In this video the lecturer gives an overview of available resources and explains why we need data visualisation to interpret data, and to communicate our understanding. He also emphasises the advantages of automating the data visualisation pipeline for reproducibility and replicability.

Transcript of video "Data visualization: Introduction and motivation"

Links used in video "Data visualization: Introduction and motivation"

Lessons learned
  • When looking at data alone without visualising it, we may miss seeing important structure.
  • Avoid tools that cannot be automated/scripted.
  • Optimise for comprehension and accessibility.

Food for thought

  • Can you explain why the generation of figures as part of a data analysis pipeline needs to be automated?
  • What problems can you anticipate for a data visualisation workflow which is not automated?
  • Can you describe examples where statistical values alone, without an accompanying figure may not be enough?
Last modified: Tuesday, 3 January 2023, 12:36 PM