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Ontology Development Methods

Ontology Development Methods. Semantic web technology. Uschold & King Ontology Development Method. Uschold and King define ontology as a process, which can again be broken down into a number of smaller steps: 1. Identification of the key concepts and relationships in the domain of interest

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Ontology Development Methods

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  1. Ontology Development Methods Semantic web technology

  2. Uschold & King Ontology Development Method • Uschold and King define ontology as a process, which can again be broken down into a number of smaller steps: 1. Identification of the key concepts and relationships in the domain of interest 2. Production of precise, unambiguous text definitions for such concepts and relationships 3. Identification of terms to refer to such concepts and relationships 4. Achieving community agreement on all of the above

  3. 1. Identification of the key concepts and relationships in the domain of interest • For the initial stages of the ontology capture process, Uschold and King recommend a brainstorming phase, which should produce all relevant concepts and relationships the ontology should contain. At this stage, concepts are represented by terms (labels) which my hide differences in interpretation and understanding of fundamental concepts. • The authors point out that while brainstorming works well, it may have to be supplemented with other sources of information if domain expertise is required.

  4. 2. Production of precise, unambiguous text definitions for such concepts and relationships • In a second step then, the identified concepts should be arranged into “work areas corresponding to naturally arising sub-groups”. To decide whether a term should be included or excluded from a grouping and the ontology in general, a reference should be made to the requirements specification of the ontology. • The authors thus underline again the vital importance of the availability of such a document. They also recommend, that inclusion or exclusion decisions be documented for future reference. • Finally, it is recommended that “semantic cross-references” be identified which link concepts in one group to those of another group

  5. 3. Identification of terms to refer to such concepts and relationships • In a third step in the capture process, Uschold and King recommend the identification of meta-ontologies which may be suitable for the particular domain ontology to be constructed, without making a firm ontological commitment. • They recommend that a consideration of the concepts in the domain ontology and their interrelationships guide the choice of a meta-ontology.

  6. 4. Achieving community agreement on all of the above • In a fourth step, precise definitions of all terms and concepts in the ontology should be produced. Definitions for concepts which have a maximum semantic overlap between work areas should be produced first, as these are more likely to be the most important concepts and it is important to get these definitions right in the first instance. • Uschold and King advocate to focus initially on the definition of cognitively basic terms as opposed to more abstract ones, as this should facilitate the process of relating terms in different areas. To develop the definitions, precise natural language text definitions of all terms be produced, while taking great care to ensure consistency with other terms which are already in use. • The introduction of new terms to be avoided at this stage. The provision of examples is considered to be helpful.

  7. Toronto Virtual Enterprise Method • The TOVE project, acronym of TOronto Virtual Enterprise project is a project to develop an ontological framework for enterprise integration (EI) based on and suited for enterprise modelling. • The original goal of the project was fourfold: • Create a shared representation or ontology of the enterprise that each agent in the distributed enterprise can jointly understand and use • Define the meaning of each description or semantics • Implement the semantics in a set of axioms that will enable TOVE to automatically deduce the answer to many "common sense" questions about the enterprise • Define a symbology for depicting a concept in a graphical context

  8. Toronto Virtual Enterprise Ontologies

  9. The first goal is approached by defining a reference model for the enterprise. A reference model provides a data dictionary of concepts that are common across various enterprises, such as products, materials, personnel, orders, departments, etc. It provides a common model before the creation of an enterprise-specific model. The second goal is approached by defining a generic level representation in which the application representations are defined in terms of. The generic level, is in turn, defined by a conceptual level based on the ‘terminological logic’ of the Enterprise. We approach the third goal by defining at each level of the representation, generic and application, a set of axioms that define common-sense meanings for the terminology.

  10. Methontology • METHONTOLOGY is among the more comprehensive ontology engineering methodologies as it is one for building ontologies either from scratch, reusing other ontologies as they are, or by a process of re-engineering them. • The framework enables the construction of ontologies at the knowledge level, i.e., the conceptual level, as opposed to the implementation level. • It consists of: identification of the ontology development process with the identification of the main activities, such as, evaluation, configuration, management, conceptualization, integration implementation; a life cycle based on evolving prototypes; and the methodology itself specifying the steps for performing the activities, the techniques used, the outcomes and their evaluation.

