OVERVIEW OF DATA VISUALIZATION · PDF fileOVERVIEW OF DATA VISUALIZATION ... Game Scores, Scientific Data, Biotech, ... • 2007 Google buys Gapminder (demographics data Viz)

INFOVIS8803DV > SPRING 17

OVERVIEW OF DATA VISUALIZATIONVisual Representations + Interaction Techniques

Prof. Rahul C. Basole

CS/MGT 8803-DV > January 11, 2017


Administrative

• Course Website

– Syllabus

– Schedule

– Assignments

– Grading

– Instructor & TA

– DataVis Resources

• T-Square

• Piazza– piazza.com/gatech/spring2017/8803

• Tumblr

datavis17.wordpress.com

Please cc TA on emails


Name Cards?


Recall: What is DataVis?

• DataVis is presenting data via interactive charts, graphs, maps so

that users can understand the data, answer questions about the

data and gain insights from the data

• It’s REPRESENTATION + INTERACTION


DataVis ≠ Scientific Visualization (SciVis) & Medical Data Visualization (MedVis)


DataVis ≠ SciVis & MedVis (cont.)

• SciVis/MedVis Data generally associated with physical positions in a

2D or 3D space – data has some “geometry”

• In DataVis, the data is generally abstract. We have to create a

geometry with which the data is encoded.


Biological Visualization (BioVis)


Why do we have humans in the

decision making loop?


Why have a computer in the loop?


And why is DataVis so important today?


Data Overload


Data Overload (cont.)



Data Overload (cont.)

• How to make use of data?

• How do we make sense of data?

• How do we harness data in decision-making processes?

• How do we avoid being overwhelmed?


The Challenge

Transform the data into information (understanding,

sensemaking, insight) thus making it useful to people.


The Problem

How?

Data Transfer

Web,

Books,

Papers,

Game Scores,

Scientific Data,

Biotech,

Shopping,

People,

Stock/Finance,

Social Media,

News,

…

Vision: 100 MB/s

Ears: <100 b/s

Telepathy

Haptic/Tactile

Smell

Taste

(BIG, WIDE, SMALL)

DATA


Human Vision

• Highest bandwidth sense

• Fast, parallel

• Pattern recognition

• Pre-attentive

• Extends memory and

cognitive capacity

• People think visually

Impressive.

Let’s use it!




1 2 8 1 7 6 8 7 5 6 1 3 8 9 7 6 5 4 6 9 8 4 5 0 6 9 8 5 6 0 4 9 8 2 8 2 6 7 6 2

9 8 0 9 8 5 8 4 5 8 2 2 4 5 0 9 8 5 6 4 5 8 9 4 5 0 9 8 4 5 0 9 8 0 9 4 3 5 8 5

9 0 9 1 0 3 0 2 0 9 9 0 5 9 5 9 5 9 5 7 7 2 5 6 4 6 7 5 0 5 0 6 7 8 9 0 4 5 6 7

3 8 4 5 7 8 9 8 0 9 8 2 1 6 7 7 6 5 4 8 7 6 3 6 4 9 0 8 5 6 0 9 1 2 9 4 9 6 8 6


1 2 8 1 7 6 8 7 5 6 1 3 8 9 7 6 5 4 6 9 8 4 5 0 6 9 8 5 6 0 4 9 8 2 8 2 6 7 6 2

9 8 0 9 8 5 8 4 5 8 2 2 4 5 0 9 8 5 6 4 5 8 9 4 5 0 9 8 4 5 0 9 8 0 9 4 3 5 8 5

9 0 9 1 0 3 0 2 0 9 9 0 5 9 5 9 5 9 5 7 7 2 5 6 4 6 7 5 0 5 0 6 7 8 9 0 4 5 6 7

3 8 4 5 7 8 9 8 0 9 8 2 1 6 7 7 6 5 4 8 7 6 3 6 4 9 0 8 5 6 0 9 1 2 9 4 9 6 8 6


Consider a (classical) example:

The Anscombe’s Quartet

• Statistics are the same for each of the four x-y tables (the quartet)

– Mean = 9

– Variance = 9

– Correlation = 0.816

– Linear regression: y = 3 + 0.5x

• So what’s different about the data?

