Singapore University of Social Sciences

Data Visualisation and Storytelling

Data Visualisation and Storytelling (ANL501)


ANL501 Data Visualisation and Storytelling aims to equip students with the knowledge and skills to construct compelling data visualisations using a programming and reproducible approach. The course will delve into the core concepts of data visualisations grounded in the principles of Grammar of Graphics. Students will gain fundamental skills in R to acquire, transform and manage data for visualisation. Students will also become proficient in developing R programs to construct visualisations tailored for different data types including univariate and multivariate categorical and numerical data, time series data, and spatial data. Emphasis will be placed on the implementation of visualisation best practices in R in the context of reproducible workflow and the application of sound storytelling principles to create data-rich presentations for decision-making.

Level: 5
Credit Units: 5
Presentation Pattern: EVERY REGULAR SEMESTER


  • Introduction to R and RStudio
  • R operations and programming
  • Data management in R
  • Principles of data storytelling and essential descriptive statistics
  • Introduction to R for data visualisation
  • The Grammar of Graphics and its components
  • Data preprocessing and data management with tidyverse
  • Reproducible workflow with RMarkdown
  • APIs for data acquisition
  • Visualising time series, numerical, categorical, and table data
  • Visualising spatial data
  • Storyboarding and best practices for data storytelling

Learning Outcome

  • Assess the data requirements for data visualisation
  • Compose data-rich visualisations based on the principles of Grammar of Graphics
  • Critique data stories constructively
  • Construct R programs for data visualisation
  • Create RMarkdown documents as part of a reproducible workflow
  • Design and implement a data visualisation workflow from data acquisition, data transformation, and then to data visualisation
  • Demonstrate understanding of descriptive statistics in the context of data visualisation
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