.6 for cq as a new ci.,
Suppose that someone wants to build a lightweight ontology based on the European Training Thesaurus (ETT), which is a term-based thesaurus and it follows the record-based model.,
The European Training Thesaurus (ETT) constitutes the controlled vocabulary of reference in the field of vocational education and training (VET) in Europe.,
The generated ontology will be based on th … The generated ontology will be based on the lightweight ontology architectural pattern (AP-LW-01). Each thesaurus term is mapped to a class. For the disambiguation of the semantics of the BT, NT and RT relations among thesaurus terms the pattern relies on an external resource. In the case of that the external resource does not provide any relation between two terms, the pattern takes advantage of the use of logical patterns for asserting the relation partOf, subClassOf or relatedClass. For the UF/USE relations we use the logical pattern proposed by Corcho et al. suggested as best practice in the context of this antipattern: the tendency to declare two classes equivalent when in fact their labels simply express synonym. fact their labels simply express synonym.,
1. Create the learning class and the perso … 1. Create the learning class and the personal development class.
2. Create the competence class.
3. Using the external resource identify the semantics of the relation between
competence and learning, and set up the relation identified.
4. Create the performance class.
5. Using the external resource identify the semantics of the relation between
performance and personal development, and set up the relation identified.
6. Assert that achievement is label of the performance class.
7. Using the external resource identify the semantics of the relation between
competence and performance, and set up the relation identified.
8. Create the skill class.
9. Using the external resource identify the semantics of the relation between skill and competence, and set up the relation identified.
9.1. Create the efficiency class.
9.2. Using the external resource identify the semantics of the relation between
efficiency and performance, and set up the relation identified.
9.3. Create the failure class.
9.4. Using the external resource identify the semantics of the relation between
failure and performance, and set up the relation identified.
9.5. Create the success class.
9.6. Using the external resource identify the semantics of the relation between
success and performance, and set up the relation identified. mance, and set up the relation identified.
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