Infrastructure Engineering - Research Publications
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ItemDeveloping a seamless SDI model across the land-sea interface( 2007)A more integrated and holistic approach to management of spatial information relating to coastal and marine environments is needed and this can be facilitated by the creation of a Spatial Data Infrastructure (SDI) on a seamless platform. There is a growing and urgent need to create a seamless SDI model that bridges the gap between the terrestrial and marine environments, creating a spatially enabled land-sea interface to more effectively meet sustainable development objectives. This paper discusses the principles and concepts followed by introduction to issues and challenges that must be overcome in developing an overarching architecture for a seamless SDI that allows access to and interoperability of data from marine, coastal and terrestrial environments.
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ItemBuilding the spatial data infrastructure through data sharing: measuring progress within Australian local and state government jurisdictions( 2007)In the past decade efforts to develop spatial data infrastructures (SDIs) have migrated from the initial “top-down” national approaches to “bottom-up” and cross jurisdictional efforts at the sub-national level. Although national SDI developments are fundamental to building the SDI culture and policy, it is sub-national and local SDI development that will deliver the immediate benefits to citizens and the community. In countries which have highly decentralised federations of states such as Australia, United States and Canada, the challenge is how to co-ordinate the literally thousands of often small local government jurisdictions which are important contributors to state and local SDIs. In recent years, a number of co-operative spatial data sharing partnerships between local and state government have emerged in Australia. These partnerships are relatively new initiatives that have been established to facilitate more effective sharing of spatial data between organisations, but also as a mechanism to contribute to SDI development. To maximise the benefits from these partnerships it is essential to understand the factors that contribute to their successful operation and sustainability. This paper investigates these collaborative arrangements and examines the motivations, mechanisms and frameworks for data sharing between local and state governments.
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ItemSDI to Facilitate a Spatially Enabled Society(Spatial Sciences Institute, 2007)
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ItemSpatial data integration: a necessity for spatially enabling government(University of Melbourne, The Centre for SDIs and Land Administration, 2007)Introduction Most governmental decisions involve a spatial component (Williamson and Wallace, 2006), therefore informative decision making within governments is highly reliant upon multi-sourced spatial data. The ability to spatially enable governments through the use of integrated multi-source spatial data at different governmental levels makes governmental decisions incredibly efficient (Mitchell, 2006b), though governments rarely produce all the data required for their business. Rather, they obtain and integrate data from different sources. However, the diversity of data producers hinders effective spatial data integration. There are many technical and non-technical obstacles in the integration of multi-sourced spatial data and this is one of the major problems in sharing and using spatial data among government organizations. From a technical perspective, spatial data may differ semantically, syntactically and structurally. Institutional, social, policy and legal issues also hinder data integration. In order to effectively overcome these issues, a holistic framework is required to manage and address the issues. SDIs aim to facilitate the integration of multi-source spatial data by providing a holistic framework in which spatial data stakeholders (governments, private sector, etc) interact with spatial data effectively through technological components. There are inconsistencies in the various data within an SDI which lead to data inconsistency and hinder data integration. These inconsistencies should be managed through the SDI framework. However, at the moment, the SDI framework does not deal with these inconsistencies effectively. Hence, we need to identify and map the inconsistencies and develop tools and guidelines within the framework of an SDI to manage them. This will then make it easier for data to be integrated across and within government organisations.
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ItemBrave new world: innovative tools for spatially enabling land administration(University of Melbourne, The Centre for SDIs and Land Administration, 2007)Introduction The term silo effect gained prominence in government and business circles during the 1990s (Williamson, 2007). It denotes the entrenched lack of communication and collaboration between organisations and their systems. For decades private organisations held onto their capital, information and skills for internal use only. All this changed with the introduction of information and communication technologies: by sharing resources with its business partners and customers a company could decrease costs, streamline processes and create better customer relations. The silo effect had to be overcome. The field of land administration was created in part in response to discussions about the silo effect. It was clear that the institutions dealing with tenure registration, cadastral mapping, natural resource management and so on, needed to be united. Integration of their theories, processes and information would result in better land management. The collaboration of ideas began in the late 1990s and has resulted in academic theories being used to enhance understandings of practical issues: for example hierarchal spatial reasoning has been applied to spatial data infrastructures (Rajabifard, 2002), policy design concepts to land policies (Ting, 2002), benchmarking to land administration systems (Steudler, 2003), cost benefit analysis to decision making about land (Paez, 2005). Organizational theory has advanced collaboration within land administration agencies (Warnest, 2005; McDougall, 2006) and tenure theories have been applied to the rural parts of developing countries (Dalrymple, 2006). Land administration is now multidisciplinary: its ability to use of the tools and theories of diverse disciplines has been its underlying strength. This chapter takes a similar approach: it looks at new theories and concepts from outside the discipline that will assist in spatially enabling land administration. Particularly, the management of the hundreds of new land rights, restrictions and responsibilities that exist over land. Ontological design, social learning, spatial technologies and uncertainty theory are four areas worthy of consideration. Each could profoundly impact upon existing land administration systems.
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ItemAn Initial Model Of The Computation Viewpoint For A SDI( 2007)The Commission on Spatial Data Standards of the International Cartographic Association (ICA) is working on defining formal models and technical characteristics of Spatial Data Infrastructures (SDI). The Commission has already presented models of the Enterprise and Information Viewpoints from the ISO Reference Model for Open Distributed Processing (RM-ODP) standard (ISO/IEC 10746:1995). The Commission is now taking this further to model the Computation Viewpoint, which describes how the different services of an SDI fit together. The models should be seen as a continuing step towards the overall model of the SDI and its technical characteristics.The Commission has identified six broad groupings of services: Registry, Data, Processing, Portrayal, Application and Management. The interactions between these high-level services have been modelled using the Unified Modeling Language (UML) Component Diagrams. The detailed services have been modelled using UML Class Diagrams (Object Management Group 2005).