eage Short Course 4 Data Visualization Principles for Scientists

Room 4

Monday

8 June 2026

Time

8:30-16:00

CPD Points

5

Instructor

Steve-Horne

 Steve Horne
Silixa Ltd

Data analysis science and big data with AI technology. Analyst or Scientist uses a computer and dashboard for analysis of information on complex data sets on computer. Insights development engineer

Overview

Participants will learn the basic principles of scientific data visualization. Topics will include the appropriate choice of colour and how to effectively choose and design plots. The course will include many data examples – both good and bad – and will include an opportunity to critique and redesign visuals based on the principles described in the course.

Course Outline

The instructor will show good, bad and ugly visualizations and will describe what makes a good data visualization and how some plots deceive – sometimes intentionally! There will be a fast historical tour taking in pivotal plots from, among others, Florence Nightingale, William Playfair, John W. Tukey and, of course, Edward Tufte. After this, participants will learn about human vision and how we can exploit our biology to efficiently process charts. We will then take a deep dive into human colour perception to discuss issues around colour vision deficiencies and how we can reach a wider audience through a careful choice of colours. The instructor will continue exploring this theme of human visual perception by reviewing the concept of pre-attentive attributes and the Gesthalt principles and how these can be employed in our charts. We will pay particular attention to line charts, pie charts and why 3D effects should only be used with caution. Next, we will review typefaces (fonts), tables and file formats before we move to a practical session where participants will be asked to choose a plot, identify any shortcomings, and then perform a data viz do-over based on the principles learnt during the day.

Course Topics

  1. Introduction – Overview of the course and why data visualization matters
  2. History – Short review of key contributors
  3. Human Vision – Colour and colour vision deficiencies.
  4. Colour – Choosing colour palettes.
  5. Plotarium – Alternative plot types.
  6. Typefaces – Selecting fonts.
  7. Tables – Designing tables.
  8. Design Principles – Gesthalt and other design principles.
  9. Posters – Layouts.
  10. Ethical Considerations.
  11. Makeover – Practical exercises.

Participants’ Profile

This course is for anyone who presents, reviews or interprets scientific data. Participants will learn how to create efficient data visualizations by choosing appropriate chart types and applying good design principles

Prerequisites

Participants should be reasonably confident with a data visualization tool e.g. Excel, Matlab, python etc. as we will be performing a data visualization makeover in our last session of the day.

TimeActivity
08:00Departure from conference center Messe Wien
09:00 – 09:20Safety introduction ITC
09:20 – 10:50ITC / TECH Center & Lab
10:50 – 11:00Group exchange
11:00 – 12:30ITC / TECH Center & Lab
12:30 – 13:30Lunch at the ITC event area
14:30Arrival back at conference center Messe Wien
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