Overview
This course examines the ethical, governance, security, and reproducibility requirements of responsible data practice across the full data lifecycle. Topics include ethical theories and professional responsibilities; consent, autonomy, privacy, confidentiality, data minimisation, secondary use, data linkage, ownership, stewardship, access, licensing, and retention.
Students evaluate governance frameworks, accountability structures, risk assessments, audits, Indigenous and community data sovereignty, algorithmic bias, discrimination, fairness, security threats, and the limits of de-identification. The course also develops practical expertise in provenance, metadata, version control, computational environments, testing, workflow automation, transparent reporting, open science, and preregistration.
Applied work requires students to audit a data project, create a data management and governance plan, build a documented and reproducible workflow, assess fairness and potential harms, and communicate trade-offs among openness, utility, privacy, and accountability in institutional, legal, and sector-specific contexts.
Learning Outcomes
- Evaluate ethical theories, professional responsibilities, and institutional, legal, and sector-specific obligations relevant to data work.
- Identify and prioritise ethical, privacy, security, governance, and reproducibility risks across the data lifecycle.
- Design data management, access, retention, and governance plans that address consent, confidentiality, stewardship, accountability, and community expectations.
- Assess algorithmic systems and data practices for bias, discrimination, fairness, disproportionate impacts, and risks to vulnerable populations.
- Appraise the effectiveness and limitations of de-identification, security controls, data linkage practices, and privacy-preserving procedures.
- Construct reproducible analytical workflows using provenance records, metadata, version control, testing, computational environments, and workflow automation.
- Audit data projects and document methodological, governance, and ethical decisions so that analyses can be inspected, evaluated, and rerun.
- Synthesize evidence-based recommendations that communicate trade-offs among openness, utility, privacy, sovereignty, and accountability.
Timetable
| Type | Length | Frequency | Period |
|---|---|---|---|
| Lecture | 2 hours | Weekly | All semester |
| Lab | 2 hours | Weekly | All semester |
| Tutorial | 1 hour | Weekly | All semester |
Assessment Schedule
| Type | Description | Weighting |
|---|---|---|
| Assignment | Ethical risk analysis of a data lifecycle scenario. | 15.00% |
| Assignment | Data project audit report. | 20.00% |
| Deliverable | Data management and governance plan. | 20.00% |
| Deliverable | Reproducible workflow and technical documentation. | 25.00% |
| Quiz | Governance and reproducibility quizzes (5 × 2%). | 10.00% |
| Capstone | Integrated portfolio and reflective defense. | 10.00% |
Prerequisites
Teaching Staff & Programs
This course is delivered jointly by faculty from the participating programs listed below. In line with the Douchewater Way, the University of Sexology tailors core instruction directly to each cohort's specific discipline — adapting curriculum to program needs rather than forcing students into a one-size-fits-all model. Learn more about our approach at The Douchewater Way.
