LET S GO BACK TO THE VERY FIRST HISTORICAL KNOWN EXAMPLES OF INFORMATION VISUALIZATIONS

(1)

Prof Mikael Jern 2014

Introduction to InfoVis and Geovisual Analytics Prof Mikael Jern

NCVA, Linköping University

”Discovery consists of seeing what everybody has seen and thinking what nobody has thought”

Albert von Szent-Gyorgyi (1893-1986)

http://ncva.itn.liu.se/

LET’S GO BACK TO THE VERY FIRST HISTORICAL KNOWN EXAMPLES OF INFORMATION

VISUALIZATIONS

Visualization is one of the oldest

communication media

(2)

Interest of the National Debt

Minard 1858 vs. EU NUTS2 2012

Cattle sent to Paris Age groups 0-15 and 65+

(3)

Information Visualization - Cholera outbreak London 1854

infected water pump?

Dr. John Snow:

Investigation of deaths from cholera

London, September 1854

death locations

spatial cluster

Information Visualization - Cholera outbreak London 1854

(4)

A good data representation is the key to solving the problem Information Visualization - Today

Industry

number of employees Point colour =

“förändring Rörelse”

Shape Colour =

“Företagsklimat”

http://ncomva.se/apps/dual/app/en/#story=0

The most famous example of an early Information Visualization!!

Minard’s graph from 1861 of Napoleon's march through Russia 1812

(5)

Geographic location in (X,Y) Flow map - Direction of movements Size of Army in flow (weighted arrows)

Temperature TIME!

Poland

temperature 422,000

100,000

4,000

60,000

Berezina River

The most famous example of an early Information Visualization!!

Napoleon's march through Russia 1812 from Poland to Moscow

Geographic location in (X,Y)

Flow map - Direction of movements Temperature temperature

Minard’s Graphics produced today with InfoVis!!

Napoleon's march through Russia 1812 from Poland to Moscow

(6)

AnotherMinard’s Graphics

Flow Map Visualization of French wine exports around 1864

World Trading - Collaboration between OECD and NCVA Trading with focus Japan 2009

Flow Map Visualization in InfoVis Today

(7)

Using Bar Chart AND Flow Map gives more Information (Knowledge)

Flow Map Visualization in InfoVis Today

http://mitweb.itn.liu.se/GAV/flowmaptrade/

Migration to and from Norrköping Kommun

Flow Map Visualization in InfoVis Today

http://mitweb.itn.liu.se/GAV/flowmapsweden/#

(8)

Sankey ”energy” chart 2013

http://www.iea.org/Sankey/

From Computer Graphics to Information Visualization ...

and Geovisual Analytics ...to InfoGraphics

Computer Graphics (vector drawings) Raster Graphics (pixel oriented) 1970:

1978:

1980:

1985:

1995:

Data Visualization Scientific Visualization Information Visualization

(9)

Example of InfoGraphics – This is NOT InfoVis!

http://www.linkedin.com/news?viewArticle=&articleID=904262641&gid=80552&type=member&item=79869 741&articleURL=http%3A%2F%2Fwww%2Eguardian%2Eco%2Euk%2Fworld%2Finteractive%2F2011

%2Fmar%2F22%2Fmiddle-east-protest-interactive-

timeline&urlhash=uwzt&goback=%2Egde_80552_member_79869741

Example of InfoGraphics – This is NOT InfoVis!

(10)

Example of Information Visualization (Visual Analytics)

Volume Rendering

Isosurfaces

SciVis

Physical data

Glyphs

Scatter Matrix Table Lens

Parallel Coordinates

InfoVis

Abstract data

(11)

SciVis = Physical Data (human body, earth, molecules, physical space

InfoVis = Abstract Data (statistical, financial, business information, text documents

(12)

3D InfoVis vs. 2D InfoVis

from one 3D view to multiple linked views

3D InfoVis vs. 2D InfoVis

from one 3D view to multiple linked views

(13)

Prof Mikael Jern 2014 TIME

Country

Immigrants

Multiple Time Shaded “3D Curves”

(14)

Energy

Consumption

3D Scatter Plots were popular in the late 80s

Scatter Plot – simple

(15)

Why Information Visualization?

 Massive statistical and business information … and is growing

 Which information is important?

 Gain insight and knowledge

“a picture is worth a thousand words”

•Domestic sales larger than International and growing;

•Flat international sales and decreases sharply in August;

•Cyclical sales pattern in Domestic sales repeated on a quarterly basis reaching a peak in last month of quarter;

What these numbers could not communicate when presented as text in a table, which our brains interpret through the use of verbal processing, becomes visible and understandable when communicated visually. This is the power of “statistics data visualization."

Cyclical sales

(16)

Search + Examine + Explain =

SEE

 to search for meaningful patterns … Discovery

 then examine them and once they’re found…. Gain Understanding

 to communicate meaningful findings to others ….. Explain

“aha, I see!”

