38 research outputs found

    Development and validation of a disaster management metamodel (DMM)

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    Disaster Management (DM) is a diffused area of knowledge. It has many complex features interconnecting the physical and the social views of the world. Many international and national bodies create knowledge models to allow knowledge sharing and effective DM activities. But these are often narrow in focus and deal with specified disaster types. We analyze thirty such models to uncover that many DM activities are actually common even when the events vary. We then create a unified view of DM in the form of a metamodel. We apply a metamodelling process to ensure that this metamodel is complete and consistent. We validate it and present a representational layer to unify and share knowledge as well as combine and match different DM activities according to different disaster situations

    Metamodelling Approach To Support Disaster Management Knowledge Sharing

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    Handling uncertain events that could happen anytime and anywhere and dealing with many complex systems interconnected physically and socially makes Disaster Management (DM) a multidisciplinary endeavor and a very difficult domain to model. In this paper we present a development and validation of a Disaster Management Metamodel (DMM), a language that we develop specific for describing DM domain. The metamodel, a precise definition of the constructs and rules needed for creating the semantic models of DM domain consists of four views based on four DM phases including Mitigation, Preparedness, Response and Recovery-phase classes of concept. A Model Importance Factor (MIF) criterion is used to identify 10 existing disaster management models to evaluate the expressiveness and the completeness of DMM. The paper presents the synthesis process and the resulting metamodel, as a foundational component to create a Disaster Management Decision Support System (DMDSS) to unify, facilitate and expedite access to DM expertise

    Towards knowledge sharing in disaster management: An agent oriented knowledge analysis framework

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    Disaster Management (DM) is a complex set of interrelated activities. The activities are often knowledge intensive and time sensitive. Sharing the required knowledge timely is critical for DM. In developed countries, for recurring disasters (e.g. floods), there are dedicated document repositories of Disaster Management Plans (DMP) that can be accessed as needs arise. However, accessing the appropriate plan in a timely manner and sharing activities between plans often requires domain knowledge and intimate knowledge of the plans in the first place. In this paper, we introduce an agent-based knowledge analysis method to convert DMPs into a collection of knowledge units that can be stored into a unified repository. The repository of DM actions then enables the mixing and matching knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). We use the flood management plans used by SES (State Emergency Service), an authoritative DM agency in NSW (New State Wales) State of Australia to illustrate and give a preliminary validation of the approach. It is illustrated using DMPs along the flood prone Murrumbidgee River in central NSW

    Customising agent based analysis towards analysis of disaster management knowledge

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    © 2016 Dedi Iskandar Inan, Ghassan Beydoun and Simon Opper. In developed countries such as Australia, for recurring disasters (e.g. floods), there are dedicated document repositories of Disaster Management Plans (DISPLANs), and supporting doctrine and processes that are used to prepare organisations and communities for disasters. They are maintained on an ongoing cyclical basis and form a key information source for community education, engagement and awareness programme in the preparation for and mitigation of disasters. DISPLANS, generally in semi-structured text document format, are then accessed and activated during the response and recovery to incidents to coordinate emergency service and community safety actions. However, accessing the appropriate plan and the specific knowledge within the text document from across its conceptual areas in a timely manner and sharing activities between stakeholders requires intimate domain knowledge of the plan contents and its development. This paper describes progress on an ongoing project with NSW State Emergency Service (NSW SES) to convert DISPLANs into a collection of knowledge units that can be stored in a unified repository with the goal to form the basis of a future knowledge sharing capability. All Australian emergency services covering a wide range of hazards develop DISPLANs of various structure and intent, in general the plans are created as instances of a template, for example those which are developed centrally by the NSW and Victorian SES’s State planning policies. In this paper, we illustrate how by using selected templates as part of an elaborate agent-based process, we can apply agent-oriented analysis more efficiently to convert extant DISPLANs into a centralised repository. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). The work is illustrated using DISPLANs along the flood-prone Murrumbidgee River in central NSW

    Disaster Management (DM) Model Transformations Framework

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    Metamodelling produces a ‘metamodel’ capable of generalizing the domain. A metamodel gathers all domain concepts and their relationships. It enables partitioning a domain problem into sub-problems. Decision makers can then develop a variety of domain solutions models based on mixing and matching solutions for sub-problems indentified using the metamodel. A repository of domain knowledge structured using the metamodel would allow the transformation of models generated from a higher level to a lower level according to scope of the problem on hand. In this paper, we reveal how a process of mixing and matching disaster management actions can be accomplished using our Disaster Management Metamodel (DMM). The paper describes DM model transformations underpinned by DMM. They are illustrated benefiting DM users creating appropriate DM solution models from extant partial solutions

