Some quotes about visual thinking, always useful to have at hand:
“More than 50 percent of the cortex, the surface of the brain, is devoted to processing visual information,” points out Williams, the William G. Allyn Professor of Medical Optics. “Understanding how vision works may be a key to understanding how the brain as a whole works.”
“Today we receive 5 times as much communication as we did in 1966. This means how you share your dat will drastically determine the size of your audience. Researchers have found that colour visuals increase the willingness to read by 80% and that we get a sense of a visual scene in less than 1/10 of a second. (…) The more you leave out, the more you highlight what you leave in”
“People are more inclined to perceive certain visual cues (variables) better than non-visual cues” –
SAP Analytics Cloud. The data Visualization handbook.
Guide for Dataviz basics
“Vision is enabled by the eyes, which contain a light-sensitive chemical that converts light energy from our environment into electrical activity; a process referred to as transduction. This electrical activity is then transmitted from the retina, a layer of tissue at the back of the eye containing photoreceptor cells, to the brain via the optic nerve. Once this information is received by the brain it is instantly transformed into conscious experience, which we use to identify and locate all objects in our environment and guide our movements and interactions. We are also able to determine our distance from objects, the distance between objects and their relationships to each other on the basis of light information.(…) Human vision is the product of light energy entering the eye, which is then converted into electrical activity. This electrical energy then undergoes a series of different processes in the brain to create our conscious experience of the world. Therefore, we must understand the physiology and the processes underlying visual perception in order to fully appreciate what and why we extract what we do from our environment.”
The Interaction Design Foundation. (n.d.). 1.1: Understanding Human Vision. The Interaction Design Foundation. https://www.interaction-design.org/courses/the-ultimate-guide-to-visual-perception-and-design/lessons/1.1.
“Perception is the process through which people acquire, interpret, and organize information coming from their sensory organs. It starts with sensory registration of the information and ends with construction of mental representations of the perceived object. Perception influences every act of creation because the way people perceive things determines how they think about things.”
E Necka Encyclopedia of Creativity Elsevier Ed 2011
“The reason for writing this text was the fact that although our knowledge is based on a collection of the most elementary facts and experiences, we usually start being aware of them and begin to study them only when something stops functioning. Perception after all is one of the basic ways of meeting reality and for many it actually is the reality. Despite this, it is usually the last thing we think of in our research.(…)
“To study the world means to study perceptions and ideas we created, and the world is mainly the world of perceptions, images or ideas. Thus, when we want to study something, first we should know where, when and how to meet and learn it. “
Perception Theories, Andrej Demuth 2013
“If we are going to use our visual skills to assist us in data analysis, it is important to remember that they have evolved to handle quite different tasks from those encountered in a typical data analysis. The tasks which our visual system excels at are those which were useful to our hunter-gatherer forbears. These tasks include recognising shapes, discerning colour, judging sizes and distances, and tracing and extrapolating motion in three dimensions. Some of these skills seem directly useful in data analysis, but it is very important that we understand both the strengths and weaknesses of the visual system when used in this way. “
Ross Inhaka. Notes to Statistic 120 : Information Visualisation course, Statistics Department, Auckland University.
“Choosing a set of colours which work well together is a challenging task for anyone who does not have an intuitive gift for colour. Some general guidance on colour choice is available in books on art and graphic design. These books suggest the use of complementary colours, split complementaries, triads and tetrads. Most of the advice is based on the use of a vaguely described “colour wheel,” and does not recognise the fact that there are many different colour wheels to choose from.
The notable exception to this rule is to be found in the work of the noted 19th century colourist Albert Munsell. Munsell developed a colour notation system (, , ) which he used in teaching. The system is deeply rooted in how we perceive colour but has a strong quantitative basis. In addition, Munsell gives well defined, quantitative rules which can be used to choose harmonious sets of colours. Munsell’s work has always been appreciated in publishing and related graphic arts, and it now appears to be undergoing a rediscovery by those working in user-interface design and visualisation (see ,  and  for example).
Munsell describes colour in terms of hue, value and chroma; hue corresponding to dominant wavelength, value to brightness and chroma to colourfulness. Unlike saturation, which is a statement of colourfulness relative to the maximum possible for a given hue and value, chroma is an absolute measure of colourfulness (the maximum chroma possible for red is much greater than that for green). “
Ross Ihaka. Colour for Presentation Graphics Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003) March 20–22, Vienna, Austria
“All perceiving is also thinking, all reasoning is also intuition, all observation is also invention.” — Rudolf Arnheim, Art and Visual Perception: A Psychology of the Creative Eye (1954)
“To the physicist, balance is the state in which the forces acting upon a body compensate one another. In its simplest form, balance is achieved by two forces of equal strength that pull in opposite directions. The definition is applicable to visual balance. Like a physical body, every finite visual pattern has a fulcrum or centre of gravity. (…) Visual balance can be obtained in infinitely different ways (…) I see an object, I see the world around me. What do these statements mean? (…) If vision is an active grasp, what does it take hold of?”
