How can data become a story that people want to explore? In this directed studies course, students learn how to turn raw datasets into compelling, interactive data stories that combine analysis, narrative, and visual design. Rather than simply presenting charts and numbers, the course explores how to create experiences that invite audiences to discover patterns, explore perspectives, and engage with data. The goal is not simply to visualize data, but to make data come alive as an interactive story.

Content

This lecture explores the foundations, techniques, and design principles behind effective data-driven storytelling. It covers the following topics:

• Introduction to Data Journalism - Data journalism is a field of journalism that uses data as a primary source. It involves collecting, cleaning, analyzing, and interpreting datasets to uncover stories that may not be immediately visible. Unlike traditional reporting, which often focuses on interviews and observations, data journalism emphasizes empirical evidence and quantitative reasoning.

• Basic Visualization Techniques & Data Analysis - Data analysis transforms raw numbers into meaningful insights. Journalists use descriptive statistics, comparisons, trend analysis, and correlation analysis to identify patterns. Effective visualizations are accurate, simple, and focused. They highlight key insights without overwhelming the audience.

• Narrative Structure in Data Stories - Depending on the interplay between author and reader, a different narrative structure has to be chosen.

• Narrative Patterns in Data Stories - A narrative pattern in a low-level narrative device that serves a specific intent, like persuading or convincing the audience.

• Design Decisions and Evaluation - Which designs can raise empathy in the reader? How to design maps to tell stories?

Goals of this course

• Develop a coherent narrative structure for a data story.
• Integrate data insights into a compelling storyline.
• Use narrative patterns effectively.
• Write clear explanations that translate complex data into accessible language via visualizations.

Prerequisites

• Data Visualization - Basic Concepts

Past Student Projects

Summer 2026

• Are we really choosing what we buy?
• How a rule nobody wanted became law
• Will AI kill your job?
• Europe's air got cleaner. But not everywhere equally.
• Miniatur Bodenssee