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For 'concept', see Concept (disambiguation)

In information science a conceptualization is an abstract simplified view of some selected part of the world, containing the objects, concepts, and other entities that are presumed of interest for some particular purpose and the relationships between them. An explicit specification of a conceptualization is an ontology, and it may occur that a conceptualization can be realized by several distinct ontologies. An ontological commitment in describing ontological comparisons is taken to refer to that subset of elements of an ontology shared with all the others. "An ontology is language-dependent", its objects and interrelations described within the language it uses, while a conceptualization is always the same, more general, its concepts existing "independently of the language used to describe it". The relation between these terms is shown in the figure to the right.

Not all workers in knowledge engineering use the term ‘conceptualization’, but instead refer to the conceptualization itself, or to the ontological commitment of all its realizations, as an overarching ontology.

Purpose and implementation

As a higher level abstraction, a conceptualization facilitates the discussion and comparison of its various ontologies, facilitating knowledge sharing and reuse. Each ontology based upon the same overarching conceptualization maps the conceptualization into specific elements and their relationships.

The question then arises as to how to describe the 'conceptualization' in terms that can encompass multiple ontologies. This issue has been called the 'Tower of Babel' problem, that is, how can persons used to one ontology talk with others using a different ontology? This problem is easily grasped, but a general resolution is not at hand. It can be a 'bottom-up' or a 'top-down' approach, or something in between.

However, in more artificial situations, such as information systems, the idea of a 'conceptualization' and the 'ontological commitment' of various ontologies that realize the 'conceptualization' is possible. The formation of a conceptualization and its ontologies involves these steps:

• specification of the conceptualization
• ontology concepts: every definition involves the definitions of other terms
• relationships between the concepts: this step maps conceptual relationships onto the ontology structure
• groups of concepts: this step may lead to the creation of sub-ontologies
• formal description of ontology commitments, for example, to make them computer readable

An example of moving conception into a language leading to a variety of ontologies is the expression of a process in pseudocode (a strictly structured form of ordinary language) leading to implementation in several different formal computer languages like Lisp or Fortran. The pseudocode makes it easier to understand the instructions and compare implementations, but the formal languages make possible the compilation of the ideas as computer instructions.

Another example is mathematics, where a very general formulation (the analog of a conceptualization) is illustrated with 'applications' that are more specialized examples. For instance, aspects of a function space can be illustrated using a vector space or a topological space that introduce interpretations of the 'elements' of the conceptualization and additional relationships between them but preserve the connections required in the function space.

See also

• Knowledge representation and reasoning
• Ontology alignment
• Ontology (computer science)
• Semantic integration
• Semantic matching
• Semantic translation

References

1. Cite error: The named reference CZ was invoked but never defined (see the help page).
2. ^ Gruber, Thomas R. (1993). "A translation approach to portable ontology specifications" (PDF). Knowledge Acquisition. 5 (2): 199–220. {{cite journal}}: Unknown parameter |month= ignored (help)
3. ^ Barry Smith (2003). "Chapter 11: Ontology". In Luciano Floridi, ed (ed.). Blackwell Guide to the Philosophy of Computing and Information (PDF). Blackwell. pp. 155–166. ISBN 0631229183. {{cite book}}: |editor= has generic name (help)
4. Roger F. Gibson (1999). "Ontological commitment". In Robert Audi, ed (ed.). The Cambridge Dictionary of Philosophy (Paperback 2nd ed.). p. 631. ISBN 0521637228. {{cite book}}: |editor= has generic name (help) A shortened version of that definition is as follows:

   The ontological commitments of a theory are those things which occur in all the ontologies of that theory. To explain further, the ontology of a theory consists of the objects the theory makes use of. A dependence of a theory upon an object is indicated if the theory fails when the object is omitted. However, the ontology of a theory is not necessarily unique. A theory is ontologically committed to an object only if that object occurs in all the ontologies of that theory. A theory also can be ontologically committed to a class of objects if that class is populated (not necessarily by the same objects) in all its ontologies.

5. Luigi Ceccaroni, Myriam Ribiere (2002). "Modeling utility ontologies in agentcities with a collaborative approach" (PDF). Proceedings of the workshop AAMAS. A quotation follows:

   “Researchers...come from different areas of study and have different perspectives on modeling, but significantly they pledged to adopt the same ontological commitment. That is, they agree to adopt common, predefined ontologies...to express general categories, even if they do not completely agree on the modeling behind the ontological representations. Where ontological commitment is lacking, it is difficult to converse clearly about a domain and to benefit from knowledge representations developed by others... Ontological commitment is thus an integral aspect of ontological engineering.”

6. ^ Nicola Guarino (1998). "Formal Ontology in Information Systems". In Nicola Guarino, ed (ed.). Formal Ontology in Information Systems (Proceedings of FOIS '98, Trento, Italy). IOS Press. pp. 3 ff. ISBN 978-90-5199-399-8. {{cite book}}: |editor= has generic name (help)
7. ^ For example, see Luigi Ceccaroni, Myriam Ribiere (2002). "Modeling utility ontologies in agentcities with a collaborative approach" (PDF). Proceedings of the workshop AAMAS.
8. ^ Frank van Harmelen. "Ontology mapping: a way out of the medical tower of babel" (PDF).
9. In information science, one approach to finding a conceptualization (or avoiding it and using an automated comparison) is called 'ontology alignment' or 'ontology matching'. See for example, Jérôme. Euzenat, Pavel Shvaiko (2007). Ontology Matching. Springer. ISBN 3540496122.
10. Nicola Guarino, Massimiliano Carrara, Pierdaniele Giaretta (1994). "Formalizing ontological commitments" (PDF). AAAI. 94: 560–567.{{cite journal}}: CS1 maint: multiple names: authors list (link)
11. Maja Hadzic, Pornpit Wongthongtham, Elizabeth Chang, Tharam Dillon (2009). "Chapter 7: Design methodology for integrated systems - Part I (Ontology design)". Ontology-Based Multi-Agent Systems. Springer. pp. 111 ff. ISBN 364201903X.{{cite book}}: CS1 maint: multiple names: authors list (link)

Further reading

• G Guizzardi (2007). "On Ontology, ontologies, conceptualizations, modeling languages and (meta)models". In Olegas Vaselicas, Johan Edler, Albertas Caplinskas, eds (ed.). Frontiers in artificial intelligence and applications, databases and information systems IV (PDF). IOS Press. ISBN 978-1-58603-715-4. {{cite book}}: |editor= has generic name (help)CS1 maint: multiple names: editors list (link)
• Katherine Munn, Barry Smith, ed. (2008). Applied ontology: an introduction. Ontos Verlag. ISBN 3938793988.

External links

• Marek Obitko (2006–2007). "Specification of conceptualization". Ontologies and the semantic web.{{cite web}}: CS1 maint: date format (link)

This article incorporates material from the Citizendium article "Conceptualization (information science)", which is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License but not under the GFDL.

• Information science
• Ontology
• Knowledge engineering
• Knowledge representation
• Ontology (information science)
• Semantic Web
• Technical communication