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Data Visualizations Decoded
Tweet: juliargentinaG
No definitions
No central repository
No use case driven
approach
Visualization Taxonomies (220 years back)
196
7
199
6
199
7
2003 20041786
Layout
Line, Bar,
Pie Chart
The Commercial &
Pol...
Visualization Taxonomies (and counting)
2008 20132007
Data Type
Data,
Information,
Concept,
Strategy,
Metaphor,
Compound
P...
5
Changing the Question
“I want to see the scatter
plot view of this data.” with
“I want to see what the
correlations are ...
Collect & Organize
Collect & Organize & Discover
Attributes
Grouping
Ranking
Calculations
Drill
Down
Time Correlations
Flow
Networks Predicti...
Patterns of Use
Comparisons: Attributes, Time, Rank
Connections: Drill Down, Flow, Grouping,
Networks
Conclusions: Calcula...
9
Comparisons
Attributes, Time, Rank
Defining the Question
“I want to see
a pie chart
to”….. “I want
to see the
attributes of
this fund.”SOURCE: https://fundre...
Attributes
Understanding the
characteristics of
an object
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Attributes
Understanding the
characteristics of
an object
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Defining the Question
“I want to see
a line chart.”
….. “I need to
see what has
occurred.”
SOURCE: https://systematicedge....
Time
Tracking
events as they
unfold over
time
Fund Assets
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Time
Tracking
events as they
unfold over
time
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Time
Tracking
events as they
unfold over
time
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Defining the Question
“I want to see
a heat
map.”….. “I
need to see
who’s landed
on top.” SOURCE:
Visualizing Financial Da...
Rank Establishing
relationship
s of greater
than, less
than or
equal to
SOURCE:
Visualizing Financial Data
Rodriguez & Kac...
Connections
Drill Down, Flows, Groups, Networks
Defining the Question
….. “I need to
see both
aggregates &
details.”
SOURCE: CalPERS Annual Report 2013
Drill Down
Shifting
from
summary
to detail
information
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Drill Down
Shifting
from
summary
to detail
information
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Defining the Question
….. “I need
to see the
influence
and
impact.”
SOURCE: Smith College Annual Report 2013
Flows
Transformin
g data from
one stage to
another
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Defining the Question
….. “I need to see the
major themes.”
Groups
Creating
categories
from a
data set
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Groups
Creating
categories
from a
data set
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Defining the Question
….. “I need to see
connections and links.”
Networks
Connectin
g the dots
between
discrete
locations
SOURCE: Mappa Mundi
30
Conclusions
Calculations, Correlations, Predictive
Defining the Question
….. “I want to see the outcomes of
this distance calculation.”
SOURCE: Wikipedia
Calculations
Translatin
g
equations
to be
visually
deciphere
d
SOURCE: Wikipedia
Defining the Question
….. “I need
to see the
level of
correlation.
”
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczma...
Correlations
Discovering
congruency
between dat
a sets
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Correlations
Discovering
congruency
between dat
a sets
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Correlations
Discovering
congruency
between dat
a sets
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Correlations
Discovering
congruency
between dat
a sets
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Defining the Question
….. “I need to
foresee the
possibilities.”
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Predictive
Predicting
outputs
based on
learned
inputs
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Predictive
Predicting
outputs
based on
learned
inputs
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Predictive
Predicting
outputs
based on
learned
inputs
SOURCE:
Visualizing Financial Data
Rodriguez & Kaczmarek
Collect & Organize & Discover
Attributes
Grouping
Ranking
Calculations
Drill
Down
Time Correlations
Flow
Networks Predicti...
www.vizipedia.com
Browse
Reference
Contribute
Tweet: juliargentinaG
Thanks!
Publish
SOURCE: http://www.sapient.com/content/dam/sapient/sapientglobalmarkets/pdf/thought-leadership/crossings-fall2012....
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Data Visualizations Decoded 2015

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Designing data visualizations presents us with unique and interesting challenges: how to tell a compelling story; how to deliver important information in a forthright, clear format; and how to make visualizations beautiful and engaging.

Publié dans : Données & analyses
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Data Visualizations Decoded 2015

