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Visual Alpha-Beta-Gamma: Rudiments of Visual Design for Data Explorers

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  • Science Practice

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This article discusses terminology useful toward the creation and discussion of visualizations. It continues and expands on a hands-on tutorial delivered by the author at the VisWeek2012 conference in October 2012 in Seattle, WA. Today, many fields of scientific activity have become increasingly reliant on visuals as means of dissemination, exploration, and analysis of information. Consequently, either directly or through computer coding, many scientists become de facto image-makers. This article aims at providing basic introduction to visual language to those data explorers, those who depend in their fields of activity for producing (creating or generating) images. Five elements (the vocabulary) of visual language and four visual structures (the grammar) are defined, explained, and discussed. These aspects of the vocabulary and grammar of visual language are then elucidated through pictorial examples, thus presenting basic interdisciplinary knowledge of the subject from a design practitioner’s perspective. The article concludes with a bibliography with recommendations of valuable readings for further investigation of the topic. It is hoped that the paper provides useful background to be informedly used in readers’ own imagemaking activities.
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KEYWORDS Data explorers, design commandments,
design rudiments, image-making, scientists, tutorial,
visual language, visual structures, VisWeek
ABSTRACT is article discusses terminology useful
toward the creation and discussion of visualizations.
It continues and expands on a hands-on tutorial delivered
by the author at the VisWeek conference in October
 in Seattle, WA.
Today, many elds of scientic activity have become
increasingly reliant on visuals as means of dissemination,
exploration, and analysis of information. Consequently,
either directly or through computer coding, many scientists
become de facto image-makers. is article aims at provid-
ing basic introduction to visual language to those data
explorers, those who depend in their elds of activity for
producing (creating or generating) images. Five elements
(the vocabulary) of visual language and four visual structures
(the grammar) are dened, explained, and discussed.
ese aspects of the vocabulary and grammar of visual
language are then elucidated through pictorial examples,
thus presenting basic interdisciplinary knowledge of the
subject from a design practitioner’s perspective.
e article concludes with a bibliography with recom-
mendations of valuable readings for further investigation
of the topic. It is hoped that the paper provides useful
background to be informedly used in readers’ own image-
making
activities.
inTRODuCTiOn
Image-making was the general theme of a hands-on
tutorial titled “Good Practice of Visual Communication
Design in Scientic and Data Visualization” conducted
by the author at the VisWeek conference in Seattle,
Washington, on October th . Explored from a range
of perspectives, the tutorial provided its participants with
an overview of selected visual elements and structures
available to an image-maker. It showcased successful
as well as failed visualization examples, last but not least,
the tutorial facilitated a live sketching exercise in which
all tutorial participants were able to freely experiment with
dierent ideas and strategies toward representing data.
In this article we present and expand on the content
Visual Alpha-Beta-Gamma:
Rudiments of Visual Design
for Data Explorers
mAREK KulTYS, mA
of the rst part of the VisWeek tutorial: a lecture
about visual language—the language through which the
image-maker speaks to their audience. We will discuss
visual language under two aspects. e rst deals with
visual vocabulary and outlines ve distinct elements
present in graphic visualizations: point, line, area, color
and typography. e second part discusses four kinds
of relationships between visual elements used in visualiza-
tions—the visual grammar of an image: grid, negative
space, synthesized seeing and time. Each feature of visual
language examined here is briey discussed and accompa-
nied by instructive illustrations.
e article is primarily addressed to those data explorers
(scientists, analysts, researchers, visualization experts)
who strive to represent complex content visually, but
may be lacking in the basic knowledge and understanding
of visual language skills. Aiming at briey and broadly
introducing the reader to the most basic topics of visual
design as seen from the practitioner’s point of view, as well
as conned to the format of a journal article, the author
took the liberty of arbitrarily selecting examples for
discussion in this paper. Although a well-informed
and visualization savvy reader might nd this selection
incomplete, inconsistent, or even disputable (there is
a number of much more systematic and comprehensive
studies of visual language available), it is hoped that (for
a start) a curious data explorer untrained in image-making
will nd this article eye-opening, instructive and—with
the help of the extensive bibliography concluding the
article—a good vantage point for further independent
study of the topic.
viSuAl vOCABulARY: pOinT
e smallest unit of visual form is a point. Graphically
a point is a dot—a tiny material surface characterized by
color, shape, and other possible attributes. Additionally,
we will dene a dot as having a position on a plane.
Scientically it is an abstract entity, a variable, a set of
coordinates with a precise location in mathematical space.
Both the graphical and mathematical perspective
on the point is true for scatterplot diagrams, where any
point is a carrier of numeric values located on chart axes.
us a point can indicate a very precise moment in time,
pinpoint a specic location in space or any other measure-
ment on a scale.
