visualization in science

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Visualization in science Nataša Tepić

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Visualization in science. Nataša Tepić. dictionary: Visualisation is a relatively new term which describes the process of representing information or ideas by diagrams or graphs . expansion: maps, plots, animations, video, movies,. What is visualization ?. - PowerPoint PPT Presentation

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Page 1: Visualization in science

Visualization in science

Nataša Tepić

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What is visualization?

dictionary: Visualisation is a relatively new term which describes the process of representing information or ideas by diagrams or graphs.

expansion: maps, plots, animations, video, movies, ...

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You must never tell a thing. You must illustrate it. We learn through the eye

and not the noggin.

Will Rogers (1879 - 1935)

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One picture is worth ten thousand words.

Frederick R. Barnard: Printer's Ink

10.03.1927.

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JMP

The greatest value of a picture is when it forces us to notice what we

never expected to see.

John Tukey

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till 16th century data visualization = maps

History

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the oldest known map (town map)6200 BCMuseum at Konya, Turkey

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the first world map

- Anaximander from Miletus in Asia Minor (610-546 BC), Turkey (his map has been lost, Herodotus describes it in books “The Histories” II & IV)

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in 15th century - Nikolaus Krebs (Nicholas of Cusa, Nicolaus Cusanus) developed graphs of distance vs. speed, presumably of the theoretical relation

during 16th century - development of geometric diagrams and various maps for data exploration– official start of data visualization

during 17th century - analytic geometry (René Descartes, Pierre de Fermat, ...) , theories of errors of measurement and estimation, the birth of probability theory, and the beginnings of demographic statistics and '' political arithmetic''

History

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What do we see?

form color depth motion

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Human visual system

human sight reacts more intensively on contrast than on intensity

colors which we *see* are not completely identical to the colors in the nature

purpose of human sight is constant object recognition regardless of angles, distance or lighting

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Seeing is a Complex Process

Our brain constructs image from: information from our eyes information stored in our brain

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perception

process of collecting information about world through our senses and their interpreting

perception depends on cultural heritage perception changes with experience

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Do you ever get something like this via e-mail?

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Optical illusions

Illusions trick us into perceiving something differently than it actually exists, so what we see does not correspond to physical reality. The word illusion comes from the Latin verb illudere meaning, "to mock."

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Why are optical illusions important for data visualization? inappropriate visual stimulation can

confuse our brain manipulative visual stimulation can cause

wrong interpretation

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Optical illusions

Problems with visual perception: area angles perspective

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10 ??

How much is the area of circle B?

answer: 17

A B

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angle problem

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perspective problem

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co-effects

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Müller-Lyer

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co-effects

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co-effects

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co-effects (pattern completion)

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Johann Poggendorff’s illusion

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co-effects

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co-effects

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co-effects

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co-effects

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Eye Test

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experiment

volunteer

Look at words from left to right. Say aloud the color of the text. Don’t read text.

DUBROVNIK

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ŽUTAŽUTA PLAVAPLAVA NARANČASTANARANČASTACRNACRNA CRVENACRVENA ZELENA ZELENA

LJUBIČASTALJUBIČASTA ŽUTAŽUTA CRVENACRVENA NARANČASTA NARANČASTA ZELENAZELENA

CRNACRNA PLAVAPLAVA CRVENACRVENA

LJUBIČASTA LJUBIČASTA ZELENAZELENA PLAVAPLAVA NARANČASTANARANČASTA

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YELLOWYELLOW BLUE BLUE ORANGEORANGEBLACKBLACK REDRED GREEN GREEN

PURPLE PURPLE YELLOWYELLOW REDRED ORANGE ORANGE GREENGREEN BLACKBLACK

BLUEBLUE RED RED PURPLE PURPLE GREENGREEN BLUEBLUE ORANGEORANGE

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This is left-side/right-side-brain conflict. Right-side-brain tries to say color but left-side-brain insists on reading the word.

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Color MeaningColors are non-verbal communication. They have symbolism and color meanings that go beyond ink.

red action, confidence, courage, vitalityblue unity, harmony, calmness, coolness, conservatismyellow joy, optimism, summer, cowardice, greedgreen spring, fertility, youth, environment, good luckorange energy, heat, enthusiasm, playfulnesspurple royalty, nobility, ceremony, magic, mysterypink femininity, love, beauty

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male

female

A B

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About 12 - 20 percent of white males and a tiny fraction of females are color blind.

Normal Color Vision Red-Green Color Blind  Left Middle Right Left Middle RightTop 25 29 45 25 Spots SpotsBottom 56 6 8 56 Spots Spots

Color BlindnessIshihara Test for Color Blindness

1

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small squares –same color or not?

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theory ....

Edward E. Tufte (professor emeritus of statistics, graphic design, and political economy)

"The Leonardo da Vinci of data."New York Times

he coined the term "chartjunk“.

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chartjunk This chart shows only five hard-to-read

numbers, 1, 2, 4, 8 and 16, but the digital file of the image is 11216 bytes (numbers) in size.

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theory....

Tufte uses the term data-ink ratio and argues strongly against the inclusion of any non-informative decoration in visual presentations of quantitative information and claims that ink should only be used to convey significant data and aid in its interpretation.

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Lurking behind chartjunk is contempt both for information and for the audience. Chartjunk

promoters imagine that numbers and details are boring, dull, and tedious, requiring ornament to enliven. Cosmetic decoration, which frequently

distorts the data, will never salvage an underlying lack of content.

If the numbers are boring, then you've got the wrong numbers.

