which knowledge can be encoded and is transmittable in language
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Answer:
Knowledge representation languages
For ontologies to be used within an application, the ontology must be specified, that is, delivered using some concrete representation. This is the encoding step described above. There are a variety of languages which can be used for representation of conceptual models, with varying characteristics in terms of their expressiveness, ease of use and computational complexity. The field of knowledge representation (KR) has, of course, long been a focal point of research in the Artificial Intelligence community [29]- here we simply outline some of the KR languages which have been used for ontologies in bioinformatics (see Table 1).
Major considerations in the choice of representation are the expressivity of the encoding language, the rigour of an encoding and the semantics of a language:
The expressivity of an encoding language is a measure of the range of constructs that can be use to formally, flexibly, explicitly and accurately describe the components of an ontology as set out in Section 2. For example, first order logic is very expressive. However, there is a trade-off between expressivity (what you can say) and complexity (whether the language is computable in real time).
The rigour of an encoding is a measure of the satisfiability and consistency of the representation within the ontology. A model is satisfiable if none of the statements within contradict each other (e.g., an Enzyme is a protein which catalyses Reaction and Protein which notCatalyses Reaction would be contradictory). Consistency within an ontology is a matter of encoding the conceptualisation of the knowledge in the same manner throughout the ontology. The rigour of an ontology's representational scheme should be maintained by the systematic enforcement of mechanisms using the ontology, which ensures the uniform and universal interpretation of the ontology. Rigour can be maintained computationally via logic based systems or by the skill of the human encoder. Obviously, in the latter case, mistakes are more easily made and confidence in re-use of the ontology by other developers would be reduced.
The semantics of a language refers to the fact that it is unambiguously what the language means. For example, the language construct `A subconcept-of B' - does this mean that all the instances of A are also instances of B, or parts of B, or special kinds of B? Just because two languages use the same syntax does not mean they intend the same meaning. Clearly defined and well-understood semantics are essential if the ontology is to be used within the bioinformatics community for exchange of information. The definition of a general exchange language for ontologies is the subject of much current effort in the ontology research community [30].
Languages currently used for specifying bio-ontologies fall into three kinds: vocabularies defined using natural language; object-based knowledge representation languages such as frames and UML, and languages based on predicates expressed in logic such as Description Logics.
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