FIT5207 is an elective unit in the Master of Data Science course for postgraduate students. This unit explores how the emerging field of data science can be applied to address the key sustainability challenges of our time.

Admin - fix of typo and formatting

25/08/2015 - Admin: number learning outcomes 28/4/2021 - Unit disestablished at FEC 2/21 Item 6.2

FIT5207 Data for Sustainability is an elective unit and forms part of the Master of Data Science course. Its key objectives are to prepare students so that they will:

On successful completion of this unit, students should be able to:

1. critique (or analyse) data science methodologies that relate to sustainability

1. critique emerging technologies and analyse how they can be applied to key sustainability issues

1. analyse the effectiveness of spatial data science in relation to location-specific sustainability issues

1. interpret the significance of data science technologies and assess the impact they have had on the goal of sustainability

020399 Information Systems, n.e.c. 050999 Environmental Studies, n.e.c.

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 visualization, modelling and simulation in exploring natural phenomena and addressing environmental problems. It also looks at the knowledge management challenges of storing, managing, integrating and utilizing 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.

Bert J. M. de Vries (2012) Sustainability Science Cambridge University Press

Ting Yu, Nitesh Chawla, Simeon Simoff (Eds.) (2013) Computational Intelligent Data Analysis for Sustainable Development. - Chapman & Hall/CRC Data Mining and Knowledge Discovery Series Published: April 4, 2013 by Chapman and Hall

"Sustainability: A Comprehensive Foundation" UoI free online textbook http://www.earth.illinois.edu/sustain/sustainability_text.html

on-campus

This unit is proposed with 100% in-semester assessment due to the practical nature of the content. The study of sustainability is based on a strong relationship with practice and evaluation of a student's knowledge and understanding must be based on being able to apply conceptual knowledge in concrete examples and to evaluate specific projects. The assessable items in this unit will include two practical assignments drawing upon demographic, environmental or geographic datasets (weighted 30% each) and a detailed analysis of a sustainability case study (40%). Assessment will be verified through peer review presentation following each of the practical assessments, and by informal interview with the tutor/lecturer for the case study analysis.

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

Contact hours for on-campus students:

Two hours lectures

Two hours Tutorials

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

Additional requirements for ALL students:

A minimum of 8 hours of personal study per week for completing tutorial activities, assignments, private study and revision

FIT

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