It is a valuable observation to understand that a point
is primarily a natural phenomenon. e sky at night
contains hundreds of visible points, the macrocosm
of shiny stars, each indicating a specic location in the
universe measured by the age of light traveling towards us.
Observing the stars and trying to work out how the universe
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rudiments of visual design for data explorers
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area from another, therefore, is the rst step when creating
divisions on blank surface of paper or screen. A line can
indicate length and direction—both these abilities are
important for visualizing information and cartography.
A meandering line can carry valuable information about
the shape of a continent, resembling someones face prole,
or depicting a specic bone taken from human skeleton.
Hand-drawn lines always carry some artistic qualities:
bringing dynamism, gesture, or emotion to an image.
Expressing these notions with a singe line is possible owing
to the fact that a line is a visual object—and it has thickness.
Draw a vector line in a computer program and increase it’s
thickness until it is dicult to decide, whether it is seen is
still a line or maybe already a rectangle… Tricky, is it not?
ere is a ne line between these two cases and ones
judgement would usually depend on one’s context.
All these characteristics of a line provide potential
for carrying information. Stock exchange performance can
be represented with a single line shooting up, then diving
down, up and down, up, down… A curved line drawn
on the world map calculates an orbit of a satellite passing
above continents and seas. A network of intersecting
colored lines can represent a whole rail transportation
system in busy metropolitan areas within London, Moscow,
Tokyo, or Warsaw. In all these cases lines are saturated
with information of various kind: time, value, location,
direction, train service, etc. In contemporary world we
continuously rely on complex information but not oen
pay much attention to the fact that it is oen read from
such a rudimentary yet ecient form—a simple line.
viSuAl vOCABulARY: AREA
An area can be marked out between at least three inter-
secting lines or created by a line in motion. A razor blade
reveals an area of naked skin from beneath a beard and
shaving foam; several strokes usually suce to shave one’s
whole face. A very specic instance of dividing space with
a line is when we draw a loop or any other closed polygon.
It creates a border, an inside–outside relationship between
two areas which we call shapes. Because we also like to
recognize familiar shapes in abstract forms (who has never
spotted a cumulus white elephant or a cirrus rabbit in the
skies?), we tend to ignore the objective, formal appearance
of outlined areas and ll it with our personal associations.
And this poses problems for image-makers.
From the practitioner’s point of view, the under-dened
inside–outside relationship oen leads to ambiguity. A circle
( ) can represent virtually anything. Is it a ball?
Is it a hole in a wall? Or maybe a ring? Each interpretation
is true until a watchful image-maker provides us with
works has always been one of humankind’s most ancient
pursuits. In the opposite corner of the scale of things there
is an atom, a droplet, a primitive living cell, a microorgan-
ism… We do not necessarily know how an atom looks
like, but we know it as a localized mass and an epicenter
of forces—both anchored in a specic point in space.
Pointillists observed the world around them as
a collection of interrelated points. ey were a group
of artists who in late th Century developed a new
painting technique in which small, discrete spots of pure
color were systematically applied on canvas to collectively
form a meaningful picture. Pointillism relies on the ability
of human seeing to blend distributed colors spots into
a combined tone. Most notable pointillist painters were
Georges Seurat, Paul Signac and Camille Pissarro.
Today, many imaging technologies rely on the same
principles, which underlay pointillism. In  printing
an image is developed by applying patterns of discrete
dots in a meaningful combination. In fact, the only mark
that modern digital printers can produce is a point of ink.
In a very similar fashion  displays generate complex
images by combining colored points (pixels) in a meaning-
ful pattern. Contemporary image-maker should to be
aware of the fact that this is how every digital visualization
is produced today, be it on screen or in print.
viSuAl vOCABulARY: linE
“Breadth-less length” is how line is described in Euclidean
geometry—a continuous extent of length that has no
breadth. Mathematically it is an abstract concept, extending
innitely without beginning or end. Pick any two points
in space and you will be able to stretch a line through
them. A line segment on the other hand starts in one point
and ends in another, and marks the shortest way between
those two. A line can also join separate point into meaning-
ful
groups. ree lines connecting three points make up
a triangle; a hendecagon comprises eleven even lines.
Little wonder that rst astronomers felt compelled to draw
imaginary lines in night skies—ancient star constellations
help us identify and locate heavenly bodies until today.
From a designer’s perspective a line is a function of
time. It is a single continuous form created by a pencil tip
scratching on the surface of paper. A line is hence one
of the most primitive graphic entities—an elementary
form of expression in drawing, sketching, diagramming,
mapping—be it manual or digital. Whether straight,
crooked, spiraling, or open or closed, it always becomes
a notation of point’s travel in space over a period of time.
Being such an important element of visual language,
a line has hence a variety of roles to play. It separates one
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rudiments of visual design for data explorers
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formal hints. Additional lines of internal structure dening
the area inside the circle transform it into a basketball
( ). If a pattern appears on circle’s outside, we
learn that the ambiguous area is in fact a hole
( ).
