Visualization in science

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Visualization in science

• Nataša Tepic

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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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History

• till 16th century data visualization maps

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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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History

• 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''

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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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How much is the area of circle B?
A B

• answer 17

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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 Poggendorffs 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. Dont read text.
• DUBROVNIK

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ŽUTA PLAVA NARANCASTA CRNA CRVENA
ZELENA LJUBICASTA ŽUTA CRVENA NARANCASTA ZELENA
CRNA PLAVA CRVENA LJUBICASTA ZELENA PLAVA
NARANCASTA
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YELLOW BLUE ORANGE BLACK RED GREEN PURPLE YELLOW
RED ORANGE GREEN BLACK BLUE RED PURPLE GREEN
BLUE ORANGE
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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 Meaning

• Colors are non-verbal communication. They have
  symbolism and color meanings that go beyond ink.
• red action, confidence, courage, vitality
• blue unity, harmony, calmness, coolness,
  conservatism
• yellow joy, optimism, summer, cowardice, greed
• green spring, fertility, youth, environment, good
  luck
• orange energy, heat, enthusiasm, playfulness
• purple royalty, nobility, ceremony, magic,
  mystery
• pink femininity, love, beauty

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male
female
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Color Blindness Ishihara Test for Color Blindness
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 Right Top 25
29 45 25 Spots
Spots Bottom 56 6 8
56 Spots Spots
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 Napoleons 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
  elements
• Henry Moseley (1887-1915, British chemist,
  Rutherfords 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
  elements
• Henry Moseley (1887-1915, British chemist,
  Rutherfords 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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Profits!!!!
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• range 9
• 105,832 105,837 105,838 105,841

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Bureau of Justice Statistics
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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

• SRCE
• http//www.srce.hr/stat-sas/tecajevi.html
• Gallery of Data Visualization - The Best and
  Worst of Statistical Graphics
• http//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.html
• http//chemweb.calpoly.edu/ (Jennifer Retsek's
  Homepage)
• http//www.ritsumei.ac.jp/akitaoka/index-e.html
• http//junkcharts.typepad.com/
• http//www-personal.engin.umich.edu/jpboyd/sciviz
  _1_graphbadly.pdf
• http//CAUSEweb_org
• https//www.edwardtufte.com/
• http//www.csc.villanova.edu/map/1040/Tufte1.ppt
  1
• http//homepages.dcc.ufmg.br/jussara/metq/aula10.
  ppt89
• http//www.gautschy.ch/alfred/SciIll/CraftingIll.
  html