FIT5207 - Data for sustainability - 2017

This unit is designed to introduce and explore the ways emerging technologies have opened up new possibilities for sustainability and sustainable development. This includes exploring the role of new techniques in data management, data analytics, data visualisation, modelling and simulation in exploring natural phenomena and addressing environmental problems. It also looks at the knowledge management challenges of storing, managing, integrating and utilising the ever increasing volume of data now becoming available through a variety of new techniques and technologies (e.g. Geoinformatics, remote-sensing, community-based data collection, social media). This includes the increasing importance of Big Data as well as a range of decision-support tools and techniques.

At the completion of this unit, students should be able to:

1. critique (or analyse) data science methodologies that relate to sustainability;
2. critique emerging technologies and analyse how they can be applied to key sustainability issues;
3. analyse the effectiveness of spatial data science in relation to location-specific sustainability issues;
4. interpret the significance of data science technologies and assess the impact they have had on the goal of sustainability.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week consisting of:

1. Contact hours for on-campus students:
   • Two hours lectures
   • Two hours tutorials
2. Study schedule for off-campus students:
   • Off-campus students generally do not attend lectures and tutorials, however they should plan to spend equivalent time working through resources and participating in online discussions.
3. Additional requirements for all students:
   • A minimum of 8 hours of personal study per week for completing tutorial activities, assignments, private study and revision.

See also Unit timetable information