t.BA.DS.VDSS.20HS (Visualisation and Data Science Storytelling) 
Module: Visualisation and Data Science Storytelling
This information was generated on: 06 October 2022
No.
t.BA.DS.VDSS.20HS
Title
Visualisation and Data Science Storytelling
Organised by
T IDP
Credits
4

Description

Version: 4.0 start 01 February 2022
 

Short description

 This module provides basic knowledge on data visualization and data science storytelling. The course content includes visual elements, functions and effects as well as analysis and interpretation of data visualizations. In practical exercises, you will learn how to a) visualize data with appropriate software and tools and b) communicate effectively with data visualizations.

Module coordinator

 Ruckstuhl, Andreas, rkst

Learning objectives (competencies)
Objectives Competences Taxonomy levels
You are familiar with the visual repertoire of data visualizations and visualization types. F K1, K2
You are able to visualize data by using tools and appropriate software. M K3
You are able to describe the target group of your data visualization. M, SO K3
You are able to select the right visualization type for your message F K3
You can analyze data visualizations and evaluate their strengths and weaknesses. F, M K4
You can estimate possible impacts. F, M K4
You can design data visualizations and critically reflect on the result. F, M, SE K5, K6
You understand the interrelationship between data visualization and storytelling. You can apply this knowledge in the appropriate communication context. F, M, SO K2, K3

Module contents

 Visual elements and visualization types; Development of personas; Application and impact of data visualizations; Design of data visualizations; Analysis, interpretation and evaluation of data visualizations and data science stories; Tools and programming.

Teaching materials

 Slides, compulsory reading

Supplementary literature

 Ward, M., Grinstein, G. & Keim, D. (2015). Interactive data visualization. Foundations, techniques and applications (2nd ed.). CRC Press.
Kirk, A. (2016). Data Visualisation. A Handbook for Data Driven Design. London: Sage.
Cairo, A. (2016). The truthful art: Data, charts, and maps for communication. Berkeley: New Riders.
Munzner, T. (2015). Visualization analysis and design. Boca Raton: Taylor & Francis.
Nussbaumer Knaflic, C. (2015). Storytelling with data. Hoboken: Wiley.

Prerequisites

 none

Teaching language

 (X) German ( ) English

Part of International Profile

 ( ) Yes (X) No

Module structure

 Type 3a
  For more details please click on this link: T_CL_Modulauspraegungen_SM2025

Exams
Description Type Form Scope Grade Weighting
Graded assignments I during teaching semester Presentation (group work) oral 15 min. grading 20%
Graded assignments II during teaching semester Code In writing Runnable Code grading 10%
End-of-semester exam Written Exam (Moodle) written 45 min. grading 70%

Remarks

  

Legal basis

 The module description is part of the legal basis in addition to the general academic regulations. It is binding. During the first week of the semester a written and communicated supplement can specify the module description in more detail.

Note

Course: Visualisation and Data Science Storytelling - Praktikum
No.
t.BA.DS.VDSS.20HS.P
Title
Visualisation and Data Science Storytelling - Praktikum

Note

  • No module description is available in the system for the cut-off date of 02 August 2099.
Course: Visualisation and Data Science Storytelling - Vorlesung
No.
t.BA.DS.VDSS.20HS.V
Title
Visualisation and Data Science Storytelling - Vorlesung

Note

  • No module description is available in the system for the cut-off date of 02 August 2099.