1.21/03/14 pag. 1 Information visualization lecture 5 interaction Katrien Verbert Department of Computer Science Faculty of Science Vrije Universiteit Brussel katrien.verbert@vub.ac.be

2. 21/03/14 pag. 2 Where are we? Fundamentals Percep'on Vision Color Principles Techniques Representa'on Presenta'on Interac3on Applica3ons Casestudies Dashboards VisualAnaly3cs 3. 21/03/14 pag. 3 Interactive data visualizations Graphic design Dataanalysis Sta3c visualiza3on Slidesource:MichaelPorath 4. 21/03/14 pag. 4 Interactive data visualizations Graphic design Dataanalysis Interac'on Design Sta3c visualiza3on User interface design Exploratory data analysis Interac3ve visualiza3on Slidesource:MichaelPorath 5. 21/03/14 pag. 5 Why interaction? When is (static) representation not enough? 6. 21/03/14 pag. 6 Why interaction? When is (static) representation not enough? Scale Toomanydatapoints Toomanydierentdimensions Storytelling Explora3on Learning Slidesource:MichaelPorath 7. 21/03/14 pag. 7 User intent: what is the objective? Select Recongure Encode Abstract/ elaborate Filter Connect Explore Yietal.2007 8. 21/03/14 pag. 8 User intent: what is the objective? Select Recongure Encode Abstract/ elaborate Filter Connect Explore Userintent 9. 21/03/14 pag. 9 Select / focus Mark something interesting. 10. 21/03/14 pag. 10 Select/focus 11. 21/03/14 pag. 11 Select/focus Pick a detail from a larger dataset to keep track of it. 12. 21/03/14 pag. 12 Example: placemark feature in Google Earth 13. 21/03/14 pag. 13 Explore Show something different. 14. 21/03/14 pag. 14 Explore example technique panning 15. 21/03/14 pag. 15 Explore example technique panning 16. 21/03/14 pag. 16 NY Times: Mapping America Overcome limitations of display size Most common technique: panning SanFrancisco NewYork 17. 21/03/14 pag. 17 h