Credibility vanishes in clouds of chartjunk; who would trust a chart that looks like a video game?

Edward Tufte, "Envisioning Information", 1990

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If a picture is not worth a 1000 words, to hell with it!

Ad Reinhardt

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the best statistical graphic ever drawn

Like good writing, good graphical displays of data communicate ideas with clarity, precision, and efficiency.

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The French engineer, Charles Minard (1781-1870), illustrated the disastrous result of Napoleon's failed Russian campaign of 1812. The graph shows the size of the army by the width of the band across the map of the campaign on its outward and return legs, with temperature on the retreat shown on the line graph at the bottom.

Many consider Minard's original the best statistical graphic ever drawn.

Why?

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the best statistical graphic ever drawn

He took a two dimensional space and managed to accurately depict five data variables: size of invading army, size of retreating army, geographic location, temperature, and of course, time. The multivariate data is presented in such a way as to provide an intriguing narrative as to the fate of Napoleon’s army.

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- new version (SAS/IML)

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cholera epidemic in London 1854.

Dr. John Snow (1855) observed that cholera occurred almost entirely among those who lived near (and drank from) the Broad Street water pump. He had the handle of the contaminated pump removed, ending the neighborhood epidemic which had taken more than 500 lives.

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Florence Nightingale - mother of modern nursing

After witnessing deplorable sanitary conditions in the Crimea, she wrote Notes on Matters Affecting the Health, Efficiency and Hospital Administration of the British Army (1858), an influential text including several graphs which she called "Coxcombs". This figure (reproduced with SAS/Graph) makes it abundantly clear that far more deaths were attributable to non-battle causes ("preventable causes") than to battle-related causes.

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Escaping the 2D plane: The Stereogram

By the end of the 19th century, as more statistical data became available, the limitations of 2 dimensions of the plane for the representation of data were becoming more apparent. Several systems for representing 3D data were developed between 1869-1880.

- author Luigi Perozzo- Annali di Statistica, 1880.- this figure shows the population of Sweden from 1750-1875 by age groups

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Chemical examples:

1. periodic table of chemical elements

Dimitri Mendeleev (1834-1907, Russian chemist)

He predicted the chemical and physical properties of unknown elements (e.g. Ga, Ge), and left spaces open in his periodic table for them.

order in periodic table by mass number

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Chemical examples:

2. wavelengths of the X-ray emissions of the elementsHenry Moseley (1887-1915, British chemist, Rutherford’s student)

In 1913 Moseley published the results of his measurements of the wavelengths of the X-ray spectral lines of a number of elements which showed that the ordering of the wavelengths of the X-ray emissions of the elements coincided with the ordering of the elements by atomic number. It became apparent that atomic weight was not the significant player in the periodic law as Mendeleev, Meyers and others had proposed, but rather, the properties of the elements varied periodically with atomic number.

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Chemical examples:

2. wavelengths of the X-ray emissions of the elementsHenry Moseley (1887-1915, British chemist, Rutherford’s student)

Moseley's graph represents an outstanding piece of numerical and graphical detective work. He noted that there were slight departures from linearity which he could not explain; nor could he explain the multiple lines at the top and bottom of the figure. The explanation came later with the discovery of the spin of the electron.

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the Worst Statistical Graphics ....

Like poor writing, bad graphical displays distort or obscure the data, make it harder to understand or compare, or otherwise thwart the communicative effect which the graph should convey.

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105832

105833

105834

105835

105836

105837

105838

105839

105840

105841

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

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105832

105834

105836

105838

105840

105842

105844

105846

105848

105850

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr Projected

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range 9 $

$105,832 $105,837 $105,838 $105,841

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Med. 1

Med. 3

010203040506070

80

90

A

B

C

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0

10

20

30

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50

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Med. 2 Med. 2 Med. 3 Med. 4

0102030405060708090100 A

B

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0

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86 87 88 89 90 91 92 93 94 95 96

Homicide Victimization Rates by Region

Northeast

Midwest

South

West

Bureau of Justice StatisticsBureau of Justice Statistics

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05

1015202530354045505560657075808590

Med. 1 Med. 2 Med. 3 Med. 4

A

B

C

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David W. Roubik, 1978. Robert M. Hazen

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384 plots and 1 map

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Literature SRCEhttp://www.srce.hr/stat-sas/tecajevi.html Gallery of Data Visualization - The Best and Worst of Statistical Graphicshttp://www.math.yorku.ca/SCS/Gallery/ Milestones in the History of Thematic Cartography, Statistical Graphics, and Data Visualization http://www.math.yorku.ca/SCS/Gallery/milestone/ Predavanja Ross Ihaka (Statistics 120 - Information Visualisation) http://www.stat.auckland.ac.nz/~ihaka/120/

http://www.math.yorku.ca/SCS/sugi/saslogo.htmlhttp://chemweb.calpoly.edu/ (Jennifer Retsek's Homepage)http://www.ritsumei.ac.jp/~akitaoka/index-e.htmlhttp://junkcharts.typepad.com/http://www-personal.engin.umich.edu/~jpboyd/sciviz_1_graphbadly.pdf http://CAUSEweb_orghttps://www.edwardtufte.com/http://www.csc.villanova.edu/~map/1040/Tufte1.ppt#1http://homepages.dcc.ufmg.br/~jussara/metq/aula10.ppt#89http://www.gautschy.ch/~alfred/SciIll/CraftingIll.htmlhttp://spacecraft.ssl.umd.edu/old_site/academics/483F02/04_eng_graphics_2002.pdf