Drawing another circle inside the rst one prompts us to
see them related; our mind lls the gap for us, and a white
area emerges between the circles ( ).
Wary of many ambiguities of visual vocabulary, an
informed image-maker will always saturate an image with
just enough necessary context information to allow for
its intended interpretation. Let us consider an example
borrowed from the author’s own design practice—illustrating
cell receptors anchored in cell’s membrane. Here we can
see a receptor embedded in a lipid bilayer ( ),
which divides the frame into two distinct areas: above the
membrane (where the main part of the receptor resides)
and below the membrane (with ends of receptor’s trans-
membrane domains). For a knowledgeable reader this
image alone may suce to identify the inside of the cell
(cytoplasm) and its outside (environment). is is possible
owing to the fact, that our educated reader can be familiar
with microbiology visualizations and capitalizing on this
experience, she/he would understand the image in spite
of ambiguities. However, for those readers not educated
in life sciences, the A image might not be enough, because
they need additional cues to help them see the continuity
and physicality of cellular structure. When discussing the
cell alone, we benet from having cell’s inside area lled
with a pattern or shade ( ), which shows that
the membrane encloses internal material of some kind.
Giving denition to this inner area is important, because
it allows us not only to juxtapose it with the empty
background, but also provides extra interesting data on
cytoplasm density. Same principle applies when the focus
is on cell’s environment ( ). Here again, while
emphasizing the fact that the cell is not levitating in white
emptiness but suspended in a solution, we also provide
approximate information on this solution’s qualities—
namely its concentration represented by the scattering of
dots. Finally, we can combine the  and  images together,
to form one comprehensive image presenting a whole
range of information at once ( ). Our image
thus dense with extra information will always outperform
those with less to tell.
An informed image-maker strives to observe her/his
own work from the perspective of a prospective viewer.
Forgetting now and again our specialist professional
background is always good tactics to reassure us, that
the information and visual cues we provide in our images
is sucient for non-expert audiences.
viSuAl vOCABulARY: COlOR
Color is a visual sensation created by objects reecting
specic wavelengths of light—the visible spectrum
of electromagnetic radiation. A lemon appears yellow
because it reects rays of light only in those wavelengths,
which are in the yellow region of the spectrum, and
absorbs all other wavelengths. However, if we observe
the same lemon through a blue-stained glass, it will appear
green instead of yellow. is is because the blue glass
changes the frequency of yellow light reected from
the lemon and shis it to the green part of the spectrum.
Obviously, such visual intervention does not change
lemon’s properties—it only changes the sensation of
the light captured by our eyes’ retinas.
Color is a most subtle and tricky tool in image-maker’s
repertoire. Many artistic and scientic careers have been
dedicated to studying color and color perception (color
theory), and there is still a lot to be learned. Here, we will
 : Ambiguous circle. Image-maker helps the viewer
interpret the shape by providing visual cues (redesigned and
redrawn aer Adrian Frutiger)..
 : Image-maker increases information density
by adding patterns to eliminate inside-outside ambiguity.
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focus on the use of color in design practice.
Colors we use in print or on screen are composites—
selected tones are produced by carefully combining basic
colors of paints or lights ( ). Most commonly we
use four primary tones of ink in print (Cyan + Magenta
+ Yellow + blacK = CMYK color model) and three elemen-
tary
tones of light for display (Red + Green + Blue = RGB
color model). e  model produces additive colors,
because by introducing combinations of red, green and
blue lights to darkness we can attain the whole gamut of
tones.  culminates in pure white light produced from
all three lights shining with full power. e  model
oers subtractive colors, as four process inks take away
brightness from white paper. is process culminates in
rich black—four blots of primary colors applied in one spot.
(Technically, black is necessary because reective light is
not as “pure” as incident light, otherwise  would renders
black in the same manner as  renders white.)
In image-making and visualizing color can perform
specialized functions. It can act as a noun and ) label
specic objects or structures—in London Underground
network diagrams the Central line is always labelled red
and the District line green. Also trac lights operate a
universal language of color: go when green, stop when red.
Color can be employed as scale or quantity to ) measure
a given variable—we use of that function in elevation maps
where ocean depths are measured with shades progressing
from dark to light blue. Nature uses color scales less
directly but still very eectively to indicate when an apple
or a tomato is nally ripe. irdly, color is oen used
in image-making to ) represent reality and imitate
things—maps showing green deserts and green rain
forests will be undoubtedly misunderstood, because the
use of colors will not adhere to our everyday experience.
In more complex images color can also contribute to )
building space and depth—ordering of plans in an image
can be suggested by progressive desaturation of distant
objects, which is known as aerial or atmospheric perspective
(see “Mona Lisa” by Leonardo da Vinci). Finally, color can
also ) decorate and enliven provided that it is done with
a purpose—Torre Agbar skyscraper in Barcelona is a good
example of such decoration with glass elevation eectively
illuminated at night and vividly opalescent in daylight.
