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Spatial Data Management (GEOM90008)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
Contact information
Semester 1
Martin Tomko
email: tomkom@unimelb.edu.au
Semester 2
Alan Thomas
email: alan.thomas@unimelb.edu.au
Overview
Availability | Semester 1 Semester 2 |
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Fees | Look up fees |
This subject combines practical spatial data management with the underpinning theories of spatial and spatiotemporal data representation and handling from Geographic Information Science. Spatial information is answering ‘where’ and ‘when’ questions – which are fundamental in decision making in complex systems, be it in urban planning, traffic and infrastructure management, environmental management, public health and sustainability, or any other social, economic, and environmental context.
The subject introduces foundations of effective, efficient, and large-scale spatial data management. This subject will cover the concepts, methods, and approaches that allow for efficient representation, querying, and retrieval of spatial data, in a modern ecosystem of spatial databases interfacing a geographic information system.
The knowledge acquired is fundamental for subsequent studies in spatial data analytics and visualisation, and is of particular relevance to people wishing to establish a career in the spatial information, the environmental, or the planning industry. It is also suited for every postgraduate student who is looking for solid skills with Geographic Information Systems.
In this subject, we will discuss the intricacies of computational representation and management of spatial information. The subject takes a spatial database perspective to management of extensive spatial datasets. The subject will cover the modelling, loading, transformation, analysis, and retrieval of spatial data in spatial databases. The subject covers data representations (vector, raster, and network data); spatial operations, including geometric, topological, set-oriented, and network operations; spatial indexes and access methods, including quadtrees and R-trees. The subject exposes the students to the whole lifecycle of spatial data management in a team-based project.
Please view this video for further information: Spatial Data Management
Intended learning outcomes
On completion of this subject, students should be able to:
- Associate the value of spatial information to digital infrastructure management;
- Evaluate fundamental data structures and analysis procedures associated with spatial information;
- Apply the database design process to manage information about infrastructure data;
- Combine advanced skills in the design and use of a spatial database supported by a Geographic Information System on a complex infrastructure project;
- Demonstrate professional skills in ethics and sustainability, communication, and teamwork.
Generic skills
On successful completion, students will have:
- The ability to transfer domain knowledge to fundamental challenges in society
- The ability to undertake problem identification, formulation, and solution
- The ability to communicate effectively, with a project team and with the community at large
- The ability to effectively manage information and documentation
- An understanding of professional and ethical responsibilities, and a commitment to them
- A capacity for lifelong learning and professional development.
Last updated: 26 August 2024