FIT5205 - Data in society - 2017

In the digital world, how we communicate, conduct business and socialize is revolutionising our way of life. The explosion of data and discovery are transforming the way we live and work, altering relationships between government and citizens, businesses and consumers, the researchers and the researched, the public and private sectors, the individual and society. This unit explores how big data analytics can potentially help grow the economy, improve health and education, support national security, protect the environment, enable more energy efficiency, drive innovation and progress, and support more resilient, sustainable communities and cultures. It also addresses the risks associated with the application of big data analytics in government and big business to support greater surveillance of citizen by state and consumers by business, disempower individuals and vulnerable communities, support discrimination, threaten social inclusion, social justice, human and civil rights, self-determination and privacy, and widen the divide between the data haves and have-nots.

The unit will cover: introduction to social, cultural and heritage informatics; building digital media/data ecosystems and using data technologies to achieve the benefits and mitigate the risks of big data; developing socio-legal and policy frameworks to ensure transparency, good governance, accountability and ethical practice; big data rights regimes - rights in data, rights to self determination, privacy rights, access rights, discovery rights, IP and copyright; use of big data to support resilient, sustainable communities and cultures.

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

1. explain social, cultural and heritage informatics;
2. describe and analyse digital media/data ecosystems;
3. analyse issues relating to the benefits and risks of big data in society;
4. investigate how rights in data, rights to self determination, privacy rights, access rights, discovery rights, IP and copyright apply in different contexts/scenarios;
5. develop recommendations for socio-legal and policy frameworks and strategies for transparency, good governance, accountability and ethical practice in data management and use, including data rights management;
6. analyse needs and issues relating to the use big data to support resilient, sustainable communities and cultures.

In-semester assessment: 100%

Minimum total expected workload equals 12 hours per week comprising:

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

See also Unit timetable information

Professor Susan McKemmish

Archives and recordkeeping

Data science

Library and information science