Content
Graphs are an excellent way to share your research data with your audience. But it's also hard: which graph type works best in which situation - and why? What color scheme should you use to strengthen your message? What are some common pitfalls to avoid? How can you add the perfect title, labels, legend and caption? How do you move beyond a boring pie or bar chart? In this workshop, we see how basic design and communication principles help you decide which graph type is best for you, which out-of-the-box graph types might grab the attention of your audience, and how you should style them so your message is loud and clear. We'll have a look at (mostly free) online and offline tools to create beautiful, clear and accurate graphs that go far beyond the default Excel visuals. Make the graphs in your next presentation, article or poster stand out!
By the end of this workshop you will have covered 4 themes:
- An introduction to data visualization
- Graphical representation of data
- Design and production of data visualization
- Visualization of scientific research
Day 1:
- An introduction to data visualization
- Properties of good data visuals
- Tools to create data visuals (static) and choosing the right chart type
Day 2:
- Feedback on homework assignment and tools to create data visuals (interactive)
- Using colour and text in data visuals and selected use cases for scientists (visualizing uncertainty, maps, qualitative charts)
For this course, particpants will be asked to work on an intermediate assignment (approx. 1 à 2 hrs.) after course day 1.
Practical information
Course dates and location:
Course HC01: 5 and 12 December 2024 | 9h30 - 17h00 | Campus Middelheim - Building G - Room G.017 |
Course HC02: 23 and 30 January 2025 | 9h30 - 17h00 | Campus Middelheim - Building G - Room G.005 |
Teacher:
Koen Van den Eeckhout (Baryon design)
Language of the course:
English
Docop-points:
1,2 points
Registration:
Via Sisa Self Service. Log in with your student account. Registration is possible as from 3 September 2024 and after you've been (re-)enrolled as a PhD student for 2024-2025.