A knowledgeable image-maker should learn about
the nature of color, color models and color functions,
additionally, they should remember three rules when
deciding on the use of color. Firstly, ) no more than six
to eight distinct colors should be used to label objects that
appear in close proximity to one another. e human eye
can eortlessly distinguish no more than approximately
eight hues. We all have struggled with diagrams or charts
where colors are too similar to dierentiate between the
categories they purportedly label. If twenty variables are
to be colored in one chart, a skilled image-maker should
consider ways of restructuring the data (sub-categorization,
using several charts, etc.) Secondly, ) colors used to
measure should be used intelligently and with respect
for the whole scale they represent. It is common practice
to use full-spectrum rainbow color scales to quantify data
in maps and diagrams, even though the full spectrum
scale does not oer a visually uniform distribution of hues
( ). Extreme ends of the rainbow scale tend
to exaggerate value uctuations and visually dominate
an image, whereas the middle section of the spectrum
lacks sucient denition and contrast to give true justice
to the whole range of values in that part of the rainbow
 : Two color
models.  = Red
+ Green + Blue light.
 = Cyan +
Magenta + Yellow +
black ink.
visual alpha beta gamma:
rudiments of visual design for data explorers
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scale. To avoid color exaggeration and misrepresentation
one should employ those color scales, which give equal
delity and prominence to both central and extreme scale
sectors ( ). irdly, ) when choosing colors one
should always be cognizant of those who possess color
deciencies. ere are many types of color deciency,
most of which can be simulated with popular online tools
(e.g.: www.colorschemedesigner.com); these sources
provide advice on inclusive color selections. An informed
image-maker strives to design for the widest possible
audience —in the end it is in everyone’s best interest.
Color scale presented in   is an example of this
highly appraisable design policy of inclusivity.
viSuAl vOCABulARY: TYpOgRAphY
Letters and other typographic symbols are graphic shapes
that carry variable levels of meaning. Although a literate
person sees the same letterforms as an analphabetic
person, it is the literate individual who can collectively
read them, thus accessing abstract meaning encoded
within the text. Typography, and writing in general, are
visual representations of language. We rely on typefaces
to achieve this within typographical constructs. Today,
we use fonts—electronic data les containing characters,
glyphs, and other symbols, whereas in traditional letter-
press printing there were metal blocks with raised, mirror
image characters that permitted their inking toward the
typesetting process.
Typographic means of expressions is essential for
contemporary image-making. Typographical knowledge
permits an image-maker to skillfully edit stand-alone text,
label a map, or create a legend to explain a visualization.
Here we will discuss the anatomy of a typeface, as well
as basic functions performed by typography in visual
communication.
e Latin alphabet is organized with the words wrapped
downwards to form columns of parallel lines reading from
le to right (i.e., in the Westernized manner). Characters
are set on a horizontal axis called the baseline ( ).
To identify this baseline locate the bottom horizontal edge
of letter “Z”—it abuts the baseline. e x-height is type’s
second elementary dimension. It is the space between the
baseline and the upper edges of the lower case letter “x”
(known as mean line). Within the x-height resides the body
of the character. Lower case letters a, c, e, m, n, o, r, s, u, v,
w, x, and z can be tted within the x-height space almost
entirely. ose portions of letters b, d, f, h, i, k, l, and t that
remain above the mean line are called ascenders. Conse-
quently, those portions of letters g, j, p, q, and y residing
below the baseline are called descenders.
e specic letterform design of each font makes
it more suitable for one user’s purpose, or task, and less
suitable for another. Because two fonts of the same numeric
size measured in points (e.g.: pt) can have strikingly
dierent x-heights, their legibility eectively depends on
the x-height value. e larger it is, the bigger the characters
 :
Color scales.
Image-maker’s duty is
to faithfully map colors
onto a data set.
Perceptual palette
utilizes color and its
properties to represents
terrain elevation much
better than palette .
Image by Matteo
Niccoli, Mycarta, 
(Modied.))
visual alpha beta gamma:
rudiments of visual design for data explorers
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of a particular font appear to the reader. For instance, text
set in Gotham Book (size pt) will appear bigger font
than the same text set in Times New Roman Regular
(pt), because Gotham’s x-height is approximately 
greater than x-height in Times. is seems not much,
but when text is displayed dynamically and requires high
legibility this  makes important dierence. Furthermore,
digital displays usually promote larger x-height fonts,
because it allows for more exibility in typesetting and
improves overall experience and ease of reading.
In editorial and image-making, typography plays more
of a role than just visualizing language. It provides the means
of structuring and organizing a text message through basic
typographic variables, such as: font size, font weight (light–
regular–bold),
line spacing, positioning, alignment and
justication (justify right, justify le, align to centre), etc.
