Domain-Specific Ontology

해석이 이상하더라도 참고.보세요..철학자들이 하는 말이라 힘드네요.

What is ontology in information systems?
Ontology is the study of 'what there is.' An ontology written by a philosopher can be described as...

(온톨로지의 개념은 원래 철학자들이 정의를 했죠..^^;)

"... a particular system of categories accounting for a certain vision of the world. As such, this system does not depend upon a particular language: Aristotle's ontology is always the same, independently of the language used to describe it." (Guarino 1998)

이 세상의 어떤 비전(관찰..)으로 분류된 특정한 시스템(체계). 그런거와 같이 이 시스템(체계)은 특정한 언어에 의존되지 않는다. 아리스토텔레스의 온톨로지는 그것(어떤한 시스템)을 기술(묘사)하기 위해 사용된 언어는 독립적이면서도(모 다른 언어를 사용하더라도) 항상 (의미가)같다. (해석이 맞는지.어렵다)

An ontology describes what is fundamental in 'what there is' or 'what is real'. It defines the terms used to construct a description of reality in its most general sense and how the terms are related. It must be able to describe a reality without specifying particulars of any category. It must be able to be used to describe reality at any point in time (either well into the future, or into the past). A high-level philosophical ontology must be able to describe reality in this way.

"[Ontology is t]he study of being in so far as this is shared in common by all entities, both material and immaterial. It deals with the most general properties of beings in all their different varieties" (Kim and Sosa 1995)

"Metaphysics can also be understood in a more definite sense, suggested by Aristotle's notion (in his Metaphysics, the title of which was given by an early editor of his works, not by Aristotle himself) of "first philosophy," namely, the study of being qua being, i.e. of the most general and necessary characteristics anything must have in order to count as being an entity (ens). Sometimes 'ontology' is used in this sense, but this is by no means common practice, 'ontology' being often used as a synonym for metaphysics" (Audi 1995)

For our purposes, we find the following definition most helpful, and I adopt it in my work:
Reference Ontology

"Ontology, understood as a branch of metaphysics, is the science of being in general, embracing such issues as the nature of existence and the categorical structure of reality. ... Different systems of ontology propose alternative categorical schemes. A categorical scheme typically exhibits a hierarchical structure, with 'being' or 'entity' as the topmost category, embracing everything that exists." (Honderich 1995)
온톨로지는 형이상학(metaphysics)적 학문의 한 분야로써 이해한다. 온톨로지는 일반적으로 본질(being)의 과학이다. 리얼리티의 분류된 구조와 자연의 본성과 같은 이슈를 포용한다. 온톨로지의 다른 체계는 대체적인 분류된 주제를 제안한다. 분류된 주제는 전형적으로 계측적인 구조를 보인다.(이 의미는 OWL에서는 클래스와 클래스, 속성과 속성과의 관계를 subClassOf, subPropertyOf로 나타내죠^^)

Ontology of this nature represents a framework using which the building blocks of reality are described, in a way that is divorced from any specific situation or state of affairs. This agrees with Guarino's definition we gave earlier. It encompasses everything that exists but is general.

In contrast, other parts of informatics, notably but not restricted to artificial intelligence (AI) (Vickery 1997; Vet and Mars 1998) and more generally, computer scientists use ontology in a highly pragmatic way. This is known as:

Domain-specific Ontology

"[o]n the other hand, in its most prevalent use in AI, an ontology refers to an engineering artifact, constituted by a specific vocabulary used to describe a certain reality, plus a set of explicit assumptions regarding the intended meaning of the vocabulary words." (Guarino 1998)
다른 한편으로, 온톨로지의 대부분 개념은 인공지능에서 사용한다. 온톨로지는 특별한 어휘을 구성하는 공학 인공물에서 참조한다. 그 어휘는 어떤한 리얼리티를 묘사에 의해 사용된다. 덧붙혀서 어휘 단어들이 의미하는 복잡한 가정의 집합이다.

For example, microeconomics, or a specific plant taxonomy each has its own categories of terms and intended meaning for terms used in these fields.

To help clarify the distinction between the two meanings Guarino finds in computing, he continues by saying:

"[t]he two readings of 'ontology'... are indeed related [to] each other, but in order to solve the terminological impasse we need to choose one of them, inventing another name for the other: we shall adopt the AI reading, using the word conceptualization to refer to the philosophical reading. Specifically, two ontologies can be different in the vocabulary used (using English or Italian words, for instance) while sharing the same conceptualization." (sic) (Guarino 1998)

Many, in line with philosophy maintain the term 'reference' ontology for the philosophical meaning and use 'domain-specific' ontology for this latter much more recently adopted term. However, the two should be, and are, related. A sensibly constructed domain-specific ontology should map back to a reference or philosophical ontology. Also each may be used to specify specific members of categories that account for a specific reality.

Let's consider examples. A 'reference' ontology has extremely general terms (individual, attributes, class, set, etc.) and describes reality 'in its most general sense'. A 'domain specific' ontology, while not necessarily committing to specific instances of the ontology (you, me, my cat) it may commit to categories such as 'pet', 'bridge', 'animal', 'election campaign' and also remain broad in its coverage of reality. It is clearly becoming more specific but without committing to specific individuals but it is not, in its fullest definition, general enough to 'stand the test of time' (there was a time when bridges didn't exist).

Some 'domain specific' ontologies are expressed in terms of a 'reference ontology' but some have grown 'bottom up' without a deep consideration of the upper most categories. A domain specific ontology is also likely to be restricted in the breadth of reality it describes, such as ontologies restricted to 'engineering', or 'medicine'. Finally, we may be able to commit ourselves to actual members of each category (you, me, and my cat). This specificity of reality is not of interest to us.

We can represent these ideas diagrammatically and see the definition of ontology stratified as we have described above.
A stratification of 'ontology' philosophical (Reference), computer science (Domain-specific) and Specific reality.

In the data modelling world, a reference ontology can be understood as a data modelling language such as a crude object model consisting of 'objects' that are described using 'properties' and where relationships relate objects with one another. A domain-specific ontology is paralleled in data modelling by a data model, for example consistent with the crude object model, showing a university with entities such as 'department', or 'faculty', and 'examination' with abstracted relationships between the entities. An example of a specific reality would commit to student 'Tony Blair' and subject 'AKA100 International Politics 1'. A domain specific ontology may extend to a certain reality such as this. In data modelling, the language used commits to a reference ontology and we want to examine this commitment in more detail. However, it can be said that in AI not all domain specific ontologies map back to coherent reference models. Some highly pragmatic examples of domain specific ontologies (such as CYC and Semantic Web) do not attempt to define high-level categories that are philosophically consistent.

There are correspondingly several levels at which ontologies can be computationally applied. Firstly, at the level of specific reality, various logical conclusions may be derived based on that specific reality. At the level of domain specific reality, discussions of the relationship between categories and the sorts of specific states of affairs that may exist can be carried out computationally. Finally, at the highest reference level, logical conclusions can be drawn about the veracity and effectiveness of the ontological commitments contained at that level.

In researching data modelling languages it is reference ontology that is of interest.)

[원문] http://www.dis.unimelb.edu.au/staff/simonm/ontology.htm