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One approach to generic data modeling has the following characteristics:

  • A generic data model shall consist of generic entity types, such as 'individual thing', 'class', 'relationship', and possibly a number of their subtypes.
  • Every individual thing is an instance of a generic entity called 'individual thing' or one of its subtypes.
  • Every individual thing is explicitly classified by a kind of thing ('class') using an explicit classification relationship.
  • The classes used for that classification are separately defined as standard instances of the entity 'class' or one of its subtypes, such as 'class of relationship'. These standard classes are usually called 'reference data'. This means that domain specific knowledge is captured in those standard instances and not as entity types. For example, concepts such as car, wheel, building, ship, and also temperature, length, etc. are standard instances. But also standard types of relationship, such as 'is composed of' and 'is involved in' can be defined as standard instances.

This way of modeling allows the addition of standard classes and standard relation types as data (instances), which makes the data model flexible and prevents data model changes when the scope of the application changes.

A generic data model obeys the following rules:

  1. Candidate attributes are treated as representing relationships to other entity types.
  2. Entity types are represented, and are named after, the underlying nature of a thing, not the role it plays in a particular context. Entity types are chosen.
  3. Entities have a local identifier within a database or exchange file. These should be artificial and managed to be unique. Relationships are not used as part of the local identifier.
  4. Activities, relationships and event-effects are represented by entity types (not attributes).
  5. Entity types are part of a sub-type/super-type hierarchy of entity types, in order to define a universal context for the model. As types of relationships are also entity types, they are also arranged in a sub-type/super-type hierarchy of types of relationship.
  6. Types of relationships are defined on a high (generic) level, being the highest level where the type of relationship is still valid. For example, a composition relationship (indicated by the phrase: 'is composed of') is defined as a relationship between an 'individual thing' and another 'individual thing' (and not just between e.g. an order and an order line). This generic level means that the type of relation may in principle be applied between any individual thing and any other individual thing. Additional constraints are defined in the 'reference data', being standard instances of relationships between kinds of things.

Examples of generic data models are ISO 10303-221, ISO 15926 and Gellish

Data organization

Another kind of data model describes how to organize data using a database management system or other data management technology. It describes, for example, relational tables and columns or object-oriented classes and attributes. Such a data model is sometimes referred to as the physical data model , but in the original ANSI three schema architecture, it is called "logical". In that architecture, the physical model describes the storage media (cylinders, tracks, and tablespaces). Ideally, this model is derived from the more conceptual data model described above. It may differ, however, to account for constraints like processing capacity and usage patterns.

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Source:  OpenStax, Data structures and algorithms. OpenStax CNX. Jul 29, 2009 Download for free at http://cnx.org/content/col10765/1.1
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