SlideShare a Scribd company logo
1 of 35
Interactive Data
Visualization (with D3.js)
            Lynn Cherny
       lynn@ghostweather.com
              @arnicas
Shneiderman’s Infovis mantra (1996)




The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
Shneiderman, B. 1996

                                                                        3
Shneiderman’s Infovis mantra (1996)

Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand


The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
Shneiderman, B. 1996

                                                                        3
Updated with Jeff Heer in 2012




Heer, J and B. Shneiderman, “Interactive Dynamics for Visual Analysis:A taxonomy of tools that support the fluent and flexible use of visualizations”
http://queue.acm.org/detail.cfm?id=2146416
Updated with Jeff Heer in 2012




Heer, J and B. Shneiderman, “Interactive Dynamics for Visual Analysis:A taxonomy of tools that support the fluent and flexible use of visualizations”
http://queue.acm.org/detail.cfm?id=2146416
Updated with Jeff Heer in 2012




Heer, J and B. Shneiderman, “Interactive Dynamics for Visual Analysis:A taxonomy of tools that support the fluent and flexible use of visualizations”
http://queue.acm.org/detail.cfm?id=2146416
Updated with Jeff Heer in 2012




Heer, J and B. Shneiderman, “Interactive Dynamics for Visual Analysis:A taxonomy of tools that support the fluent and flexible use of visualizations”
http://queue.acm.org/detail.cfm?id=2146416
“Visualize data by choosing visual
            encodings”
Position on common scale



                                                               Position on unaligned scale

                                                 Accuracy of
                                                 Judgments               Length



                                                                        Direction

Cleveland-McGill Hierarchy
       of Perception                                                     Angle



                                                                          Area



                                                                        Volume
                                                Genericness
                                                of Judgments
                                                                       Curvature



                                                                        Shading

Image from Alberto Cairo’s The Functional Art
                                                                       Saturation
Aka, “Why pie charts are (often) bad”




           http://en.wikipedia.org/wiki/Pie_chart
Aka, “Why pie charts are (often) bad”




           http://en.wikipedia.org/wiki/Pie_chart
“Filter out data to focus on relevant
                items ”
Crossfilter airline data demo: http://square.github.com/crossfilter/




                                 9
“Sort items to expose patterns”
http://www.nytimes.com/interactive/2012/09/14/us/how-the-chicago-public-school-district-compares.html
By me, adapting code of @mbostock’s: http://www.ghostweather.com/essays/talks/networkx/adjacency.html
“Select items to hightlight, filter, or
         manipulate them”
by @jasondavies:
http://bl.ocks.org/1341281
NVD3: A higher level d3 library of chart types:
         http://nvd3.com/ghpages/scatter.html
My Demo App
“Navigate to examine high level
 patterns and low-level detail”
   (the old “zoom / details on demand”)
http://dataviz.rennesmetropole.fr/quisommesnous/index-fr.php
A few more zoom examples...

       Zoom/pan axis example: http://
           bl.ocks.org/1182434




 Some map zoom code examples: https://bl.ocks.org/1284044
               http://bl.ocks.org/2206590

                                 19
“Coordinate views for linked, multi-
    dimensional exploration”
http://mbostock.github.com/d3/talk/20111116/iris-splom.html
http://woodchanges.com/
“Annotate patterns to document
           findings”
“Annotate patterns to document
                   findings”


“What we don’t do: here’s a bunch of data, we hope you find
                something interesting in it.”
                 -- paraphrase of Amanda Cox, NYT
http://www.nytimes.com/interactive/2012/08/24/us/drought-crops.html
http://www.nytimes.com/interactive/2012/02/13/us/politics/2013-budget-proposal-graphic.html
http://www.nytimes.com/interactive/2012/09/20/world/africa/the-attack-on-the-american-
                            mission-in-benghazi-libya.html
Learning D3.js
• The D3.js repo website has a tutorials list: https://github.com/
  mbostock/d3/wiki/Tutorials

• Short intro book by Mike Dewar: http://shop.oreilly.com/
  product/0636920025429.do

• Scott Murray’s forthcoming intro book and his tutorials: http://
  alignedleft.com/tutorials/

• Some great tutorials by Jim Vallandingham for more advanced
  folks, including how to make a NYT-style stepper and a bubble
  vis like the ones I showed: http://vallandingham.me/
Join the local D3 meetup!

               Next talk is Oct 22:

http://www.meetup.com/Boston-d3-js-User-Group/events/83944092/




                                 28
lynn @
GhostWeather.com
      Thanks!

