Generic data model: Difference between revisions

Revision as of 02:32, 8 October 2008

Revision as of 01:30, 9 October 2008

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[[Image:HL7 Reference Information Model.jpg|thumb|360px|Example of a Generic data model.<ref> Amnon Shabo (2006). [http://www.hhs.gov/healthit/ahic/materials/01_07/phc/genomics.html Clinical genomics data standards for pharmacogenetics and pharmacogenomics].</ref>]]

'''Generic data model'''s are generalizations of conventional [[data model]]s. They define standardised general relation types, together with the kinds of things that may be related by such a relation type.

== Overview ==

ThisThe definition of generic data model is similar to the definition of a natural language. For example, a generic data model may define relation types such as a 'classification relation', being a [[binary relation]] between an individual thing and a kind of thing (a class) and a 'part-whole relation', being a binary relation between two things, one with the role of part, the other with the role of whole, regardless the kind of things that are related. Given an extensible list of classes, this allows the classification of any individual thing and to specify part-whole relations for any individual object. By standardisation of an extensible list of relation types, a generic data model enables the expression of an unlimited number of kinds of facts and will approach the capabilities of natural languages.

Conventional data models, on the other hand, have a fixed and limited ___domain scope, because the instantiation (usage) of such a model only allows expressions of kinds of facts that are predefined in the model.

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== References ==

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