UBC Theses and Dissertations
A classification theory based information systems model Parsons, Byron Jeffrey
Information systems (IS) development is viewed as a process of transforming users' knowledge about some subject matter into a computer-based system which faithfully represents that knowledge. A critical step in this process is conceptual modelling - the development of an implementation-independent representation of the relevant knowledge. While the importance of conceptual modelling has gained increasing recognition, many existing conceptual models remain based on software, rather than knowledge, constructs. This research adopts the premise that a conceptual model should provide constructs for directly modelling knowledge. Since the subject matter of organizational IS is typically things in organizations, theories of concepts (classification), which deal with the structure and organization of knowledge about things, are an appropriate source of modelling constructs. A classical theory of concepts suggests five knowledge constructs - instance, property, concept, specialization, and composition. The thesis develops formal definitions of each of these constructs. The notion of direct correspondence is then used to define a conceptual information systems model called MIMIC, which contains a corresponding set of constructs - object, attribute, class, specialized class, and composite class. The model offers several contributions to conceptual modelling research and practice, including: 1)minimal requirements for a "good" class structure; 2)naturalness of a lattice structure for class organization; 3)refinements to the meaning of IS-A connections between classes in a lattice; 4)distinction between simple relationships and those which can be regarded as objects; 5)simple foundation for treating time in conceptual modelling; and 6)a normative model of objects under the assumption that a fundamental objective of the object paradigm of computing is to provide a set of natural modelling constructs. The value of the model is further illustrated by using it as a framework to evaluate several other conceptual modelling approaches. The results of this comparison indicate that, while other models do support cognitive constructs to varying degrees, each is weak in supporting some elements of the classical view of concepts. Finally, a detailed example is used to demonstrate the capability of the model for uniformly representing knowledge across several classes of applications.
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