DATA VIZ
IE, Sandra Becker MAD 05/2018
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INTRO DATAVIZ
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WHY DO WE NEED DATA VIZ?
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"THE PURPOSE OF DATA VISUALIZATION ARE INSIGHTS NOT PICTURES."
BEN SCHNEIDERMAN
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"LET MY DATASET CHANGE YOUR MINDSET."
HANS ROSLING
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"IT'S NOT WHAT YOU LOOK AT THAT MATTERS, IT'S WHAT YOU SEE ."
HENRY DAVID THOREAU
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"ABOVE ALL ELSE SHOW THE DATA ."
EDWARD TUFTE
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WHAT IS DATA VIZ?
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BIG
DATAVIZ
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REALTIME
DATAVIZ
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DYNAMIC
DATAVIZ
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SMART
DATAVIZ
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DIMENSIONAL
DATAVIZ
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ART
DATAVIZ
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DATAVIZ PRACTICE
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HOW TO CREATE A DATA VIZ?
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#1 OBJECTIVE DEFINE
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#2 DATA EXPLORE
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#3 IDEA DESIGN
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VIZ TYPES
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CHOOSE THE RIGHT VIZ TYPE?
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VIZ ENCODING
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#4 TOOL EXECUTION
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PROGRAMMING
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LOCATION
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EXPLORE
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#5 RESULT REVIEW
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U X
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HUMAN PERCEPTION
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GOODVIZ
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BADVIZ
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WTFVIZ
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ALGORITHM VIZ
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ASSIGNMENT01
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PART01
VIZEVALUATION
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01 CHOOSE A DATA VIZ PROJECT
02 DISCUSS THE QUESTION CATALOGUE
03 SUMMARISE YOUR EVALUATION
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Q1 WHAT IS THE OBJECTIVE?
Q2 WHAT IS THE CLASS (DATA VIZ OR INFOGRAPHIC)?
Q3 WHAT IS THE VIZ TYPE, IS THE CHOICE ACCURATE?
Q4 WHAT VIZ ENCODING ARE USED, IS THE CHOICE ACCURATE?
Q5 WHAT ARE THE POSSIBILITIES TO INTERACT?
Q6 ANY PROBLEMS REGARDING HUMAN PERCEPTION?
Q7 ANY IMPROVEMENTS REGARDING THE UX?
Q8 IS IT A GOOD DATA VIZ? WHY/WHY NOT?
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PART02
VIZCREATION
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01 CHOOSE ONE EXAMPLE
02 DEFINE OBJECTIVES & EXPLORE THE DATA
04 TRY DIFFERENT VIZ TYPES AND VIZ ENCODINGS
05 CHOOSE THE MOST ACCURATE DATA VIZ
06 SUMMARISE YOUR CREATIONS
07 EXPLAIN THE REASONS FOR YOUR CHOICE
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PERCEPTION DESIGN
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ANSCOMBE'S QUARTET
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SEEING = UNDERSTANDING
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WEBER'S LAW
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PRESENTING TRUTH
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#1 show the data
#2 tell the truth
#3 help the viewer to think about the information rather than the design
#4 encourage the eye to compare the data
#5 make large dataset coherent
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COLOR
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danger
passion
blood
love
agressive
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environment
nature
permission
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sun
happiness
playful
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water
cool
quietness
hope
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death
luxury
sophistication
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wedding
pure
innocent
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POSITION
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REDUNDANT
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INTERACTIVITY
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NAVEGAR
IDENTIFICAR
COMPROBAR
REDUCIR
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LOCATION VIZ CARTO
PART 1
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VISUALIZE ANALYSE VISUALIZE ANALYSE VISUALIZE ANALYSE VISUALIZE
VISUALIZE ANALYSE VISUALIZE ANALYSE VISUALIZE
VISUALIZE ANALYSE VISUALIZE ANALYSE
VISUALIZE ANALYSE VISUALIZE
VISUALIZE ANALYSE
VISUALIZE
STOP!
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HOW TO DEAL WITH BIG DATASETS?
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AGGREGATE HEXAGONAL BINNING & CLUSTERING
FILTER EXTREM & TARGET GROUPS
STYLE SIZE & OPACITY
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01 CUSTOMER CONCENTRATION HEATMAP
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02 EXTREM GROUP FILTER
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03 SPEND SEGMENTS
CLUSTERS
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04 TARGET GROUP
STYLING
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ALL IN 1 MAP
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LOCATION VIZ CARTO
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SHOP AREA PERFORMANCE
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01 TARGET GROUP
STYLING BY VALUE & ICON
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02 AREA OF INFLUENCE
CREATE TRAVEL OR DISTANCE BUFFERS
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02 AREA OF INFLUENCE
INTERSECT WITH THE SECOND LAYER & AGGREGATE & STYLE BY VALUE
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ASSIGNMENT02
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01 CHOOSE A DATASET
02 EXPLORAR THE DATA USING CARTO
03 CREAT ONE FINAL MAP & INTERPRETATION
04 EXPLAIN YOUR PROCESS AND CHOICE
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DYNAMIC VIZ D3.JS
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DYNAMIC VIZ D3.JS
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EXPLORATIVE VIZ GGPLOT2
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NETWORK VIZ
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VIZ STORYTELLING
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VIZ STORYTELLING
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FUTURE VIZ
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THANK YOU.
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