Using typography an informed image-maker
will be able
to introduce hierarchy to text, which can be attained by
dierentiating font size or form. Most oen two font forms
(serif and sans-serif) and three font sizes (e.g. pt, pt and

pt) is enough to structure a complex texts in a transparent
and attractive fashion. Other means of text manipulation
such as character color (not necessarily venomous reds—
consider toned greys) and indentation help identify and
group information types, as well as emphasize its key parts.
e old motto “less is more” summarizes the best part of
all typographic works ever designed.
viSuAl gRAmmAR
Once an image-maker learns and understands the visual
vocabulary, it is time to become familiar with more global
relationships and interactions that happen between groups
of elements of visual language. Just as for written or verbal
language through which employ syntax and grammar to
assign intended meaning to a collection of words, so is
the case for visual language whereby we observe structures
and rules that put our visual vocabulary in context.
We will discuss four arbitrarily selected structures:
design grid, negative space, synthesized seeing, and time.
is selection is informed by observations made at scientic
conferences, where the author had an opportunity to
identify most common mistakes and weaknesses in the
ways scientists visualize and communicate their work.
It is hoped that becoming familiar with the basics of visual
grammar will help all curious data explorers improve their
image-making skills.
viSuAl gRAmmAR: gRiD
Designers use grids to impose structure on content; to
provide content with hierarchy and architecture, and to
guide the reader step-by-step through the message. Grid
is an invisible rhythm that allows us to sense regularity in
what is seen, to help us anticipate what is bound to happen
on the following pages… and ultimately to be surprised by
what we eventually nd there. Being one of visual grammar
structures, a grid organizes visual vocabulary just as syntax
organizes words in a sentence, similarly to how rhyming
schemes generate patterns within poetry.
 : Typography
is organized on a base-
line. -height compari-
son reveals dierences
in typeface volume
between two distinct
fonts of same size.
visual alpha beta gamma:
rudiments of visual design for data explorers
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Contemporary grid stems enable our innate urge to
organize things. e ancient Greeks used the golden ratio
( : .…) to design impressive temples such as the
Parthenon. If the ratio of the sum of two quantities +
to the larger  is equal to the ratio of the larger  to the
smaller , then those three quantities are in the golden
ratio. Artists, mathematicians and philosophers explored
this ratio for centuries. In the th Century a more
pragmatic approach emerged and Swiss/French architect
Le Corbusier proposed the Modular—his own system
of measurement and scale based on the proportions of
human body.
Today, none of the rules of constructing the grid is
regarded as universal, however there is a good practitioners’
consensus to employ any favored grid and use it with
persistence and consistency. An informed image-maker
should therefore always decide prior to starting any design
work what grid to use, how many identical modules should
a column and a row have, what should be the size of a single
module, how many lines of text to t inside one module,
how much space should be dedicated to margins
( ).
Once these decisions are made, it is crucial to adhere to
them thoroughly, with no concession for exceptions or
overriding initial guidelines. Consistency in using the
selected grid results in quality work, thoughtful planning
and order. Any deviation produces disorder and confusion.
Readers, who wish to further explore the topic of grids,
grid templates and instructions on how to use them in
practice, will be delighted to visit e Grid System website
(www.thegridsystem.org). ere one will nd a range
of useful resources, articles and tools, as well as an eye-
opening simulation—make sure to press the “Show Grid”
button in upper right corner of the web page.
viSuAl gRAmmAR: nEgATivE SpACE
Negative space might seem a little bit like magic: it is
invisible, it contains nothing, just void, but nevertheless
it is still present, prompts associations, and lls our minds
with visual stimuli and ideas. Negative space resides in close
proximity to the subject of representation and inuences
it, oen adding or shiing image meaning. In th Century
avant-garde visual art negative space played major role
being extensively studies by László Moholy-Nagy in his
collage works, emerging in many paintings by Juan Miró,
providing spatial context in Piet Mondrian’s and eo van
Doesburg’s compositions.
As an integral part of every visual composition,
negative space, should never be considered as leovers,
mere by-product or waste. Quite the contrary—it should
be harnessed and used in one’s favor to reinforce the
message an informed image-maker strives to communicate.
If we consider drawing not as a process of adding color,
but as a process of removing the white from paper, the
concept of negative space becomes more dened and
graspable. Because negative space can be created only
indirectly as a quality of space around or between other
objects, one needs to rely on the elements of visual vocabu-
lary
to produce it, as well as on one’s keen eye to observe
specic kinds of relationships those elements establish.
Negative space between two parallel lines can transform
in viewer’s mind from space to invisible matter, if we
narrow down the gap between those lines ( ).
Very popular instances of exploiting the peculiar
properties of negative space are gure-ground reversal
images, e.g. the Rubins vase ( ). is example
exploits the viewer’s confusion and indecision toward
interpreting what is the actual subject in the image—does
 : Grid organizes text and images. Work-in-
progress view (bottom spread, le page) reveals modular
structure of the layout.
