FIT5206 - Digital continuity - 2019

Maintaining continuity in a digital data driven world is emerging as a key challenge for organisations, communities, governments and societies. Digital continuity is defined as the ability to use digital information in the way that is needed for as long as it is needed. It encompasses understanding the frameworks, principles, processes and technologies underpinning intergenerational system conceptualisation, design, development and implementation.

This unit will build on the introduction to digital/data curation provided in FIT5146. It will examine the laws, frameworks and policies for managing and preserving digital media and data as evidence and cultural heritage; access and appraisal strategies, policies and tools, metadata regimes for digital media and data archives; digital repository platforms, technologies, systems and tools; management of archival databases, datasets and digital media collections; and development and deployment of digital media and data archiving tools and services for users. Exemplar digital media and/data archiving initiatives and projects in the community and cultural heritage sectors will also be explored.

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

1. explain the role that records and archives play in organisations and society;
2. evaluate and apply archival frameworks, policies and best practice for the preservation of digital resources as evidence, memory and cultural heritage;
3. specify functional requirements for and evaluate digital repository platforms, technologies, systems and tools;
4. identify and evaluate digital archiving tools and services for users;
5. evaluate digital archiving initiatives/projects in the community and cultural heritage sectors.

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 tutorials
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

Archives and recordkeeping

Data science