Providing a framework to seamlessly integrate data on people, business, and the environment in a consistent way
Abstract
Location can be described and used to spatially enable data in a number of different ways. Street address is useful for service delivery; land parcels for revenue raising and investment; coordinates and grids for positioning and monitoring changes in the landscape; various administrative boundaries for law enforcement and service management; statistical geographies for statistics. Using location as a common linking feature, Location Index helps to bring together socio-economic, statistical and environmental data from across a number of government sources Geoscience Australia and it partners are working on implementation of the Location Index to address cross-portfolio data use needs around location-based data to provide a consistent way to seamlessly integrate data on people, business, and the environment Location Index will develop an agreed and consistent way - or ways - to translate and connect different methods of referencing location across government data and benefit users by: -building a set of re-usable tools and APIs -developing best practice guidelines and documentation to support developers and users -reducing costs in accessing the data -enabling fast and easy access to the data -enabling stable, persistent and repeatable access to the data -reducing complexity in using of the data -increasing interoperability with other datasets -improving decision making through the use of trusted data -providing transparency in how the data was made and what is planned for the datasets future. Location Index is being delivered in two phases over the next two years Phase One will deliver a working prototype to demonstrate how a functional Location Index can be used to improve the ability to accurate and consistently analyse and interrogate location data. A set of guidelines outlining how data should be'spatially enabled' will accompany the prototype to support users in the analysis and interpretation of the newly combined datasets. Phase Two will build on findings from Phase One and deliver a refined and more robust prototype and supporting governance to support a positive user experience, easy access to collated data and fast analysis and interpretation of this data.
- Publication:
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EGU General Assembly Conference Abstracts
- Pub Date:
- April 2019
- Bibcode:
- 2019EGUGA..21.2231C