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the contour outline a black silhouette of a vase? Or may be
the negative space between two white proles? An experi-
enced image-maker will know how to handle negative
space to channel its potential and avoid its traps.
viSuAl gRAmmAR: SYnThESiSED SEEing
Synthesized seeing relates to the overall balance of tones
and shades observed in any image or text block. We squint
our eyes to better see the whole by making it harder to
notice specic details and particular features of an image.
In an attempt to see the forest, we choose not to notice trees.
is simple trick—inspecting an image while squint-
ing—provides an informed image-maker with a powerful
tool of analyzing the distribution of shades and tints in
a composition, as well as the relationships between them.
It is also helpful when one looks for the visual keys presented
in the image—viewer’s eyes will most likely notice and
follow those parts of the image, where synthesized seeing
reveals strongest contrasts. Finally, synthesized seeing
gives the image-maker an opportunity to look at the
image with a fresh, unbiased eye, which is always valuable
when some visual distance is required to remain critical.
is technique of synthesized seeing is nothing new
or controversial in the art world—at least not any more.
It is owing to the th Century painters Jean-Baptiste
Camille Corot and Édouard Manet, as well as the impres-
sionists who followed, that we now understand this
anti-idealistic, very sober and critical approach towards
an image: to represent only what is actually seen and
not what is known to be in front of our eyes. Consider
the painting by Claude-Oscar Monet titled “e Beach in
Trouville” (), in which two ladies are portrayed sitting
at the seaside. e observer looks against the sun, hence
ladies’ faces are heavily shaded. Monet could not see their
faces, so even though he knew they had faces and charac-
teristic facial features (eye lids, eye brows, lips, noses,
colored irises, etc.), he did not include that in the picture.
Condent in only what he saw under those specic
circumstances, he painted ladies’ portraits in a very
synthesized manner.
Condent data explorers and visualizers shall keep
in mind Manet’s, Corot’s and Monet’s lessons, and put
themselves in their viewers’ position to seek balance in
their works, as well as judge their image-making from
an objective distance and through squinted eyes.
viSuAl gRAmmAR: TimE
Einstein showed that time is relative, but in our everyday
experience of the passing of minutes, hours, days and years
it changed very little. Time passes just as it passed last year,
a hundred and a billion years ago. However—just like in
Einstein’s physics—time for an image-maker is a malleable
entity, yet another dimension that can be easily bent and
manipulated with the use of simple visualization strategies,
which we discuss below.
In showing time an image-maker employs sophisticated
visual grammar structures, technical properties of selected
media (from simple drawing to motion graphics, to
interactive simulations) and most of all, external cultural
connotations that allow the viewer to relate our real
everyday experience of time to the visualized timescale.
How to slow down time? Whatever in human timescale
takes just a split of a second (e.g.: a lightning) can be
captured on photography and thus its lifespan extended
even million fold. Looking at a photographed lightning
is a gi of time—observing it live never allows enough
time for noticing all the detailed shapes, random curves
and edges it has. Ironically, lightning’s image can be stored
today in the form of a digital bitmap on an electronic
memory drive—maybe some of those electrons released
from the skies are now engaged in storing a portrait of
theirs on our hard drive ( )?
Is this process possible in reverse? How to speed up
the passing of time? On two very simple images comparing
the locations of African and South American continents in
early Mesozoic era and today we can fast forward the
 : Negative space. Invisible matter emerges from
empty space as lines move closer to one another (redesigned
and redrawn aer Adrian Frutiger).
 : Negative space. Figure-ground reversal images
demonstrate how powerful a negative space eect can be.
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INSTITUTE FOR INFORMATION MAPPING
continental dri that took place over  million years
in a glimpse of an eye ( ). Such visualization
not only allows a skilled image-maker to communicate
time to her/his audience. It also explains through illustra-
tions of the results of a complex and invisible geological
process. It argues by backing up a controversial theory
with a convincing scenario. Finally, it fascinates, because
it fuels one’s imagination and interest in earth sciences.
SummARY
Nowadays visualization is one of the key ways, in which
scientic discoveries and advances in collective under-
standing are made. erefore, those scientists, researchers,
data explorers, and analysts who rely in their everyday
work on producing visualizations and generating images,
should have some acquaintance with the most rudimentary
 of good design practice.
Becoming knowledgeable in the basics of any practice-
led discipline is never easy. at being the case, we have
prepared a list of nine design commandments to conclude
this article and hopefully stay with the reader for a while.
