Design Science Research Methodology: An Artefact-Centric Creation and Evaluation Approach

Adaptation of the Design Science Research methodology has never been easy. There have always been concerns regarding the validity of design science and the evaluation of the artefacts generated therewith and the subsequent claims of the researchers. To address these problems we propose an artefact-centric creation and evaluation methodology for design science research. This methodology begins with observation which is followed by theory building which in turn is followed by an interwoven artefact creation and artefact evaluation process. The artefact creation process focuses on the creation of key artefacts that include conceptual models, processes, conceptual frameworks, system frameworks, architectures, and implementations. The artefact evaluation process is tightly interwoven with the artefact creation process and evaluates the artefacts independently as well as against prior artefacts that influenced their creation. In this paper we discuss in brief the application of this methodology to the ‘Sustainable Business Transformation’ design science research project

A formal framework of human–machine interaction in proactive maintenance – MANTIS experience

The general concept of MANTIS project is to provide a proactive maintenance service platform architecture that allows to monitor essential system parameters and schedule maintenance in order to predict and prevent imminent failures. Human–machine interaction (HMI) is an important integral part of the platform by providing the right information in the right modality to the users when needed. As MANTIS comprises 11 distinct industrial use cases, the design of such HMI presents a great challenge. The framework presented in this paper originates from the scenariobased design and can be treated as a part of the overall scenario-based usability engineering approach. The framework has been conceived from an extensive list of HMI features extracted from the descriptions of use-case scenarios provided by each industrial partner. Due to the broad range of representative industry environments including production asset maintenance, vehicle maintenance, energy production management and health equipment maintenance we believe that the resulting HMI framework can be applied in different cases in practice and the paper would also be of general interest to the readers

Development of a decision support system through modelling of critical infrastructure interdependencies : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand

Critical Infrastructure (CI) networks provide functional services to support the wellbeing of a community. Although it is possible to obtain detailed information about individual CI and their components, the interdependencies between different CI networks are often implicit, hidden or not well understood by experts. In the event of a hazard, failures of one or more CI networks and their components can disrupt the functionality and consequently affect the supply of services. Understanding the extent of disruption and quantification of the resulting consequences is important to assist various stakeholders' decision-making processes to complete their tasks successfully. A comprehensive review of the literature shows that a Decision Support System (DSS) integrated with appropriate modelling and simulation techniques is a useful tool for CI network providers and relevant emergency management personnel to understand the network recovery process of a region following a hazard event. However, the majority of existing DSSs focus on risk assessment or stakeholders' involvement without addressing the overall CI interdependency modelling process. Furthermore, these DSSs are primarily developed for data visualization or CI representation but not specifically to help decision-makers by providing them with a variety of customizable decision options that are practically viable. To address these limitations, a Knowledge-centred Decision Support System (KCDSS) has been developed in this study with the following aims: 1) To develop a computer-based DSS using efficient CI network recovery modelling algorithms, 2) To create a knowledge-base of various recovery options relevant to specific CI damage scenarios so that the decision-makers can test and verify several ‘what-if’ scenarios using a variety of control variables, and 3) To bridge the gap between hazard and socio-economic modelling tools through a multidisciplinary and integrated natural hazard impact assessment. Driven by the design science research strategy, this study proposes an integrated impact assessment framework using an iterative design process as its first research outcome. This framework has been developed as a conceptual artefact using a topology network-based approach by adopting the shortest path tree method. The second research outcome, a computer-based KCDSS, provides a convenient and efficient platform for enhanced decision making through a knowledge-base consisting of real-life recovery strategies. These strategies have been identified from the respective decision-makers of the CI network providers through the Critical Decision Method (CDM), a Cognitive Task Analysis (CTA) method for requirement elicitation. The capabilities of the KCDSS are demonstrated through electricity, potable water, and road networks in the Wellington region of Aotearoa New Zealand. The network performance has been analysed independently and with interdependencies to generate outage of services spatially and temporally. The outcomes of this study provide a range of theoretical and practical contributions. Firstly, the topology network-based analysis of CI interdependencies will allow a group of users to build different models, make and test assumptions, and try out different damage scenarios for CI network components. Secondly, the step-by-step process of knowledge elicitation, knowledge representation and knowledge modelling of CI network recovery tasks will provide a guideline for improved interactions between researchers and decision-makers in this field. Thirdly, the KCDSS can be used to test the variations in outage and restoration time estimates of CI networks due to the potential uncertainty related to the damage modelling of CI network components. The outcomes of this study also have significant practical implications by utilizing the KCDSS as an interface to integrate and add additional capabilities to the hazard and socio-economic modelling tools. Finally, the variety of ‘what-if’ scenarios embedded in the KCDSS would allow the CI network providers to identify vulnerabilities in their networks and to examine various post-disaster recovery options for CI reinstatement projects

Decision Maps for Distributed Scenario-Based Multi-Criteria Decision Support

This thesis presents the Decision Map approach to support decision-makers facing complex uncertain problems that defy standardised solutions. First, scenarios are generated in a distributed manner: the reasoning processes can be adapted to the problem at hand whilst respecting constraints in time and availability of experts. Second, by integrating scenarios and MCDA, this approach facilitates robust decision-making respecting multiple criteria in a transparent well-structured manner

Sistema de suporte à decisão espacial aplicado à análise da vulnerabilidade dos recursos hídricos na bacia Guapi-Macacu / RJ.

Dissertação (Mestrado em Engenharia de Computação) - Faculdade de Engenharia, Universidade Estadual do Rio de Janeiro, Rio de Janeiro, 2012. Orientadora: Margareth Simões Penello Meirelles, UERJ; Co-orientadora: Rachel Bardy Prado, CNPS