Data Visualisation workshop held by Flink Labs for the Visualizing.org data visualization marathon help in Sydney.

2. Melbourne Trains

3. Author driven vs Viewer driven

4. Melbourne Taxis

5. Exploration and Engagement

6. The Data’s Journey

7. Tell a story that you can interact with

8. Our Process
Iteration
Explore and analyse
Develop detailed
data. Define
design and Develop and deploy
requirements and
visualisation visualisation
conceptual design.
prototypes.
Feedback
Exploration Design Development
Gather and review data Create interactive prototypes Develop select visualisation
Assess audience needs Design technical architecture Implement server backend
Sketch conceptual designs Design detailed interactions Handover and training
Produce data profile

9. Author driven vs Viewer driven
Martini Glass
Author driven, linear narrative initially
Opens up to viewer driven at end
Tell a story then exploration
e.g. Interactive news
Interactive Slideshow
Balance of author and viewer driven
Exploration at each stage
Primarily linear narrative
Drill Down Story
Viewer driven narrative
Initial high level overview
Viewer then drills into detail
e.g. Interactive map
J. Heer

10. Not just the averages

11. Draw the viewer into the data

12. Form
Visual Encoding
Orientation Line Length Line Width Size
Shape Curvature Enclosure Motion
Colour Position
Intensity Hue 2-D Position Grouping
Ware

13. Gestalt Principles of Visual Perception
Similarity Similarity Connection
Continuity Closure Enclosure
Proximity Proximity Proximity

14. Expanding Toolsets

15. “Real artists ship”
Don’t over reach
Focus on the story of the data
Use visual encoding wisely
Don’t make your viewer work too hard at the start