CourseSpecifications
Valid as from the academic year 2024-2025

Data Visualization (C004041)

Course size
Credits 3.0(nominal values; actual values may depend on programme)
Study time 90 h

Course offerings and teaching methods in academic year 2024-2025
A (semester 2)
Dutch
Gent
Lecturers in academic year 2024-2025
Mesuere, Bartlecture

WE02

lecturer-in-charge

Offered in the following programmes in 2024-2025
Master of Science in Teaching in Science and Technology(main subject Computer Science)
Master of Science in Teaching in Science and Technology(main subject Mathematics)
Master of Science in Computer Science
Master of Science in Mathematics

crdts
3333offering
AAA
A

Teaching languages
Dutch
Keywords
data, data visualization, data analysis
Position of the course
ContentsIntroduction• Why data visualization• Historical perspective• Principles of data visualization• • Perceiving, Interpreting, Comprehending• • Trustworthy, accessible, elegant
Data• Working with data
• Recognizing and naming the different data types
Visual encoding of data
• Representing data using marks and properties• Knowing when to use which property• The use of color: saturation, hue and luminance
Chart fundamentals• An overview of 50+ existing graph types to represent categorical, hierarchical, relational,• temporal and spatial data
Technical skills• Introduction to Observable notebooks• Introduction to Vega Lite and the Grammar of Graphics• Introduction to D3.jsAssigments and project• Discussing existing visualisations and finding ways to improve them
• Creating a complete visualisation project from raw data to a finalized end result
Initial competences
Students are expected to be able to program in a high-level programming language such as
Java, JavaScript, Python, ...
Final competences(Approved)

11 Use standard APIs and tools to create visual displays of data, including graphs, charts,
1 tables, and histograms.
2 Have familiarity with several approaches to using a computer as a means for interacting with
1 and processing data.
3 Extract useful information from a dataset.
4 Analyze and select visualization techniques for specific problems.
5 Describe issues related to scaling data analysis from small to large data sets.
6 Describe the tradeoffs of visualization algorithms in terms of accuracy and performance.
7 Propose a suitable visualization design for a particular combination of data characteristics
1 and application tasks.
8 Analyze the effectiveness of a given visualization for a particular task.
Conditions for credit contract
Access to this course unit via a credit contract is determined after successful competences assessment
Conditions for exam contract
Access to this course unit via an exam contract is unrestricted
Teaching methods
LectureExtra information on the teaching methods
Interactive lectures consisting of theory, analyzing and discussing examples, and discussing
the case studies made by the students as home work.
Study material
Type: Handbook
Name: Data Visualisation - A handbook for data driven design (Andy Kirk)
Indicative price: € 30
Optional: yes
Language : English
Author : Andy Kirk
Type: Slides
Name: Slides
Indicative price: Free or paid by faculty
Optional: noReferences
Optional books:• Data Visualisation - A handbook for data driven design (Andy Kirk)• Interactive Data Visualization for the Web (Scott Murray)
Course content-related study coaching
Assessment moments
continuous assessment
Examination methods in case of periodic assessment during the first examination period
Examination methods in case of periodic assessment during the second examination period
Examination methods in case of permanent assessment
Assignment
Possibilities of retake in case of permanent assessment
examination during the second examination period is possible in modified form
Extra information on the examination methods
Students will be evaluated by reporting about a number of case studies they analyzed as home
work assignment. Additionally, they will work on a project in team.
Calculation of the examination mark100% permanent evaluation
If the student does not pass in the first examination period, a new assignment will be providedfor the second examination period.
Facilities for Working Students(Approved)2

Mogelijkheid tot vrijstelling van aanwezigheid met vervangende opdracht na overleg met
verantwoordelijke lesgever(Approved)3