• You could study the tables very closely (and make little progress)

• Or you could visualize the data!

F.J. Anscombe, “Graphs in Statistical Analysis”, American Statistician, February 1973, 17-21.


Take out Paper + Pencil!


HIDE


Another example … Which cereal has the most/least potassium?

Is there a relationship between potassium and fiber?

If so, are there any outliers?

Which manufacturer makes the healthiest cereals?

Questions:



Visualization

• Often thought of as process of making a graphic or an image

• Really is a cognitive process

– Form a mental image of something

– Internalize an understanding

• “The purpose of visualization is insight, not pictures”

– Insight: discovery, decision making, explanation


Bottom line

• Visuals help us think

– Provide a frame of reference, a temporary storage area

• Cognition Perception

• Pattern matching

• External cognition aid

Larkin & Simon ’87

Card, Mackinlay, Shneiderman ‘98


Great quote

“Contained within the data of any investigation is information

that can yield conclusions to questions not even originally

asked. That is, there can be surprises in the data…To regularly

miss surprises by failing to probe thoroughly with visualization

tools is terribly inefficient because the cost of intensive data

analysis is typically very small compared with the cost of data

collection.”

W. Cleveland

The Elements of Graphing Data


Part of our Culture

Seeing is

believingI see what

you’re saying

A picture is

worth a 1,000

words


The purpose of DataVis is ..

• Analysis – Understand your data better and act upon that

understanding

• Presentation – Communicate and inform others more effectively


When to Apply?

• Many other techniques for data analysis

– Statistics, DB, data mining, machine learning

• Visualization most useful in exploratory data analysis (EDA)

– Don’t know what you’re looking for

– Don’t have a priori questions

– Want to know what questions to ask

“A graphic display has many purposes but it achieves its highest value

when it forces us to see what we were not expecting.”

H. Wainer


EDA Examples

• Business

– Why has Hyundai made such great strides in the US market?

– How influential was their “Lose your job, we’ll buy the car back”

campaign?

– Have their cars improved in quality? If so, in what major ways?

– Is the Genesis as good of a car as the Lexus ES?

• Airlines

– What are the key factors causing flight delays in the US?

– Are delays worse in the summer or winter?

– Is the seasonal effect influenced by geographic location?

– How does competition at an airport affect flight delays?


More on EDA

“Information visualization is ideal for exploratory data

analysis. Our eyes are naturally drawn to trends,

patterns, and exceptions that would be difficult or

impossible to find using more traditional approaches,

such as tables or text, including pivot tables. When

exploring data, even the best statisticians often set their

calculations aside for a while and let their eyes take the

lead.”

S. Few

Now you see it


Tasks for DataVis?

• Search (OK)

– Finding a specific piece of information

• How many games did the Braves win in 1995?

• What novels did Ian Fleming author?

• Browsing (Better)

– Look over or inspect something in a more casual manner, seek

interesting information

• Learn about crystallography

• What has Jane been up to lately?


Key Benefits of Visualization

• Facilitating awareness and understanding

• Helping to raise new questions and supply answers

• Generating insights

• Telling a story and making a point


Key Challenge

• How to measure and prove?

– All those benefits are not easily quantifiable and measured

• Evaluation is perhaps primary open research challenge for

visualization*

* More on this in a later class


When to Apply?

• Visuals can frequently take the place of many words

• Visuals can summarize, aggregate, unite, explain, …


Data Visualization for BI is Big Business!

• 2003 Business Objects buys Crystal Decisions ($820M)• 2004 Agilent buys Silicon Genetics (GeneSpring, used in life sciences)• 2004 Hyperion buys QIQ Solutions, dashboard software) • 2005 General Dynamics buys MayaViz (logistics)• 2005 Business Objects acquires Infommersion (data visualization)• 2006 Actuate acquires Performancesoft (PBViews)• 2006 Microsoft buys Proclarity• 2007 Google buys Gapminder (demographics data Viz)• 2007 Cognos buys Celequest (business dashboards)• 2007 Business Objects buys Inxight• 2007 Oracle buys Hyperion $3.3B• 2007 SAP buys Business Objects ($6.8B)• 2007 IBM buys Cognos ($5B)• 2007 TIBCO buys Spotfire ($195M)• 2009 IBM buys SPSS• 2010 SAS acquires Memex (law enforcement, national security)• 2013 Tableau goes IPO ($254M)• 2015 Quid receives $53M in funding

(Some acquisitions involved more than DataVis products)


How do we decide on which type of

visual representation to use?