  11. 1. Specification • The goal of the specification phase is to produce either an informal, semi-formal or formal ontology specification document written in natural language, using a set of intermediate representations or using competency questions, respectively. METHONTOLOGY proposes that at least the following information be included: • a) The purpose of the ontology, including its intended uses, scenarios of use, end-users, etc. • b) Level of formality of the implemented ontology, depending on the formality that will be use to codify the terms and their meaning. Uschold (Uschold Gruninger 1996) classifies the degree or level of formality in a range of: highly informal, semi-informal, semi-formal or rigorously formal ontologies, depending on whether terms and their meanings are codified in a language between natural language and a rigorous formal language. • c) Scope, which includes the set of terms to be represented, its characteristics and granularity

  12. 2. Knowledge Acquisition • Experts, books, handbooks, figures, tables and even other ontologies are sources of knowledge from which the knowledge can he elucidated using in conjunction techniques such us: brainstorming, interviews, formal and informal analysis of texts, and knowledge acquisition tools. • For example, if you have no a clear idea of the purpose of your ontology, brainstorming technique, informal interviews with experts, and inspecting similar ontologies will allow you to elaborate a first glossary with terms potentially relevant. To refine the list of terms and their meaning, formal and informal analysis of text techniques in books and handbooks in conjunction with structured and non-structured interviews with experts might be used to include or remove terms in the glossary. Interviews to expert might help you to build concepts classifications trees and to contrast them against figures given in books.

  13. 3. Conceptualization • In this activity, you will structure the domain knowledge in a conceptual model that describes the problem and its solution in terms of the domain vocabulary identified in the ontology specification activity. The first thing to do is to build a complete Glossary of Terms (GT). Terms include concepts, instances, verbs and properties. So, the GT identifies and gathers all the useful and potentially usable domain knowledge and its meanings. • Once you have almost completed the GT, you must group terms as concepts and verbs. Each set of concepts/verbs would include concepts/verbs that are closely related to other concepts/verbs inside the same group as opposed to other groups.

  14. After they have been built, you can split your ontology development process into different, but related, teams. Set of Intermediate Representations in the conceptualization phase.

  15. 4. Integration • With the goal of speeding up the construction of your ontology, you might consider reuse of definitions already built into other ontologies instead of starting from scratch. In this case, we propose the following: • I. Inspect meta-ontologies to select those that better fit your conceptualization. The goal is to guarantee that the sets of new and reused definitions are based upon the same set of basic terms. If existing meta-ontologies are not appropriate for your ontology, you should start the definition and implementation of a new meta-ontology in a formal language. • 2. Whether or not you reuse existing meta-ontologies, the next step is to find out which libraries of ontologies provide definitions of terms whose semantic and implementation is coherent with the terms identified in your conceptualization. Once you have chosen the most appropriate terms, if the meta-ontology upon which those terms have been built is different of the meta-ontology used to build the yours, you should check the existence of translators to transform definitions into your target language.

  16. An example of an integration document

  17. 5. Implementation • Ontologies implementation requires the use of an environment that supports the meta-ontology and ontologies selected at the integration phase. The result of this phase is the ontology codified in a formal language such us: CLASSIC, BACK, LOOM, Ontolingua, Prolog, C++ , etc. • Any ontology development environment should provide, at least: • a lexical and syntactic analyser to guarantee the absence of lexical and syntactic errors; • translators, to guarantee the portability of the definitions into other target languages; • an editor, to add, remove or modify definitions; a browser, to inspect the library of 38 ontologies and their definitions; • a searcher, to look for the most appropriate definitions; • evaluators, to detect incompleteness, inconsistencies and redundant knowledge: • an automatic maintainer, to manage the inclusion, removal or modification of existing definitions, and so on.

  18. 6. Evaluation • Evaluation means to carry out a technical judgment of the ontologies, their software environment and documentation with respect to a frame of reference (in our case the requirements specification document) during each phase and between phases of their life cycle • The output proposed by METHONTOLOGY for this activity is many evaluation documents in which the ontologist will describe how the ontology has been evaluated, the techniques used, the kind of errors found in each activity, and the sources of knowledge used in the evaluation.

  19. References • http://oa.upm.es/5484/1/METHONTOLOGY_.pdf • https://www.researchgate.net/publication/221049035_The_TOVE_Project_Towards_a_Common-Sense_Model_of_the_Enterprise • https://en.wikipedia.org/wiki/TOVE_Project • https://semanticscience.wordpress.com/2007/11/28/ontology-development-methodologies-uschold-and-king/

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