More Related Content

Viewers also liked

GraphQL: Enabling a new generation of API developer tools
GraphQL: Enabling a new generation of API developer toolsGraphQL: Enabling a new generation of API developer tools
GraphQL: Enabling a new generation of API developer toolsSashko Stubailo
 
Gephi Consortium Presentation
Gephi Consortium PresentationGephi Consortium Presentation
Gephi Consortium PresentationGephi Consortium
 
A Fast and Dirty Intro to NetworkX (and D3)
A Fast and Dirty Intro to NetworkX (and D3)A Fast and Dirty Intro to NetworkX (and D3)
A Fast and Dirty Intro to NetworkX (and D3)Lynn Cherny
 
GraphQL Story: Intro To GraphQL
GraphQL Story: Intro To GraphQLGraphQL Story: Intro To GraphQL
GraphQL Story: Intro To GraphQLRiza Fahmi
 

Viewers also liked (8)

GraphQL: Enabling a new generation of API developer tools
GraphQL: Enabling a new generation of API developer toolsGraphQL: Enabling a new generation of API developer tools
GraphQL: Enabling a new generation of API developer tools
 
Chap14
Chap14Chap14
Chap14
 
Gephi Consortium Presentation
Gephi Consortium PresentationGephi Consortium Presentation
Gephi Consortium Presentation
 
A Fast and Dirty Intro to NetworkX (and D3)
A Fast and Dirty Intro to NetworkX (and D3)A Fast and Dirty Intro to NetworkX (and D3)
A Fast and Dirty Intro to NetworkX (and D3)
 
GraphQL
GraphQLGraphQL
GraphQL
 
GraphQL Story: Intro To GraphQL
GraphQL Story: Intro To GraphQLGraphQL Story: Intro To GraphQL
GraphQL Story: Intro To GraphQL
 
D3.js for beginners
D3.js for beginnersD3.js for beginners
D3.js for beginners
 
reveal.js 3.0.0
reveal.js 3.0.0reveal.js 3.0.0
reveal.js 3.0.0
 

Similar to Interactive Data Visualization (with D3.js)

Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Star...
Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Star...Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Star...
Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Star...David Sturtz
 
Context is King: AR, AI, Salience, and the Constant Next Scenario
Context is King: AR, AI, Salience, and the Constant Next ScenarioContext is King: AR, AI, Salience, and the Constant Next Scenario
Context is King: AR, AI, Salience, and the Constant Next ScenarioClark Dodsworth
 
Gmcghee bayvis meetup_111027
Gmcghee bayvis meetup_111027Gmcghee bayvis meetup_111027
Gmcghee bayvis meetup_111027Kristen Chan
 
Recognition Markets and Visual Privacy
Recognition Markets and Visual PrivacyRecognition Markets and Visual Privacy
Recognition Markets and Visual PrivacyRyan Shaw
 
EDF2013: Big Data Tutorial: Marko Grobelnik
EDF2013: Big Data Tutorial: Marko GrobelnikEDF2013: Big Data Tutorial: Marko Grobelnik
EDF2013: Big Data Tutorial: Marko GrobelnikEuropean Data Forum
 
Ben Shneiderman: Thrill of Discovery
Ben Shneiderman: Thrill of DiscoveryBen Shneiderman: Thrill of Discovery
Ben Shneiderman: Thrill of Discoveryruss9595
 
Comp4010 Lecture8 Introduction to VR
Comp4010 Lecture8 Introduction to VRComp4010 Lecture8 Introduction to VR
Comp4010 Lecture8 Introduction to VRMark Billinghurst
 
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...Shawn Jones
 
SBQS 2013 Keynote: Cooperative Testing and Analysis
SBQS 2013 Keynote: Cooperative Testing and AnalysisSBQS 2013 Keynote: Cooperative Testing and Analysis
SBQS 2013 Keynote: Cooperative Testing and AnalysisTao Xie
 
Fcv core sawhney
Fcv core sawhneyFcv core sawhney
Fcv core sawhneyzukun
 
Big Data Tutorial - Marko Grobelnik - 25 May 2012
Big Data Tutorial - Marko Grobelnik - 25 May 2012Big Data Tutorial - Marko Grobelnik - 25 May 2012
Big Data Tutorial - Marko Grobelnik - 25 May 2012Marko Grobelnik
 
Image retrieval and re ranking techniques - a survey
Image retrieval and re ranking techniques - a surveyImage retrieval and re ranking techniques - a survey
Image retrieval and re ranking techniques - a surveysipij
 