Adhering to these commandments of good visual design
practice will assist the reader with maintaining high
quality of her/his own image-making:
1. Make use of points, lines, areas, colors and
typography to communicate information in
a diverse and legible manner;
2. Use no more than  to discrete hues in a single
visualization;
3. Use up to  font forms (serif and sans-serif) and
no more than font sizes;
4. Having decided to use a grid, always respect it;
5. Harness negative space;
6. Less is more—remove redundancy to improve key
message;
7. Place yourself in the position of your audience—
learn to think like they do;
8. Always make good eort—otherwise your reader
will need to;
9. Allow yourself enough time to produce high-quali-
ty visuals.
 : Lightning captured in a photograph. A fraction of
a second prolonged interminably.
 : Two images visualize continental dri. 
million years observed in one second (redrawn aer Antonio
Snider-Pellegrini).
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INSTITUTE FOR INFORMATION MAPPING
FuRThER READing
e list below includes some of the most interesting and
valuable positions, from which further information on
visual language can be obtained. e rst group of works
(da Vinci, Strzemiński, Frutiger, Bertin, Arnheim, Tue)
focus specically on visual language, a diversity of its forms
and expressions. e authors critique visual structures
and provide valuable guidance for implementation in one’s
own image-making practice. Unfortunately, the works of
Frutiger and Strzemiński seem to be available only in their
original languages (German and Polish respectively).
e second group contains a selection of works (McCloud,
Cobley & Jansz, Hall, Maeda, Garland), which investigate
with visual culture in a much broader sense. Here the reader
will nd information on semiotics, the workings of comics,
information design. McCloud and Garland also provide
a detailed account of the design process, which can serve
as inspiration for curious image-makers.
A Treatise on Painting” by Leonardo da Vinci;
“Teoria Widzenia” by Władysław Strzemiński;
“Der Mensch und seine Zeichen” by Adrian Frutiger;
“Semiology of Graphics” by Jacques Bertin;
“Visual inking” by Rudolf Arnheim;
“e Visual Display of Quantitative Information
by Edward R. Tue;
“Envisioning Information” by Edward R. Tue;
“Visual Explanations” by Edward R. Tue;
“Beautiful Evidence” by Edward R. Tue.
“Understanding Comics” by Scott McCloud;
“Introducing: Semiotics” by Paul Cobley
and Litza Jansz;
“is Means is, is Means at” by Sean Hall;
“e Laws of Simplicity” by John Maeda;
“Mr Beck’s Underground Map” by Ken Garland.
BiOgRAphY
Marek Kultys,  is a very interdisciplinary communica-
tion designer, design consultant and an independent
researcher based in London, UK. He works in the eld of
visual communication, information design and visualizing
invisible structures. While actively collaborating with
scientists, information mappers, educators, and other
designers, Marek also pursues his own research into the
interplay between design and sciences. Values design that
makes people think, understand and act.
Marek holds .. in Communication Design from
Central Saint Martins College of Art and Design in London,
having previously studied design in Warsaw and Zürich.
He exhibits, speaks and teaches internationally.
BiBliOgRAphY
Frutiger, Adrian. Człowiek i jego znaki. Warsaw: Do and
Optima, .
Hall, Sean. is Means is, is Means at: A Users
Guide to Semiotics. London: Laurence King Publishing,
.
Niccoli, Matteo. “e rainbow is dead…long live the
rainbow!–Part .MyCarta, . http://mycarta.
wordpress.com/2012/05/29/the-rainbow-is-dead-long-
live-the-rainbow-series-outline/
Niccoli, Matteo, and Lynch, S. “A more perceptual color
palette for structure maps.” Paper presented at the
 / Geoconvention, Calgary, Alberta,
. http://www.cspg.org/documents/Conventions/
Archives/Annual/2012/155_GC2012_A_More_Per-
ceptual_Color_Palette_for_Structure_Maps.pdf
Tue, Edward R. e Visual Display of Quantitative Infor-
mation. Cheshire: Graphics Press, .
... Within the data visualization, no more than six to eight distinct colors should be used to encode data items close to each other. The human visual system cannot distinguish more than eight (Kultys, 2013). Colors that are used to measure should be used with intelligence and a colors saturation level should be scaled to the scale of measurement that color is representing. ...
Thesis
Full-text available
This paper outlines the development of an interactive data visualization on Suicide in Ireland within an installation setting. The LeapMotion 3D Gestural controller is used as the means for a visitor to the installation to explore and interact with the data. A research overview is provided on the two core components of an interactive data visualization, representation and interaction. A background to the issue of suicide in Ireland is provided. Furthermore an overview of the technologies and software used to develop the project is included.Also presented is a detailed account of the developmental process, an evaluation of the installation and 3D gestural control for interactive data visualizations and in conclusion future possible developments and research is provided.
... Within the data visualization, no more than six to eight distinct colors should be used to encode data items close to each other. The human visual system cannot distinguish more than eight (Kultys, 2013). Colors that are used to measure should be used with intelligence and a colors saturation level should be scaled to the scale of measurement that color is representing. ...
