Please use this identifier to cite or link to this item: http://theses-test.ncl.ac.uk:8080/jspui/handle/10443.1/4025
Title: a Developing a risk communication and decision making modelling framework for system designers
Authors: Nesbitt, Daniel John
Issue Date: 2017
Publisher: Newcastle University
Abstract: Risk communication defines the process of exploring the likelihood of an understandable event occurring. Shared decision making is the process where participants of different levels of expertise discuss and come to an agreed decision. A shared decision making scenario may involve risk communication. Depending on the scenario, a decision support tool may be desired to help visualise, communicate and potentially reduce the likelihood of an adverse event occurring. As part of the development process for decision support tools, the developer should understand the problem domain that the support tool aims to resolve. One approach for understanding the problem domain is to develop a workflow model that visualises the activities and conditions that a decision making scenario has. While decision making processes and user interactions can be well discovered by using data elicitation methods, subjective data from the elicitation process poses challenges when attempting to use such data in a workflow model. For example, the order activities a person does may be inconsistent, or subject to change depending on their subjective preferences. This thesis discusses the development of tools and strategies for producing workflow models of decision making activities with qualitative and subjective data. Firstly, we discuss the development of BPMNdm (Business Process Modelling Notation – decision making), an extended workflow modelling notation to support the encapsulation of decision making activities. Secondly, we discuss how qualitative data produced using ethnographic method like participant observation can be transformed into a set of rules to encapsulate low level interaction activities between participants. Thirdly, we discuss how subjective data can be expressed as a triangular fuzzy number, which preserves the subjective nature of the data while allowing the data to be used to control the workflow model.
Description: PhD Thesis
URI: http://hdl.handle.net/10443/4025
Appears in Collections:School of Computing Science

Files in This Item:
File Description SizeFormat 
Nesbitt, D.J. 2017.pdfThesis4.09 MBAdobe PDFView/Open
dspacelicence.pdfLicence43.82 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.