Official course description, subject to change:

Preliminary info last published 15/11-23
Course info
Language:
English
ECTS points:
7.5
Course code:
BAKRDAV1KU
Participants max:
30
Offered to guest students:
yes
Offered to exchange students:
yes
Offered as a single subject:
yes
Price for EU/EEA citizens (Single Subject):
10625 DKK
Programme
Level:
Bachelor
Programme:
BSc in Digital Design and Interactive Technologies
Staff
Course semester
Semester
Forår 2025
Period
Summer 2025
Start
7 July 2025
End
1 August 2025
Exam
Exam type
ordinær
Internal/External
ekstern censur
Grade Scale
7-trinsskala
Exam Language
GB
Abstract

Learn to make custom data visualisations by designing with data. Uncover the possibilities of data visualization and discover how to play with data in code.

Description

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 data itself, creative visualisations, and how to “communicate” with the computer through code. In this course, we practice advanced data visualisation, delving into how to create visualisations that convey multivariate 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