- Use the right visual variables
- Provide context with annotations
- SFW - make sure that the results are relevant to the viewer
It was interesting for me to listen to the latest edition of Data Stories with interviewee Michelle Borkin. From the opening snippet, Michelle is confirming the fundamentals:
"Put a title on your graph, annotate the important things, label your axes, pick appropriate visual encodings, ..., people will understand your visualizations"
The basis of my "rules" come from own meandering experience as a practitioner, colored by the many subjective opinions that I have encountered. Michelle's advice comes from good old fashioned scientific experimentation - it is good to see that there is some convergence between the two!
Michelle is a Assistant Professor at Northeastern University, where she works on visualization (among other things). Papers include What Makes a Visualization Memorable? and Beyond Memorability: Visualization Recognition and Recall, both worth reading for anyone interested in the area.
Data visualization can be simple. Learn a few basics and work with your audience to design what suits them best.
As well as holding a Master's Degree in Data Analytics, Stephen Redmond is a practicing Data Professional of over 20 years experience. He is author of Mastering QlikView, QlikView Server and Publisher and the QlikView for Developer's Cookbook
