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The purpose of my research was to test the hypothesis that examining a BN structure by visualisation and verbal explanation of relationships, independently of the numbers, helps in communicating and explaining the model and BN technology to DEs, and thus helps them in constructing a BN of their domains and in defining their understanding of their domains. More specifically, the aims of this research were to:
I designed a visual tool, based on the concepts of the materialisation of the proposed approach, in order to evaluate this approach. The tool, called V-NET, supports the comparison between the structural assumptions of the domain and the graphical modelling decisions. It operates on the graph structure and helps reveal potential misrepresentation of the domain by the graph. The tool has a window interface and uses the structure as the main display. V-NET allows the user to choose nodes and then to choose one of several types of independencies to be displayed. Upon request, V-NET visualises the answer by highlighting the appropriate nodes and displays a verbal explanation of the situation.
Note: There are four different evaluation or assessment processes in this thesis, for which we use the given associated terms:
Evaluating the domain concepts and relationships: Structural assumptions (building ontology).
Evaluating the structural assumptions in order to construct the graph: Graphical modelling (This is based on the structural assumptions but also includes other considerations such as graph complexity, explanatory power, and parameters availability).
Evaluating the “quality” of a constructed graph: Assessment of the graph.
Evaluating the tool: Evaluation.
In order to answer my specific research questions I evaluated the performance of the tool using case studies for qualitative evaluation, employing three different methods of data collection: ‘evaluation’ of the tool using it myself, ‘structured interview’ and ‘unstructured interview’.
These methods were applied in three different settings in order to examine the feasibility of reducing the involvement of a BN expert in the process of KE of a model, and to test different aspects of the KE process.
In the first setting, I assessed so called ‘Toy-Nets’ developed by students as an assignment in a graduate level university course on BNs, as a ‘reality check’. In this setting, I (the BN expert, an ‘outsider’) examined networks designed by others.
In the second setting, a DE analysed his ‘real life’ elicited BN structure that he had previously constructed using V-NET, and answered a structured questionnaire (see Appendix 1) designed by myself (the BN expert). Hence, this setting involved primarily the DE and to some extent, a BN expert.
In the third setting a DE analysed a learnt network of her domain. In this setting the BN expert played only a minimal supportive role, whilst the DE had significant input into the assessment
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