Spatial Data Infrastructure

Subject GEOM90015 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

Semester 2, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 25-Jul-2016 to 23-Oct-2016
Assessment Period End 18-Nov-2016
Last date to Self-Enrol 05-Aug-2016
Census Date 31-Aug-2016
Last date to Withdraw without fail 23-Sep-2016


Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 48 hours (Lectures: 24 hours per semester; Projects/Laboratories: 24 hours per semester)
Total Time Commitment:

200 hours

Prerequisites:

Successful completion of the following is required to enrol in this subject:

Subject
Study Period Commencement:
Credit Points:

GEOM90008 Foundations of Spatial Information may be taken concurrently.

Corequisites: None
Recommended Background Knowledge:

An understanding of spatial data and relevant processes and service delivery concepts.

It is advisable that students undertake this subject in their final year of study.

Non Allowed Subjects: None
Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability

Coordinator

Prof Abbas Rajabifard

Contact

Professor Abbas Rajabifard

abbas.r@unimelb.edu.au

Subject Overview:

AIMS

In this subject, students will learn about the principles, concepts and design strategies used in the development of Spatial Data Infrastructure (SDI) as an enabling platform to facilitate multi-sourced data and service discovery, access, integration and use. An example of SDI is the land titles system and the tools used to maintain and interrogate it. Emphasis will be placed on both technological and institutional factors that facilitate the development of SDIs. Students will examine related disciplines such as land and marine administration as well as technical areas such as interoperability, web-mapping and web-delivery to better meet sustainable development objectives. This subject is of particular relevance to students who want to pursue a career in spatial data management, land administration, but is also relevant to a range of geomatic engineering disciplines that use and produce large spatial datasets for decision-making in support of sustainable development.

The subject partners with other subjects on spatial data management, spatial data analysis and spatial data visualization, and is of particular relevance to people wishing to establish a career in the spatial information industry, the environmental or planning industry.

INDICATIVE CONTENT

SDI concepts and theory, current SDI initiatives, SDI development strategies and development models; SDI as an enabling platform, SDI and Spatially Enabled Government and Society, SDI and partnership approaches, financing and capacity building, challenges for developed and developing countries, capacity building, marine SDI and seamless SDI, policy and privacy Issues, SDI and land administration, metadata, standards and clearinghouses, SDI application areas, and SDI implementation and benchmarking.

Learning Outcomes:

INTENDED LEARNING OUTCOMES (ILO)

On completion of this subject the student is expected to:

  1. Describe the core SDI principles
  2. Identify the necessary components required to support the development of SDIs, including technical and institutional arrangements and the basis of effective and efficient design
  3. Describe a range of technologies and technological concepts applicable for developing and maintaining SDIs
  4. Analyse the range of approaches to SDI development in both developed and developing countries
  5. Model, design and evaluate SDI initiatives and spatial enablement platforms.
Assessment:
  • One 2-hour written examination (40%) end of semester. Intended Learning Outcomes (ILOs) 1, 2 and 3 are addressed in the examination
  • One group major assignment (30%) of 3000 words per student member and a presentation (10 min) due at the end of semester. Requires approximately 35-40 hours of work per student. ILOs 1 to 5 are addressed in the assignment
  • One selected topic presentation (10%) over the semester, requiring approximately 13-15 hours of work. ILOs 1, 2 and 4 are addressed in the presentation
  • Two practical exercises and reports (20%) of not more than 1000 words total, to be submitted over the first eight weeks of the semester, requiring 25-30 hours of work in total. ILOs 2 and 5 are addressed in the assessment.
Prescribed Texts:
  1. Crompvoets, J., Rajabifard, A., van Loenen, B. and Delgado Fernandez, T. (2008), Multi-view Framework to Assess SDIs
  2. Rajabifard, A. (2007), Towards a Spatially Enabled Society. The University of Melbourne Press
  3. Williamson, I.P, Rajabifard, A. and Feeney, M.-E. (2003). Developing Spatial Data Infrastructures: From Concept to Reality. Taylor and Francis
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On successful completion students should have:

  • Ability to undertake problem identification, formulation, and solution
  • Understanding of social, cultural, global, and environmental responsibilities and the need to employ principles of sustainable development
  • Ability to communicate effectively with the engineering team and with the community at large.
Notes:

LEARNING AND TEACHING METHODS

The subject is based principally on content that has been developed from industry experience in designing, developing and implementing SDIs. This will be supplemented by guest presentations and seminars from industry professionals. A computer laboratory will be used to explore potential technological tools and different lab exercise that can be used to learn how to design and use different components related to SDIs. In the tutorials, students will work in groups to apply theory gained in the lectures to a real world industry case study. This learning will enable students to consolidate their knowledge in a practical and relevant way. Within their groups students will also prepare and present a minor research project on an affiliated topic of their interest selected from an extensive list.

INDICATIVE KEY LEARNING RESOURCES

The subject will utilise different sources (books, journal papers, conference papers, etc.) mostly available through the website for the Centre for SDIs and Land Administration, Department of Infrastructure Engineering, The University of Melbourne (www.csdila.unimelb.edu.au). The subject in particular will utilise the following books:

  • ‘Developing Spatial Data Infrastructures: from concept to reality’, Taylor and Francis, 2003 UK, edited by Ian Williamson, Abbas Rajabifard and Mary-Ellen F. Feeney,
  • ‘Towards a Spatially Enabled Society’, The University of Melbourne 2007, edited by Abbas Rajabifard, The University of Melbourne.
  • ‘Multi-view Framework to Assess SDIs’, edited by Joep Crompvoets, Abbas Rajabifard, Bastiaan van Loenen and Tatiana Delgado Fernandez, 2008.
  • and related scientific journal or conference publications (particularly from GSDI and INSPIRE conferences) will be also utilised.

CAREERS / INDUSTRY LINKS

Presenters from relevant government and private agencies will present guest lectures and seminars. Real-world examples of SDIs will be used as case studies.

Related Course(s): Doctor of Philosophy - Engineering
Master of Geographic Information Technology
Master of Information Systems
Master of Information Systems
Master of Information Systems
Master of Information Technology
Master of Philosophy - Engineering
Master of Spatial Information Science
Related Majors/Minors/Specialisations: MIS Professional Specialisation
MIS Research Specialisation
MIT Spatial Specialisation
Master of Engineering (Spatial)

Download PDF version.