  1. 1. Data Visualizations Decoded Tweet: juliargentinaG
  2. 2. No definitions No central repository No use case driven approach
  3. 3. Visualization Taxonomies (220 years back) 196 7 199 6 199 7 2003 20041786 Layout Line, Bar, Pie Chart The Commercial & Political Atlas PLAYFAIR Data Type, Layout Diagrams, Networks, Maps Semiology of Graphics BERTIN Data Type 1D,2D,3D, Temporal, Multi- dimensional, Tree, Network Task Overview, Zoom, Filter, Details, Relate, History, Extract The Eyes Have It: A Task by Data Type Taxonomy for Information Visualization SHNEIDERMAN Domain, Layout Scientific, GIS, Multi- dimensional, Information Landscapes, Nodes & Links, Trees, Text Transforms The Structure of the Information Visualization Design Space CARD Layout Metric, topological, grouping, composite space Syntactic Structures in Graphics ENGELHARDT Algorithm Discrete or Continuous Rethinking Visualization: A High-level Taxonomy TROY 2000 A taxonomy of visualization techniques using the data state reference model CHI Domain, Data Type, Layout Scientific, GIS, 2D, Multi- dimensional Plots, Information Landscapes, Trees, Network, Text, Web Visualization, Visualization Spreadsheets
  4. 4. Visualization Taxonomies (and counting) 2008 20132007 Data Type Data, Information, Concept, Strategy, Metaphor, Compound Periodic Table for Management EPPLER Task Quantities, Proportions, Flows, Hierarchies, Networks, Spatial, Navigation, Filtering, Arrangement, etc. Infodesign patterns BEHRENS Data Type, Layout, Task Area, Bar, Circle, Diagram, Distribution, Grid& Matrix, Line, Map, Point, Table, Text, Trees & Network What Makes a Visualization Memorable BORKIN Wolfram MATLAB Technical Computing Plotly ManyEye s Online Web Apps RAW Qlik Tableau Visualization Software Highcharts D3 Frameworks 2006 Layout, Task Spatialization, Shape, Color, Prospective Interaction Reviewing Data Visualization: an Analytical Taxonomical Study RODRIGUES Solutions reflect:  Layout  Data type  Task
  5. 5. 5 Changing the Question “I want to see the scatter plot view of this data.” with “I want to see what the correlations are with this data.”
  6. 6. Collect & Organize
  7. 7. Collect & Organize & Discover Attributes Grouping Ranking Calculations Drill Down Time Correlations Flow Networks Predictive
  8. 8. Patterns of Use Comparisons: Attributes, Time, Rank Connections: Drill Down, Flow, Grouping, Networks Conclusions: Calculations, Correlations, Predictive
  9. 9. 9 Comparisons Attributes, Time, Rank
  10. 10. Defining the Question “I want to see a pie chart to”….. “I want to see the attributes of this fund.”SOURCE: https://fundresearch.fidelity.com/mutual-funds/composition/316390772
  11. 11. Attributes Understanding the characteristics of an object SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  12. 12. Attributes Understanding the characteristics of an object SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  13. 13. Defining the Question “I want to see a line chart.” ….. “I need to see what has occurred.” SOURCE: https://systematicedge.wordpress.com/2012/12/23/hedge-fund-performance/inception-equity/
  14. 14. Time Tracking events as they unfold over time Fund Assets SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  15. 15. Time Tracking events as they unfold over time SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  16. 16. Time Tracking events as they unfold over time SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  17. 17. Defining the Question “I want to see a heat map.”….. “I need to see who’s landed on top.” SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  18. 18. Rank Establishing relationship s of greater than, less than or equal to SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  19. 19. Connections Drill Down, Flows, Groups, Networks
  20. 20. Defining the Question ….. “I need to see both aggregates & details.” SOURCE: CalPERS Annual Report 2013
  21. 21. Drill Down Shifting from summary to detail information SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  22. 22. Drill Down Shifting from summary to detail information SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  23. 23. Defining the Question ….. “I need to see the influence and impact.” SOURCE: Smith College Annual Report 2013
  24. 24. Flows Transformin g data from one stage to another SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  25. 25. Defining the Question ….. “I need to see the major themes.”
  26. 26. Groups Creating categories from a data set SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  27. 27. Groups Creating categories from a data set SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  28. 28. Defining the Question ….. “I need to see connections and links.”
  29. 29. Networks Connectin g the dots between discrete locations SOURCE: Mappa Mundi
  30. 30. 30 Conclusions Calculations, Correlations, Predictive
  31. 31. Defining the Question ….. “I want to see the outcomes of this distance calculation.” SOURCE: Wikipedia
  32. 32. Calculations Translatin g equations to be visually deciphere d SOURCE: Wikipedia
  33. 33. Defining the Question ….. “I need to see the level of correlation. ” SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  34. 34. Correlations Discovering congruency between dat a sets SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  35. 35. Correlations Discovering congruency between dat a sets SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  36. 36. Correlations Discovering congruency between dat a sets SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  37. 37. Correlations Discovering congruency between dat a sets SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  38. 38. Defining the Question ….. “I need to foresee the possibilities.” SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  39. 39. Predictive Predicting outputs based on learned inputs SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  40. 40. Predictive Predicting outputs based on learned inputs SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  41. 41. Predictive Predicting outputs based on learned inputs SOURCE: Visualizing Financial Data Rodriguez & Kaczmarek
  42. 42. Collect & Organize & Discover Attributes Grouping Ranking Calculations Drill Down Time Correlations Flow Networks Predictive
  43. 43. www.vizipedia.com Browse Reference Contribute
  44. 44. Tweet: juliargentinaG Thanks!
  45. 45. Publish SOURCE: http://www.sapient.com/content/dam/sapient/sapientglobalmarkets/pdf/thought-leadership/crossings-fall2012.pdf

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