Infrastructure Engineering - Research Publications
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ItemFacilitating the national infrastructure for managing land information through spatial metadata automation(Centre for Spatial Infrastructures, Land Administration, Department of Infrastructure Engineering, University of Melbourne, 2012)
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Item3D cadastral data model: a foundation for developing a national land information infrastructure(Centre for Spatial Infrastructures, Land Administration, Department of Infrastructure Engineering, University of Melbourne, 2012)
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Item3D visualisation as a tool to facilitate managing land and properties(Centre for Spatial Infrastructures, Land Administration, Department of Infrastructure Engineering, University of Melbourne, 2012)
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ItemTrends in 3D land information collection and management(Centre for Spatial Infrastructures, Land Administration, Department of Infrastructure Engineering, University of Melbourne, 2012)
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ItemTowards 3D land and property information: engineering institutional change(Centre for Spatial Infrastructures, Land Administration, Department of Infrastructure Engineering, University of Melbourne, 2012)
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ItemSupporting land and property risk management activities with land administration systems(Centre for Spatial Infrastructures, Land Administration, Department of Infrastructure Engineering, University of Melbourne, 2012)
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ItemTowards a national land information infrastructure for managing layered property markets in federated countries(Centre for Spatial Infrastructures, Land Administration, Department of Infrastructure Engineering, University of Melbourne, 2012)
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ItemSetting the scene for NIMLI(Centre for Spatial Infrastructures, Land Administration, Department of Infrastructure Engineering, University of Melbourne., 2012)
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ItemNorth West Melbourne data integration project( 2012)This publication highlights the importance of a national land administration infrastructure to support sustainable development. It contains a summary of research connected to the national infrastructure for managing land information project funded by the Australian Research Council Grant (LP0990571:2009-2012). This summary also covers other related research conducted overthese last four years. The projects identifies the drivers and components required for better management of land and property at a national level for Australia and makes recommendations for similar federated countries. The research project has been coordinated through the Centre for Spatial Data Infrastructures and Land Administration, the University of Melbourne in close collaboration with industry partners.
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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.