Thesis
Full-text available
This paper outlines the development of an interactive data visualization on Suicide in Ireland within an installation setting. The LeapMotion 3D Gestural controller is used as the means for a visitor to the installation to explore and interact with the data. A research overview is provided on the two core components of an interactive data visualization, representation and interaction. A background to the issue of suicide in Ireland is provided. Furthermore an overview of the technologies and software used to develop the project is included.Also presented is a detailed account of the developmental process, an evaluation of the installation and 3D gestural control for interactive data visualizations and in conclusion future possible developments and research is provided.
... Comparison of sub-Bundles in the composite Sequence Bundles visualisation is facilitated by the use of labelling by colour, as well as by plotting each group with a vertical offset relative to one another. The selection of black and saturated light blue colours in Figure 1 complies with the best practices of visual design [13], as it enables users with any kind of colour-blindness to discern each sub-Bundle, thus allowing an even greater range of users to comfortably work with Sequence Bundles. ...
Article
Full-text available
Background We introduce Sequence Bundles--a novel data visualisation method for representing multiple sequence alignments (MSAs). We identify and address key limitations of the existing bioinformatics data visualisation methods (i.e. the Sequence Logo) by enabling Sequence Bundles to give salient visual expression to sequence motifs and other data features, which would otherwise remain hidden. Methods For the development of Sequence Bundles we employed research-led information design methodologies. Sequences are encoded as uninterrupted, semi-opaque lines plotted on a 2-dimensional reconfigurable grid. Each line represents a single sequence. The thickness and opacity of the stack at each residue in each position indicates the level of conservation and the lines' curved paths expose patterns in correlation and functionality. Several MSAs can be visualised in a composite image. The Sequence Bundles method is designed to favour a tangible, continuous and intuitive display of information. Results We have developed a software demonstration application for generating a Sequence Bundles visualisation of MSAs provided for the BioVis 2013 redesign contest. A subsequent exploration of the visualised line patterns allowed for the discovery of a number of interesting features in the dataset. Reported features include the extreme conservation of sequences displaying a specific residue and bifurcations of the consensus sequence. Conclusions Sequence Bundles is a novel method for visualisation of MSAs and the discovery of sequence motifs. It can aid in generating new insight and hypothesis making. Sequence Bundles is well disposed for future implementation as an interactive visual analytics software, which can complement existing visualisation tools.
Conference Paper
*** NB Please see comments section of the page for full text article ***
Article
A text on the graphical display of quantitative data, using combinations of points, lines, coordinate systems, numbers, symbols, words, shading and colour. The book is divided into two major sections; the first reviews past and present graphical practice, such as thematic mapping, time-series plots, narrative and relational graphics. It also discusses graphical integrity, and miscommunication and distortion. Section two covers a theory of data graphics. This includes considerations of physical tools such as ink, design factors, optical art and perceptual factors, colour usage, information content, aesthetics, text and tables. The volume is illustrated with copious examples from past and present literature.-M.Blakemore
Article
The book is the culmination of two years of research by Hall into the relationship between social semiotic theory, communications studies, and art, design, fashion and material culture. It extends the insights of current social semiotic theory and communication studies by showing how the notion of the '€˜shifter' can be used both theoretically and practically to enhance our understanding of how art, design, fashion, and material culture is altered by changes in contextual understanding. The following research contribution should be seen in the light of an interrogation of the use of key semiotic concepts by means of '€˜shifting' their meanings. Seventy-six concepts from social semiotics or communication theory are investigated in, and through, real examples, often drawing from the author's own practice in design, art and photography.
Człowiek i jego znaki. Warsaw: Do and Optima
  • Adrian Frutiger
Frutiger, Adrian. Człowiek i jego znaki. Warsaw: Do and Optima, 2005.
The rainbow is dead…long live the rainbow!–Part 7 MyCartathe-rainbow-is-dead-long- live-the-rainbow-series-outline
  • Matteo Niccoli
Niccoli, Matteo. " The rainbow is dead…long live the rainbow!–Part 7. " MyCarta, 2013. http://mycarta. wordpress.com/2012/05/29/the-rainbow-is-dead-long- live-the-rainbow-series-outline/
  • Matteo Niccoli
Niccoli, Matteo. "The rainbow is dead…long live the rainbow!-Part 7." MyCarta, 2013. http://mycarta. wordpress.com/2012/05/29/the-rainbow-is-dead-longlive-the-rainbow-series-outline/
Paper presented at the 2012 CSEG/CSPG Geoconvention
  • Matteo Niccoli
  • S Lynch
Niccoli, Matteo, and Lynch, S. "A more perceptual color palette for structure maps. " Paper presented at the 2012 CSEG/CSPG Geoconvention, Calgary, Alberta, 2012. http://www.cspg.org/documents/Conventions/ Archives/Annual/2012/155_GC2012_A_More_Per-ceptual_Color_Palette_for_Structure_Maps.pdf