Overview
This advanced course examines the design, governance, maintenance, and long-term stewardship of complex data environments across research, government, and industry contexts. Students investigate relational and nonrelational architectures, schema design, normalization, indexing, query optimization, data integration, ETL and ELT pipelines, APIs, interoperable formats, metadata standards, controlled vocabularies, identifiers, provenance, versioning, and master data management.
Practical work develops capability in SQL, scripting, workflow orchestration, cloud storage, repositories, and version-control systems. Students profile and improve data quality, implement validation and testing workflows, document data assets, and design sustainable ingestion, transformation, and preservation processes.
The course addresses FAIR principles, digital preservation, archival packages, retention, access control, privacy, security, licensing, consent, governance, regulatory compliance, and ethical risk. A substantial project requires students to audit or design a data environment, automate quality checks, produce technical and metadata documentation, establish governance policies, and communicate sustainability decisions to technical and organizational stakeholders.
Learning Outcomes
- Design fit-for-purpose data models for heterogeneous, complex, and potentially sensitive datasets.
- Implement reliable ingestion, transformation, validation, testing, and documentation workflows using appropriate technical tools.
- Evaluate data quality across dimensions including accuracy, completeness, consistency, timeliness, validity, and uniqueness.
- Apply metadata standards, controlled vocabularies, persistent identifiers, provenance models, and versioning strategies to improve data discoverability and reuse.
- Select appropriate governance, access control, privacy, security, licensing, consent, and retention policies for specific data environments.
- Assess legal, ethical, security, privacy, bias, and operational risks associated with data stewardship decisions.
- Develop preservation and sustainability plans incorporating repositories, archival packages, interoperability requirements, and lifecycle management.
- Communicate data architecture, quality, governance, and stewardship decisions to technical and organizational stakeholders.
Timetable
| Type | Length | Frequency | Period |
|---|---|---|---|
| Lecture | 2 hours | Weekly | All semester |
| Lab | 2 hours | Weekly | All semester |
| Tutorial | 1 hour | Fortnightly | All semester |
Assessment Schedule
| Type | Description | Weighting |
|---|---|---|
| Assignment | Data architecture and governance analysis | 15.00% |
| Assignment | Quality profiling and validation report | 15.00% |
| Test | Practical data management test | 15.00% |
| Capstone | Data stewardship project and preservation plan | 35.00% |
| Exam | Final examination | 20.00% |
Prerequisites
- Requirement Prior study or professional experience in database systems, programming, or information management
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.