Instead of One 3D View used in SciVis InfoVis apply multiple linked Views - “Dashboards”

(17)

………InfoVis now also on mobile devices using dashboards

(requires HTML5/JS)

http://mitweb.itn.liu.se/GAV/dashboard/

………InfoVis now also on mobile devices using dashboards

(requires HTML5/JS)

http://epp.eurostat.ec.europa.eu/cache/RSI/

(18)

World Statistical Data

1. ASK A SPECIFIC QUESTION

Where do we have high Fertility Rate?

2. GATHER YOUR INFORMATION Get data from World Databank….

3. VISUALLY REPRESENT THE MENTAL MODEL Select most suitable Visualization Method

Information Visualization in 4 easy steps

(19)

4

.

RESULT IN A SCATTER PLOT

Size: Population

Time: 1960, 1961, 1962,..

Colour: Fertility Rate

Information Visualization in 4 easy steps

(X,Y): Age 0-14 vs. Fertility Rate

Age 0-14

Fertility

WORLD STATISTICAL DATA

(20)

Information Visualization Definition: Two Mantras

 Overview, zoom & filter, details-on-demand (Shneiderman - 1996)

 Analyze first, show the important, zoom, filter and analyze further and details-on-demand (Keim - 2006)

1. OVERVIEW - SCAN THE BIG PICTURE

2. ZOOM & FILTER - SEARCH SPECIFICS

3. DETAILS ON DEMAND - LINK TO FURTHER DETAILS

(21)

(22)

http://mitweb.itn.liu.se/GAV/dashboard/#story=data/Ageing Population in the World.xml&layout=[map,(scatterplot,barchart)]

Hans Rosling’s world

(23)

Scatter Plot – how many (attributes)?

World Countries

Population ages 0-14 vs. Life expectancy at birth;

Colour: Population ages 65+ ; Circle Size: Total population; Trails: Time;

Life expectancy

age 0-14

age 65+

Size: Population Time: 1960, 1961,..

Colour: age group 65+

“Scatter Matrix”

InfoVis method

(24)

fertility

fertility rate

“An Interactive visualization is worth a thousand pictures”

Spatial – Time - Variable

http://mitweb.itn.liu.se/GAV/dashboard/#story=data/Ageing Population in the World.xml&layout=[map,scatterplot]

(25)

 Information visualization is the use of interactive, visual representations of abstract data (but as you have seen often with a spatial dimension) and to use perception to amplify cognition.

 It is the process of forming a mental model of data, thereby supporting insight into that data.

Information Visualization Definition

…….forming a mental model of data, thereby supporting insight into that data….

1960 1985

2009

(26)

forming a mental model of data, thereby supporting insight into that data – Sweden municipalities age group 0-14 (1960-2010)

use COLOUR

time

1960 1985 2010

…….forming a mental model of data, thereby supporting insight into that data…. “use lines for time movements”

(27)

Information visualization is the use of interactive, visual representations ... and to use perception…

Importance of Human User Interface

Find the red square?

Information Visualization helps users …

Find patterns, outliers and trends

(28)

Find the blue circle?

"The holy grail of

information visualization is to make the insights stand out from otherwise chaotic and noisy data."

Net Migration

(29)

Net Migration in divided colour vs. grey scale

Net Migration Net Migration

 Information visualization is the use of interactive, visual representations of abstract data (but as you have seen often with a spatial dimension) and to use perception to amplify cognition.

 It is the process of forming a mental model of data, thereby supporting insight into that data.

 Information visualization helps users:

 Find patterns, outliers and trends

 Explore data to build intuition, understanding and knowledge

 Communicate understandings and knowledge to others

(30)

The Perfect Car Data Set applied to InfoVis

“Visualization of multivariate abstract data”

Abstract Data in Information Visualization

Multivariate - Quantitative data and Categorical data

Data Items

(31)

Prof Mikael Jern 2014 Miles Per Gallon

Acceleration 0-60

Size: Weight Color: Horsepower

Scatter Plot – with high correlation

http://mitweb.itn.liu.se/GAV/mdim/#story=2

Weight

Acceleration 0-60

Size: Price Colour: Miles per gallon

Scatter Plot – with high correlation

(32)

Scatter Plot – how many (attributes)?

