Semantic and organization considerations in database conceptual modelling : the Semantic Conceptual Organizational Model (SECOM)

  • Abdalah Al-Shawi

    Student thesis: Doctoral ThesisDoctor of Philosophy


    This thesis presents a new approach to designing large organizational databases. The approach emphasizes the need for a holistic approach to the design process. The development of the proposed approach was based on a comprehensive examination of the issues of relevance to the design and utilization of databases. Such issues include conceptual modelling, organization theory, and semantic theory.
    The conceptual modelling approach presented in this thesis is developed over three design stages, or model perspectives. In the semantic perspective, concept definitions were developed based on established semantic principles. Such definitions rely on meaning - provided by intension and extension - to determine intrinsic conceptual definitions. A tool, called meaning-based classification (MBC), is devised to classify concepts based on meaning. Concept classes are then integrated using concept definitions and a set of semantic relations which rely on concept content and form. In the application perspective, relationships are semantically defined according to the application environment. Relationship definitions include explicit relationship properties and constraints. The organization perspective introduces a new set of relations specifically developed to maintain conformity of conceptual abstractions with the nature of information abstractions implied by user requirements throughout the organization. Such relations are based on the stratification of work hierarchies, defined elsewhere in the thesis. Finally, an example of an application of the proposed approach is presented to illustrate the applicability and practicality of the modelling approach.
    Date of AwardJun 1991
    Original languageEnglish
    SupervisorP.A. Golder (Supervisor)


    • database design
    • conceptual modelling
    • abstraction hierarchies
    • data semantics
    • large organizational databases

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