IRJET- Criminal Recognization in CCTV Surveillance Video
IRJET-  	  Criminal Recognization in CCTV Surveillance VideoIRJET-  	  Criminal Recognization in CCTV Surveillance Video
IRJET- Criminal Recognization in CCTV Surveillance VideoIRJET Journal
 
Multimedia Information Retrieval: What is it, and why isn't ...
Multimedia Information Retrieval: What is it, and why isn't ...Multimedia Information Retrieval: What is it, and why isn't ...
Multimedia Information Retrieval: What is it, and why isn't ...webhostingguy
 
Action Genome: Action As Composition of Spatio Temporal Scene Graphs
Action Genome: Action As Composition of Spatio Temporal Scene GraphsAction Genome: Action As Composition of Spatio Temporal Scene Graphs
Action Genome: Action As Composition of Spatio Temporal Scene GraphsSangmin Woo
 
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...Shawn Jones
 
Computer Vision: Pattern Recognition
Computer Vision: Pattern RecognitionComputer Vision: Pattern Recognition
Computer Vision: Pattern Recognitionedsfocci
 
Exploring Data Visualization
Exploring Data VisualizationExploring Data Visualization
Exploring Data VisualizationJim Jenkins
 

Similar to Interactive Data Visualization (with D3.js) (20)

Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Star...
Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Star...Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Star...
Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Star...
 
Context is King: AR, AI, Salience, and the Constant Next Scenario
Context is King: AR, AI, Salience, and the Constant Next ScenarioContext is King: AR, AI, Salience, and the Constant Next Scenario
Context is King: AR, AI, Salience, and the Constant Next Scenario
 
Gmcghee bayvis meetup_111027
Gmcghee bayvis meetup_111027Gmcghee bayvis meetup_111027
Gmcghee bayvis meetup_111027
 
Recognition Markets and Visual Privacy
Recognition Markets and Visual PrivacyRecognition Markets and Visual Privacy
Recognition Markets and Visual Privacy
 
EDF2013: Big Data Tutorial: Marko Grobelnik
EDF2013: Big Data Tutorial: Marko GrobelnikEDF2013: Big Data Tutorial: Marko Grobelnik
EDF2013: Big Data Tutorial: Marko Grobelnik
 
Online Visualization Tools, November 11, 2008
Online Visualization Tools, November 11, 2008Online Visualization Tools, November 11, 2008
Online Visualization Tools, November 11, 2008
 
1.pdf
1.pdf1.pdf
1.pdf
 
Ben Shneiderman: Thrill of Discovery
Ben Shneiderman: Thrill of DiscoveryBen Shneiderman: Thrill of Discovery
Ben Shneiderman: Thrill of Discovery
 
Comp4010 Lecture8 Introduction to VR
Comp4010 Lecture8 Introduction to VRComp4010 Lecture8 Introduction to VR
Comp4010 Lecture8 Introduction to VR
 
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
 
SBQS 2013 Keynote: Cooperative Testing and Analysis
SBQS 2013 Keynote: Cooperative Testing and AnalysisSBQS 2013 Keynote: Cooperative Testing and Analysis
SBQS 2013 Keynote: Cooperative Testing and Analysis
 
Fcv core sawhney
Fcv core sawhneyFcv core sawhney
Fcv core sawhney
 
Big Data Tutorial - Marko Grobelnik - 25 May 2012
Big Data Tutorial - Marko Grobelnik - 25 May 2012Big Data Tutorial - Marko Grobelnik - 25 May 2012
Big Data Tutorial - Marko Grobelnik - 25 May 2012
 
Image retrieval and re ranking techniques - a survey
Image retrieval and re ranking techniques - a surveyImage retrieval and re ranking techniques - a survey
Image retrieval and re ranking techniques - a survey
 
IRJET- Criminal Recognization in CCTV Surveillance Video
IRJET-  	  Criminal Recognization in CCTV Surveillance VideoIRJET-  	  Criminal Recognization in CCTV Surveillance Video
IRJET- Criminal Recognization in CCTV Surveillance Video
 
Multimedia Information Retrieval: What is it, and why isn't ...
Multimedia Information Retrieval: What is it, and why isn't ...Multimedia Information Retrieval: What is it, and why isn't ...
Multimedia Information Retrieval: What is it, and why isn't ...
 
