this should be a circle new insights in data visualization
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This should be a circle New Insights in Data Visualization Jack van Wijk (TU/e) Stef van den Elzen (SynerScope) produce and collect Data People Visualization want insights The human visual system http://eofdreams.com The human visual


  1. This should be a circle

  2. New Insights in Data Visualization Jack van Wijk (TU/e) Stef van den Elzen (SynerScope)

  3. produce and collect Data People Visualization want insights

  4. The human visual system http://eofdreams.com

  5. The human visual system http://vinceantonucci.com

  6. Anscombe’s quartet Francis Anscombe, 1973

  7. Visualization produce and collect BIG Data People Visualization MESSY want insights

  8. Visualization @ TU/e – information visualization – software visualization – perception – geographic visuali scientific visualization – math vis – human computer interaction – visual analytics Data: flow fields – trees – graphs – tables – mobile data – events – … Applications: health care – software analysis – business – bioinformatics – forens

  9. Hierarchy + network Holten, 2006

  10. Hierarchical edge bundles Holten, 2006

  11. SequoiaView Van Wijk and Van de Wetering, 1999

  12. Botanically inspired treevis Kleiberg, Van de Wetering, van Wijk, 2001

  13. One picture is worth a lot of pixels • Focus on visual presentation • Show everything in one picture?

  14. Limits on perception… How many disks? Chris Healey: Perception in Visualization

  15. Limits on perception… How many disks? Chris Healey: Perception in Visualization

  16. Limits on perception… How many red objects? Chris Healey: Perception in Visualization

  17. Limits on perception… How many red objects? Chris Healey: Perception in Visualization

  18. Limits on perception… How many red disks? Chris Healey: Perception in Visualization

  19. Limits on perception… How many red disks? Chris Healey: Perception in Visualization

  20. Trends in visualization • Focus on interaction – Enable people to explore huge data • Integrate statistics and machine learning – Visual Analytics

  21. Decision trees Van den Elzen and Van W ijk, 2011

  22. Van den Elzen et al., 2014

  23. Telecom data Ivory Coast Van den Elzen et al., 2013

  24. From raw complex data  clear visual order for fast sense making

  25. Rijksmuseum van Oudheden • Visualize collection • Browse and navigate

  26. Data BIG? MESSY? ! Data 57,000 Object name: figuur; godin Description: Terracotta beeld van een vrouwelijke godin, met een hond. Met oude verlijmingen. Material: Aardewerk Size: 12,7 x 5,5 x 4,2 cm Date: romeins 150-200 Site: Nederland, Utrecht, Rhenen, graf 6b

  27. Mix of Structured & Unstructured data

  28. Data People Visualization Context Augment Data (Visual) Analytics

  29. Visualization Object name: figuur; godin Description: Terracotta beeld van een vrouwelijke godin, met een hond. Met oude verlijmingen. Material: Aardewerk Size: 12,7 x 5,5 x 4,2 cm Date: romeins 150-200 Site: Nederland, Utrecht, Rhenen, graf 6b

  30. Interaction Data People Visualization Context Augment Data (Visual) Analytics

  31. Cyber Security Financial Services Critical Open Data Infrastructure

  32. Conclusion – Visualization for Sensemaking • Generic solutions • Simple interaction / querying mechanisms • Use proven workhorses • Deal with large volume of data with – Visual analytics, augmentation • Deal with large variety of data – Interlinked views • System needs to support speed of thinking

  33. Thank you! Prof.dr.ir. Jack van Wijk dr.ir. Stef van den Elzen j.j.v.wijk@tue.nl stef.van.den.elzen@synerscope.com http://www.win.tue.nl/~vanwijk http://www.win.tue.nl/~selzen @jackvanwijk @StefvandenElzen

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