    DM model transformations framework

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    Metamodelling produces a \u27metamodel\u27 capable of generalizing the domain. A metamodel gathers all domain concepts and their relationships. It enables partitioning a domain problem into sub-problems. Decision makers can then develop a variety of domain solutions models based on mixing and matching solutions for sub-problems indentified using the metamodel. A repository of domain knowledge structured using the metamodel would allow the transformation of models generated from a higher level to a lower level according to scope of the problem on hand. In this paper, we reveal how a process of mixing and matching disaster management actions can be accomplished using our Disaster Management Metamodel (DMM). The paper describes DM model transformations underpinned by DMM. They are illustrated benefiting DM users creating appropriate DM solution models from extant partial solutions

    House price volatility metamodel for managing house price volatility knowledge

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    A change in house price is a situation that is very dynamic and unpredictable. The study found that changes in house price volatility are more dynamic than the changes in the price of goods or household income. Demographic changes, market forces and the rise of speculation are among the factors that influence the volatility in house prices. Through this research all the determining factors associated with changes in house price volatility were identified because the changes on the determinant factors have an impact on the pattern of the house price market. For the purposes of showing a comprehensive relationship between the determinants of house price with house price volatility, the methods in modelling the concept in software engineering known as metamodelling has been adapted. Through metamodelling, an artifact known as 'metamodel' is produced. Specifically for this study, the metamodel is known as House Price Volatility Metamodel (HPVM). By combining qualitative and quantitative methods, the development of HPVM implemented using 8 Step Metamodelling Creation process, where HPVM is capable of modeling the determinant factors that determine the volatility in house prices in three major categories: i) Socio-Economic view, ii) Economic view and iii) HPV Significant Value view. Three types of validation technique, Expert Review (Face to Face Validation), Frequency-Base Selection and Tracing (Case Study) in three states in Malaysia, namely Penang, Johor and Kuala Lumpur have been used to assess the effectiveness of the metamodel. Metamodel development is believed to be beneficial to various stakeholders in the domain of property market such as the government like from Ministry of Finance, real estate investors, economists, buyers and real estate practitioners where they are able to get a variety of views and considerations in assessing house price market and house price volatility. These considerations are very important in evaluating the real estate market, as it will be an input in decisionmaking basis for this field

    Application of design science research to design a modelling approach for procurement of infrastructure systems

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    © 2019 IEEE. Model-driven approaches are widely used in managing the complex domains such as infrastructure systems or disaster management. The foundation of conducting a systematic research is designing a methodology that pertinently covers the steps of research from problem definition to solution proposal and then identifying or tailoring a method for developing and validating the solution. This paper explains the application of Design Science for conducting a research which aims at providing a model-driven approach for addressing the complexities of infrastructure procurement projects. So firstly the design science artefacts are adopted for designing the method for this research. Then the steps of this method are explained briefly along with description of how each step is applied in this research. The core of this method is proposing a process for developing and validating the metamodels which is designed based on combination of other metamodeling processes

    Towards adapting metamodeling approach for the mobile forensics investigation domain

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    Mobile phones have become quite important tools in the modern world. The forensics field heavily relies on knowledge as an important resource. Due to the ongoing changes in digital technology, the power of knowledge enables innovation and assists in establishing proper standards and procedures. As such, it is necessary to establish a relationship between the information derived from knowledge to form new concepts and ideas. Knowledge in mobile forensics is scattered and huge. Hence, this leads to lack of knowledge management in mobile forensics. In addition, lead to complexity of investigation for new investigators, ambiguity in concepts and terminologies of mobile forensics domain and waste time to understand mobile forensics domain. Therefore, mobile forensics investigators are quite suffering with forensics investigation processes in their domain. This paper will develop a new approach for mobile forensics domain which is based on metamodeling. This approach contributes to unify common concepts of mobile forensics. It also provides many benefits which include simplifying the investigation process and guide investigations team, capture and reuse specialized forensic knowledge and support training and knowledge management activities. Furthermore, it reduces complexity and ambiguity in mobile forensic domai Towards Adapting Metamodeling approach for the Mobile Forensics Investigation Domain
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