The course is included in these curricula and study modules
- Big data analytics 2016 - Big data analytics
- Big data analytics 2017 - Big data analytics
- Big data analytics 2018 - Big data analytics
- Big data analytics 2019 - Big data analytics
- Big data analytics 2020 - Big data analytics
- Big data analytics 2021 - Big data analytics - specialised professional studies
- Big data analytics 2022 - Big data analytics - specialised professional studies
- Big data analytics 2023 - Big data analytics - specialised professional studies
The course takes place in period
2 (2022-10-24 to 2022-12-31)
Level/category
Teaching language
English
Type of course
Compulsory
Cycle/level of course
Second
Recommended year of study
1
Total number of ECTS
5 cr
Competency aims
Aim of this course is to equip students with
the background knowledge to create visual
presentations that effectively support human
cognition by transforming raw data into
actionable insights and knowledge.
Learning outcomes
By the end of this course, students should
understand the main principles of good data
visualization and be able to apply them
effectively. Students are also expected to
identify, differentiate, and create the most
common chart types, as well as justify their
visualization choices.
Course contents
This course focuses on the basic principles of
Data visualization, incorporating elements of
Interface and Interaction design. The course
will teach students to design effective and
user-centric visualization and information
systems. Covered topics will include: Visual
Perception, Data types, Chart types, basics of
interaction & dash boarding, and geospatial
visualizations. This course focuses mainly on
the production of graphical material.
Recommended or required reading
Hans Rosling,
https://www.ted.com/talks/hans_rosling_shows_the_b External link
est_stats_you_ve_ever_seen#t-1171606
Juuso Koponen, Jonatan Hildén, Data
visualization handbook,
Aalto ARTS Books (2019)
Tamara Munzner, Visualization Analysis and
Design, CRC Press (2014)
Alberto Cairo, The functional art : an
introduction to information graphics and
visualization, New Riders cop. (2013)
Colin Ware, Information visualization :
perception for design, Morgan Kaufmann (2013)
Mode of Delivery
Participation in tuition
Assessment requirements
Assignment 1: Critique and improve
Students need to critique a ?bad? chart and
create a new version, which should also
incorporate at least one new data set to
provide more context to the original data.
Assignment 2: Final assignment
The final assignment will be similar to last
year?s, but will focus more on the
design side. Students should follow Munzner?s
framework when creating their
assignment and need to convincingly explain
their (design) choices and decisions.
Teacher
- Becker Sandra
- Scherbakov-Parland Andrej
- Westerlund Magnus
Examiner
Westerlund Magnus
Home page of the course
Group size
No limit (28 students enrolled)
Assignments valid until
12 months after course has ended
Course enrolment period
2022-10-10 to 2022-11-06
Date | Time | Room | Title | Description | Organizer |
---|---|---|---|---|---|
2022-11-24 | 13:00 - 18:00 | Visual Analytics | Lectures held online | Becker Sandra Scherbakov-Parland Andrej Westerlund Magnus |
|
2022-11-25 | 13:00 - 18:00 | Visual Analytics | Lectures held online | Becker Sandra Scherbakov-Parland Andrej Westerlund Magnus |
|
2022-12-02 | 13:00 - 18:00 | Visual Analytics | Lectures held online | Becker Sandra Scherbakov-Parland Andrej Westerlund Magnus |
|
2022-12-08 | 13:00 - 18:00 | Visual Analytics | Lectures held online | Becker Sandra Scherbakov-Parland Andrej Westerlund Magnus |
|
2022-12-09 | 13:00 - 18:00 | Visual Analytics | Lectures held online | Becker Sandra Scherbakov-Parland Andrej Westerlund Magnus |
|
2022-12-16 | 13:00 - 18:00 | Visual Analytics | Lectures held online | Becker Sandra Scherbakov-Parland Andrej Westerlund Magnus |