Official course description, subject to change:
Basic info last published 1/10-23

Creative Data Visualisation (Summer University)

Course info
ECTS points:
Course code:
Participants max:
Offered to guest students:
Offered to exchange students:
Offered as a single subject:
Price for EU/EEA citizens (Single Subject):
10625 DKK
BSc in Digital Design and Interactive Technologies
Course manager
Part-time Lecturer
Course Academic Responsible
Associate Professor, Head of study programme
Course semester
Forår 2024
Summer 2024
8 July 2024
23 August 2024

Learn to make engaging, custom data visualisations by designing with data, illuminating patterns, and ultimately create meaning from tables and numbers.


Visualisation is an increasingly important part of making sense of our highly networked, data-rich world. Using a combination of interpretive methods and representational techniques, we will explore creative ways visualisation can make invisible relationships, structures and stories visible. This course takes a more individual approach to designing with data, going beyond standard charts.

We will learn to draw with data, with code as our enabler, using analog and digital techniques to practice creating data visualisations. We will learn how to collect, classify, encode, and display data and use interactivity to construct relationships and meaning. Along the way, we will also learn about principles and processes of data visualisation, how to develop small projects and scope expression.

The course focuses on topics of cycles, seasonality, repetition, and time in relation to the environment, changing climate, and ecosystem. We will use data about the past, present and future of our environment.

We will begin with a warm-up to the topics of design, data, programming, getting started with our topic. We will play and experiment with data visualisation in order to become familiar with d3.js. You will then create a small project, with continued code demos, design guidance and project mentorship.

Formal prerequisites

A basic knowledge of HTML and Javascript is highly recommended. This can be achieved by taking the following short tutorials:

Intended learning outcomes

After the course, the student should be able to:

  • Explain how to collect, classify, and encode data
  • Apply analog and digital techniques for making visualisations
  • Describe and apply the basics of drawing with D3.js / SVG
  • Reflect using metaphor, visual relationships, and interaction to make meaning out of data
  • Design a data visualisation experience
Ordinary exam
Exam type:
C: Submission of written work, External (7-point scale)
Exam variation:
C1G: Submission of written work for groups