Overview
This foundational course examines data as a technical, social, cultural, and ethical object. Students study the data life cycle from question formulation and collection through storage, cleaning, analysis, visualization, interpretation, preservation, and reuse.
The course develops critical data literacy through interdisciplinary datasets and introductory spreadsheet or programming tools. Topics include data structures, metadata, databases and files, collection methods, data quality, missingness, measurement error, bias, exploratory analysis, visualization, documentation, reproducibility, open data, intellectual property, privacy, fairness, accessibility, and the societal effects of algorithmic systems. Students translate real-world questions into data questions, evaluate provenance and quality, perform basic transformations and summaries, communicate evidence with uncertainty, and identify ethical risks.
Learning Outcomes
- Formulate real-world problems as answerable data questions with appropriate scope and measurable concepts.
- Classify structured, semi-structured, and unstructured data and select suitable storage, metadata, and documentation practices.
- Evaluate data provenance, quality, missingness, measurement error, bias, representativeness, and limitations.
- Apply introductory spreadsheet or programming techniques to transform, summarize, and inspect interdisciplinary datasets.
- Construct honest, clear, and accessible visualizations that reflect data structure and uncertainty.
- Analyze collection methods, including surveys, experiments, observational studies, and digital traces, for validity and ethical implications.
- Synthesize analytical decisions in reproducible documentation that supports preservation, reuse, and review.
- Assess privacy, intellectual property, fairness, accessibility, and societal risks associated with data and algorithmic systems.
- Communicate evidence-based findings with appropriate qualifications, uncertainty, and limitations.
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 question and provenance assignment | 15.00% |
| Test | Data concepts and quality test | 15.00% |
| Deliverable | Data documentation and reproducibility deliverable | 20.00% |
| Test | Exploratory analysis and visualization practical test | 20.00% |
| Exam | Comprehensive final examination | 30.00% |
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.
