UBC Theses and Dissertations
Ontological and cognitive principles on information systems modelling Saghafi, Arash
Information systems are representations or models of real-world applications. Based on this premise, success of an information system is contingent on how effectively and faithfully the representations are generated and interpreted by analysts and designers. Prior research has suggested using ontology — a branch of philosophy that deals with the order and structure of reality in the broadest sense — as guidance for the modelling process. It is expected that by improving the ontological expressiveness of conceptual models, they will become more faithful and effective representations of the real world. This thesis focuses on information models that are rooted in ontology and users’ performance of cognitive tasks when using such models. Following the three-study structure of doctoral theses, my first study synthesized the prior work that had empirically evaluated the impact of ontological guidance on users’ understanding of conceptual models. The analysis indicated a strong effect of ontological guidance on improving users’ understanding of the “conceptual domain models”, particularly for tasks that required a deeper level of understanding. This provides scientific evidence in favour of incorporating ontological guidance in education and in practice of systems analysis. My second and third studies investigated a data modelling approach that is based on ontological principles, namely the instance-based paradigm, which is an alternative to the traditional data management method. Unlike the traditional approach, the instance-based paradigm requires neither imposing pre-defined structure over the data nor central control/planning. Study 2 evaluated users’ performance in (the cognitive task of) information retrieval. It indicated that users of instance-based representations are able to formulate queries more accurately compared with users of class-based representations. Study 3 broadened the scope and focused on knowledge discovery and exploration of information (that was not necessarily created for the intended application). Results of a laboratory experiment demonstrated that users of instance-based data were able to identify more potentially interesting patterns compared with users of class-based data. With the current emphasis on information analytics and importance of incorporating insights from organizational data into decision-making, the latter two studies show that the instance-based model is a promising approach to satisfy the emerging needs of information users.
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