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
Martin Tomko
email: tomkom@unimelb.edu.au
Overview
| Availability | Semester 1 Semester 2 |
|---|---|
| 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:
- ILO 1. Associate the value of spatial information to digital infrastructure management;
- ILO 2. Evaluate and apply fundamental data structures and analysis procedures associated with spatial information;
- ILO 3. Apply the database design process to manage spatial and non-spatial relational data;
- ILO 4. Combine advanced skills in the design and use of a spatial database supported by a Geographic Information System on a complex infrastructure project;
- ILO 5. 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: 27 February 2025
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
A background in (non-spatial) databases is recommended for this course, for example successful completion of INFO20003 Database Systems, or similar relational database design, ER modelling, relational algebra, and SQL.
An applied knowledge of GIS (e.g., GEOM20013) is also an asset. Students will be provided with self-learning resources to complement their training and knowledge if necessary, before the semester.
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 27 February 2025
Assessment
| Description | Timing | Percentage |
|---|---|---|
Documentation of a training experience of the interaction with non-spatial relational databases, and of basic GIS interaction. Addressing Intended Learning Outcome (ILO) 4.
| Week 4 | 0% |
Group project – data management design proposal. Deliverable is a report of a maximum of 5 pages (per group) (25%). (30 hours of work per group member). ILOs 1, 2, 3 and 5 are addressed in this assessment.
| Week 6 | 25% |
Individual assessment targeting spatial data querying (Week 8), worth 10%. ILOs 2 and 4 is addressed in this assessment.
| Week 8 | 10% |
A 30-minute supervised in-class test (Week 9) worth 10%. ILOs 1, 2 and 3 are addressed in this assessment.
| Week 9 | 10% |
Group project – presentation requiring a 3 min 30 sec recorded video (10%). (10 hours of work required per group member). ILOs 3, 4 and 5 are addressed in this assessment.
| Week 12 | 10% |
Group project – realisation of the spatial database previously designed in the project design proposal, assessed via a report of a maximum of 15 pages (per group) and a set of database queries proving the realised implementation (35%). (requiring 50 hours of work per group member). ILOs 1-5 are addressed in this assessment.
| During the examination period | 35% |
An individually written 1-page reflection on the group project (10%). ILOs 4 and 5 are addressed in this assessment.
| During the examination period | 10% |
Last updated: 27 February 2025
Dates & times
- Semester 1
Coordinator Martin Tomko Mode of delivery On Campus (Parkville) Contact hours 48 hours (Lectures: 2 hours per week; Practicals 2 hours per week) Total time commitment 200 hours Teaching period 3 March 2025 to 1 June 2025 Last self-enrol date 14 March 2025 Census date 31 March 2025 Last date to withdraw without fail 9 May 2025 Assessment period ends 27 June 2025 Semester 1 contact information
Martin Tomko
email: tomkom@unimelb.edu.au
- Semester 2
Coordinator Martin Tomko Mode of delivery On Campus (Parkville) Contact hours 48 hours (Lectures: 2 hours per week; Practicals 2 hours per week) Total time commitment 200 hours Teaching period 28 July 2025 to 26 October 2025 Last self-enrol date 8 August 2025 Census date 1 September 2025 Last date to withdraw without fail 26 September 2025 Assessment period ends 21 November 2025 Semester 2 contact information
Martin Tomko
email: tomkom@unimelb.edu.au
Time commitment details
200 hours
What do these dates mean
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- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 27 February 2025
Further information
- Texts
- Subject notesLEARNING AND TEACHING METHODSThere will be lectures associated with weekly lab exercises to be done in a computing lab. Students are expected to interact with real systems and interact with each other in the labs.INDICATIVE KEY LEARNING RESOURCESDuckham, Sun and Worboys, 2024. GIS: A computing perspective, third edition, Routledge, ISBN: 9781466587199.Rigaux, Scholl and Voisard, 2002. Spatial databases: With application to GIS, Morgan Kaufmann, ISBN: 1558605886.Shekhar and Chawla, 2002. Spatial databases: A tour, Prentice Hall, ISBN: 0130174807.Silberschatz, Korth and Sudarshan, Database System Concepts, McGraw Hill.CAREERS / INDUSTRY LINKSSpatial data management is a fundamental professional skill for Spatial Information, Digital Infrastructure and Geographic Information Systems. Students will acquire knowledge in SQL and key database software packages, which will be essential for any future career they may aim to pursue.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Environmental Engineering Course Master of Data Science Course Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Course Master of Geography Specialisation (formal) Spatial - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
- Available to Study Abroad and/or Study Exchange Students
Last updated: 27 February 2025