Tasks + Data

*People



Visualization Zoo (Heer et al.)

• Multivariate

• Geo-Based

• Time Series

• Hierarchies

• Networks

• Etc.

All visualizationsshare a common“DNA ”—a set ofmappings betweendata properties andvisual attributessuch as position,size, shape,and color—andcustomized speciesof visualizationmight always beconstructed byvarying theseencodings.


Multivariate Data: Scatterplot


Multivariate Data: Scatterplot Matrix


Multivariate Data: Parallel Coordinates


Time-Series Data: Index Chart


Time Series Data: Small Multiples


Time Series Data: Small Multiple (II)


Time-Series Data: Stacked Graph


Geo-Based Data: Maps


Hierarchies: Indented Tree


Hierarchies: Cartesian Node-Link


Hierarchies: TreeMap (Map of the Market)

Demohttp://www.marketwatch.com/tools/stockresearch/marketmap


Hierarchies: Sunburst


Networks: Force-Directed Layout


Networks: Arc Diagrams


Networks: Matrix Diagram


Types of Interactions*

• Details on Demand

• Focus + Context

• Dynamic Query

• Brushing & Linking

• Zoom & Pan

• Animation

• Change Representation (aka Re-encode)

* (not an exhaustive list but a good start :-) )


Overview & Detail – Mouse Selection

Clicking on an

item selects it

and attributes

of the data

point are shown

Selected item

Attributes


Overview & Detail – Pop-up Tooltips

Hovering mouse cursor brings up details of

item


Focus + Context (cont.)


Focus + Context


Dynamic Query


Brushing & Linking

• Highlighting connections in multiple views

– Simultaneously examine different attributes of a data

case

• In grid of scatter plots, select one “dot”, corresponding dots

highlighted in other scatter plots

– Simultaneously examine data case from different

views

• But need to keep straight where the data case is


Brushing & Linking


Brushing & Linking – Between Multiple Views

Sameitem


Brushing Example - DataMaps

Click on

histogram to

highlight states

UMD & VaTech


Zoom & Pan

• Plenty of Examples

– Google Maps, Google Earth


Change Representation

• Interactively change entire data presentation

– Looking for new perspective

– Limited real estate may force change


Change Representation – Example

Selecting different representation from options at bottom


Animation

• Time is actually time!

• Speed

• Timesteps


Recall the Gapminder Example

• What interaction

methods were used?

http://www.gapminder.org/world/

https://www.youtube.com/watch?v=jbkSRLYSojo


Interaction Methods in Gapminder

• Change Representation (Map, Chart)

• Linking/brushing/wiping

• Details-on-Demand (DoD)

• Animation

• Change Binding of Data to a Visual Representation


Homework 2 Due Next Class

• Find two visualizations of data from one of the suggested project domains. They can

be information presentations (static) or information visualizations (interactive). For

each visualization, do a one page write-up. Each page should have the visualization

(about half the page) and then:

1. What message(s) the visualization is intend to convey.

2. A critique of the visualization – list both pros and cons – ways in which the visualization does

a good job, ways in which it could be improved.

• I will ask some of you to show your visualization and share your pros and cons with

the class.

• Think of this assignment as a first step in identifying a potential project, which is why I

suggest that you be interested in the type of data being portrayed.

• Submit on T-Square AND please bring two (2) hard copies to submit in class.

Documents

OVERVIEW OF DATA VISUALIZATION · PDF fileOVERVIEW OF DATA VISUALIZATION ... Game Scores, Scientific Data, Biotech, ... • 2007 Google buys Gapminder (demographics data Viz)