Metamodelling Approach To Support Disaster Management Knowledge Sharing

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

P2CP: A New Cloud Storage Model to Enhance Performance of Cloud Services

This paper presents a storage model named Peer to Cloud and Peer (P2CP). Assuming that the P2CP model follows the Poisson process or Little’s law, we prove that the speed and availability of P2CP is generally better than that of the pure Peer to Peer (P2P) model, the Peer to Server, Peer (P2SP) model or the cloud model. A key feature of our P2CP is that it has three data transmission tunnels: the cloud-user data transmission tunnel, the clients’ data transmission tunnel, and the common data transmission tunnel. P2CP uses the cloud storage system as a common storage system. When data transmission occurs, the data nodes, cloud user, and the non-cloud user are all together involved to complete the transaction

A review of Australian information privacy laws and standards for secure digital ecosystems

Information privacy is mainly concerned with protection of personally identifiable information. Information privacy is an arduous task, in particular, in the context of complex adaptive and multi-party heterogeneous digital ecosystems. There is a need to identify and understand the relevant privacy laws and standards for designing the secure digital ecosystems. This paper presents the results of our information privacy research in digital ecosystems through the lens of Australian privacy regulations and standards. The research results indicate that information privacy is a critical phenomenon; however, it is not adequately addressed in the context of end-to-end digital ecosystem. It is recommended that a multi-layered approach is required by reviewing and mapping Australian information privacy laws and standards at different layers to design secure digital ecosystems

Real-time task attributes and temporal constraints

Real-time tasks need attributes for monitoring their execution and performing recovery actions in case of failures. Temporal constraints are a class of real-time task attributes where the constraints relate the status of the task to temporal entities. Violating temporal constraints can produce consequences of unknown severity. This paper is part of our on-going research on real-time multi agent systems constraints. We discuss the importance of temporal constraints and present a task model that explicitly represents temporal constraints. We also present our preliminary results from our initial implementation in the domain of Meeting Schedules Management involving multiple users assisted by agents

Development and validation of a disaster management metamodel (DMM)

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

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

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

Using Adaptive Enterprise Architecture Framework for Defining the Adaptable Identity Ecosystem Architecture

Digital identity management is often used to handle fraud detection and hence reduce identity thefts. However, using digital identity management presents additional challenges in terms of privacy of the identity owner meanwhile managing the security of the verification. In this paper, drawing on adaptive enterprise architecture (EA) with an ecosystem approach to digital identity, we describe an identity ecosystem (IdE) architecture to handle identity management (IdM) while safeguarding security and privacy. This study is a part of the larger action design research project with our industry partner DZ. We have used adaptive EA as a theoretical lens to define a privacy aware adaptive IdM with a view to improve the Id operations and delivery of services in the public and private sector. The value of the anticipated architecture is in its generic yet comprehensive structure, component orientation and layered approach which aim to enable the contemporary IdM

AGILE ENTERPRISE ARCHITECTURE: A CASE OF A CLOUD TECHNOLOGY-ENABLED GOVERNMENT ENTERPRISE TRANSFORMATION

Australian government enterprises have shown a significant interest in the cloud technology-enabled enterprise transformation. Australian government suggests the whole-of-a-government strategy to cloud adoption. The challenge is how best to realise this cloud adoption strategy for the cloud technology-enabled enterprise transformation? The cloud adoption strategy realisation requires concrete guidelines and a comprehensive practical framework. This paper proposes the use of an agile enterprise architecture framework to developing and implementing the adaptive cloud technology-enabled enterprise architecture in the Australian government context. The results of this paper indicate that a holistic strategic agile enterprise architecture approach seems appropriate to support the strategic whole-of-a-government approach to cloud technology-enabled government enterprise transformation