1D: Weight vs. 2D: Acceleration 0-100 Circle Size: Price;

Colour: Miles Per Gallon;

(33)

Multivariate - Quantitative data and Categorical data

Data Items

Categorical Quantitative Categorical (Ordinal) Quantitative

Country

Acceleration 0-60

(34)

The Perfect Car Data Set applied to InfoVis

“Visualization of multivariate abstract data”

http://mitweb.itn.liu.se/GAV/mdim/#story=2

 Multidimensional Visualization of Multivariate Data

(35)

Country

Indicators Time

Italy; Fertility; 2010

Italy; [indicators]; [time]

2010 1960 Fertility GDP Population

Fertility;[data item]; [time]

2010 1960

Spatio-Temporal and Multivariate Visualization using a Data Cube

(36)

Introducing ”Treemap” – using hierarchical data

Rectangle Size = Population Colour = Fertility rate

Hierarchy = Continent-Country

Göteborg Stad tidig med Publicera Öppna Data

• Statistik visas på ett sätt som engagerar många i stadens utveckling;

• Trender över tid ökar förståelsen;

• Statiska rapporter ersätts med interaktiva webb sidor

(37)

http://ncva.itn.liu.se/great-statistics-visualization/eurostat-statistics-visualization?l=en

(38)

SCB Statistik Atlas

• Forskningssamarbete sedan 2004;

• Statistikatlas 2010;

• Storytelling;

• Visuella Nyhets- bulletiner från 2012;

• Många efterföljare;

http://www.scb.se/kartor/Statistikatlas/index.html

Nya Data

(39)

• Ett urval av SCB’s egna indikatorer

• Över tid 1968-2011

• Integrerad Storytelling

http://www.scb.se/kartor/Statistikatlas/index.htm l

Västra Götalandsregionen

http://www.vgregion.se/sv/Vastra-Gotalandsregionen/startsida/Regionutveckling/Publikationer-statistik/Interaktiv-statistik1/

(40)

Västra Götaland eXplorer Arbetslöshet

http://www.vgregion.se/sv/Vastra-Gotalandsregionen/startsida/Regionutveckling/Publikationer-statistik/Fakta-och-statistik/Interaktiv-statistik/

Arbetslöshet Totalt

Arbetslöshet Kvinnor

Arbetslöshet Män

Arbetslöshet Totalt

Story Arbetslöshet 1992-2011

(41)

Graphical Excellence requires Good Perception

Graphics excellence

 ….is the well-designed presentation of

interesting data, a matter of substance, statistics, and design

 ……consists of complex ideas communicated with: clarity, precision, and efficiency

 ……is that what gives the viewer: the greatest number of ideas, in the shortest time, with the least ink, in the smallest space

 ……is nearly always multivariate

 …..requires telling the truth about the data

Tufte

http://nvac.pnl.gov/

Introducing GeoVisual Analytics an extension to InfoVis ....in 2005

(42)

Geographic Visualization

Geovisual Analytics

Communicate Storytelling

Publish

Data Multiple Sources

Dynamic Filter Information Visualization

Cognitive Perceptual

Science

Time Animation Visualization

http://ncva.itn.liu.se/?l=en

 Interactive Visualization is nice to play with but…

 Difficult to collect and report the results knowledge gained in an Explorative Analytics session ;

 Use technologies that enable analysts to communicate what they know through use of appropriate visual

metaphor and principles of reasoning and graphics Challenge and Motivation for Geovisual Analytics ..

(43)

Big Data - http://ncva.itn.liu.se/big-data-geovisual-analytics?l=en 10,000 geographical regions

 The science of analytical reasoning facilitated by interactive visual interfaces – e.g. dynamic linked multiple views;

 Exploring and analyzing spatial-temporal and multivariate data;

 Discern trends or patterns - derive insight and draw conclusions;

 Communicate discovery and knowledge effectively for action

with 100% Web compliant;

 Moving Research into Practice;

Introducing GeoVisual Analytics an extension to InfoVis ....

(44)

 Gather Data and Information – Tasks?

 Visual representation

Choose layout and visual forms that aid analysis

 Develop insight – Interactive session Through exploration – What is important?- Filtering – Tell the Story

 Produce results (knowledge) Storytelling, Presentation, Collaboration and Publishing

Visual Analytics Reasoning Process – Sense Making Loop

Sense-making is an effort to understanding, to recognize particular

characteristics of the data and understand what they mean .. “it make sense”

Motala River – Concentration of Nitrogen

“many cows along the river”

(45)

Ericsson Research

Visualization of Self-Organizing Networks Operated by

Automatic Neighbour Relations

• Growth of cellular radio networks

• Need of automatic algorithms

• Automatic Neighbour Relations (ANR) developed by Ericsson

• ANR must be proven to gain network operators’ trust

Should we trust automatic algorithms?

(Visualization of Self-Organizing Network)

VoSON

(46)

CGI 657

PCI 481 CGI 671

PCI 11

If the PCI is unknown, the CGI is requested.

The ANR Procedure

Ericsson Research – VINNOVA

Search for mobile cell anomalies

(47)

Ericsson Research – VINNOVA

Search for mobile cell anomalies

Visual Analytics at Ericsson - Mobile accessibility

http://mitweb.itn.liu.se/GAV/anross.wmv http://ncva.itn.liu.se/anross-mobile?l=en

(48)

Dashboard multiple views application

http://mitweb.itn.liu.se/GAV/dashboard/

…….. now also on mobile devices using dashboard

(49)

http://ncva.itn.liu.se