Action Genome: Action As Composition of Spatio Temporal Scene Graphs
Action Genome: Action As Composition of Spatio Temporal Scene GraphsAction Genome: Action As Composition of Spatio Temporal Scene Graphs
Action Genome: Action As Composition of Spatio Temporal Scene Graphs
 
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
Abstract Images Have Different Levels of Retrievability Per Reverse Image Sea...
 
Computer Vision: Pattern Recognition
Computer Vision: Pattern RecognitionComputer Vision: Pattern Recognition
Computer Vision: Pattern Recognition
 
Exploring Data Visualization
Exploring Data VisualizationExploring Data Visualization
Exploring Data Visualization
 

More from Lynn Cherny

COCO's Memory Palace: A Strange Fantasia
COCO's Memory Palace: A Strange FantasiaCOCO's Memory Palace: A Strange Fantasia
COCO's Memory Palace: A Strange FantasiaLynn Cherny
 
Visualizing Networks
Visualizing NetworksVisualizing Networks
Visualizing NetworksLynn Cherny
 
Mining Someone Else's Magic World: Dwarf Fortress Story Generation
Mining Someone Else's Magic World: Dwarf Fortress Story GenerationMining Someone Else's Magic World: Dwarf Fortress Story Generation
Mining Someone Else's Magic World: Dwarf Fortress Story GenerationLynn Cherny
 
Bestseller Analysis: Visualization Fiction (for PyData Boston 2013)
Bestseller Analysis: Visualization Fiction (for PyData Boston 2013)Bestseller Analysis: Visualization Fiction (for PyData Boston 2013)
Bestseller Analysis: Visualization Fiction (for PyData Boston 2013)Lynn Cherny
 
The Bones of a Bestseller: Visualizing Fiction
The Bones of a Bestseller: Visualizing FictionThe Bones of a Bestseller: Visualizing Fiction
The Bones of a Bestseller: Visualizing FictionLynn Cherny
 
Nodebox for Data Visualization
Nodebox for Data VisualizationNodebox for Data Visualization
Nodebox for Data VisualizationLynn Cherny
 
Simplifying Social Network Diagrams
Simplifying Social Network Diagrams Simplifying Social Network Diagrams
Simplifying Social Network Diagrams Lynn Cherny
 
Design For Online Community: Beyond the Hype
Design For Online Community: Beyond the HypeDesign For Online Community: Beyond the Hype
Design For Online Community: Beyond the HypeLynn Cherny
 

More from Lynn Cherny (8)

COCO's Memory Palace: A Strange Fantasia
COCO's Memory Palace: A Strange FantasiaCOCO's Memory Palace: A Strange Fantasia
COCO's Memory Palace: A Strange Fantasia
 
Visualizing Networks
Visualizing NetworksVisualizing Networks
Visualizing Networks
 
Mining Someone Else's Magic World: Dwarf Fortress Story Generation
Mining Someone Else's Magic World: Dwarf Fortress Story GenerationMining Someone Else's Magic World: Dwarf Fortress Story Generation
Mining Someone Else's Magic World: Dwarf Fortress Story Generation
 
Bestseller Analysis: Visualization Fiction (for PyData Boston 2013)
Bestseller Analysis: Visualization Fiction (for PyData Boston 2013)Bestseller Analysis: Visualization Fiction (for PyData Boston 2013)
Bestseller Analysis: Visualization Fiction (for PyData Boston 2013)
 
The Bones of a Bestseller: Visualizing Fiction
The Bones of a Bestseller: Visualizing FictionThe Bones of a Bestseller: Visualizing Fiction
The Bones of a Bestseller: Visualizing Fiction
 
Nodebox for Data Visualization
Nodebox for Data VisualizationNodebox for Data Visualization
Nodebox for Data Visualization
 
Simplifying Social Network Diagrams
Simplifying Social Network Diagrams Simplifying Social Network Diagrams
Simplifying Social Network Diagrams
 
Design For Online Community: Beyond the Hype
Design For Online Community: Beyond the HypeDesign For Online Community: Beyond the Hype
Design For Online Community: Beyond the Hype
 

Interactive Data Visualization (with D3.js)

Editor's Notes

  1. \n
  2. \n
  3. \n
  4. \n
  5. \n
  6. \n
  7. \n
  8. \n
  9. \n
  10. \n
  11. \n
  12. \n
  13. \n
  14. \n
  15. \n
  16. \n
  17. \n
  18. \n
  19. \n
  20. \n
  21. \n
  22. Ex\nMikes stuff?\n
  23. \n
  24. \n
  25. \n
  26. \n
  27. \n
  28. \n
  29. \n
  30. \n
  31. \n
  32. \n