Rudolf Arnheim, Art and perception.2nd edition.
“The habit of separating the intuitive from the abstractive functions, as they were called in the Middle Ages, goes far back in our tradition. Descartes, in the sixth Meditation, defined man as "a thing that thinks," to which reasoning came naturally; whereas imagining, the activity of the senses, required a special effort and was in no way necessary to the human nature or essence. The passive ability to receive images of sensory things, said Descartes, would be useless if there did not exist in the mind a further and higher active faculty capable of shaping these images and of correcting the errors that derive from sensory experience. A century later Leibniz spoke of two levels of clear cognition. Reasoning was cognition of the higher degree: it was distinct, that is, it could analyse things into their components. Sensory experience, on the other hand, was cognition of the lower order: it also could be clear but it was confused, in the original Latin sense of the term; that is, all elements fused and mingled together in an indivisible whole. ”
“At the same time, the popular symbolic image, gained from a superficial knowledge of the actually quite complex physiological facts, tends to reinforce the prejudice that the intuitive and the intellectual modes of cognition function in separation from each other and that, in fact, different individuals and different professions come under either the one or the other heading. This is a harmful misunderstanding. Everything we are learning about the mental functioning of scientists and artists strengthens the conviction that the intimate interaction between intuitive and intellectual functioning accounts for the best results in both fields. “
A plea for Visual thinking, Arnheim Rudolph
“Order is a necessary condition for anything in the human mind to understand. Arrangements such as the layout of a city or building, a set of tools, a display of merchandise, the verbal exposition of facts and ideas, or a painting (….) order makes it possible to focus on what is alike and what is different, what belongs together and what is segregated”.
“(…) to transmit information means to induce order”
Order and Entropy, Rudolph Arnheim
“The current theory is that a child “draws what he knows rather than what he sees”. This theory implies the paradox that the more undeveloped creatures elaborate their sensations through higher mental processes…”
“Human vision is not simply a series of photographic images of our surroundings; as Bruce E. Goldstein, Associate Professor at the University of Pittsburgh and author of Sensation and Perception, states "...we do not just perceive what is out there. We perceive what is out there as filtered through the properties of the visual system". In order to understand what we see, we must first understand how we interpret light energy - entering the brain through the eye - into a meaningful and accurate representation of our environment.
Consideration must be given to the hue, size and distance between items when using different colours in a display, especially when the colour distinctions are important to the users understanding of the information. Here you will learn what you should do and why.
Colour plays an important role in signalling function, whether these colours occur naturally or are man-made/artificial. For example, we can determine the relative ripeness of fruit in the greengrocer's thanks to natural colour differences and we know when to stop at traffic lights through artificial/contrived colour differences.
Colour also plays an essential role in perceptual segregation, which refers to our ability to distinguish one object from another and focus on specific elements within a busy visual array. Perceptual segregation is not specific to humans, as the ability to distinguish objects is vital to the survival of many animal species. Imagine the difficulty facing an insectivorous bird if they could not isolate an insect from hundreds, if not thousands of leaves. “
(IDF, Ultimate Guide to Visual perception course, 2019)
“The composing of intelligible patterns from the noise of raw data is a hallmark of a good information designer. The most successful examples extract and present essential relationships in a coherent manner while limits ng the obtrusiveness of accessory relationships. Effective relationships are self-evident whereby the information graphic is absorbed by the mind holistically(…)
“The success of layered compositions depend on the appropriateness of the base map (pictorial, relational, quantitative or symbolic) and the quality of the designers integration (…) A first consideration in the design of information visualisation is whether users will se information as a total or ascertain through a sequence of portions.”
Parson’s Journal for Information Mapping, 2010. William Bevington and William Anderson. Complications and adjacencies
“Four phases of the problem-solving model are defined by two interconnecting continuums describing the nature of design activity and thinking. The first continuum, knowledge to making, marks the beginning and ending points of a typical design process (…) The second continuum involves different types of thinking applied in problem solving.”
Parson’s Journal for Information Mapping, 2010. Joanne Mendel and Jan Yeager. Knowledge Visualisation in Design practice.
“Perceptual processes are realized by a biological vision system that evolved under circumstances that have favored organisms (or genetic structures) that sustain contact with the environment. No one doubts that a description and understanding of the hardware of the visual system will eventually be part of an account of perception. Nevertheless, there are important differences among theories in their uses of neurophysiology”
“Gestalt theory proposes that the process of perception is an executive-free expression of the global properties of the brain. The organization and orderliness of the perceptual world is an emergent property of the brain as a dynamical system. Gestalt theory intends to distance itself from any position that posits an executive (an homuncular agency) that oversees the work of the perceptual system. The Gestalt theory, thus, recognizes regulation but will not allow a regulator. A dynamical system that instantiates a massively parallel self-organizing process satisfies is regulated but does not have a regulator. As such, the perceptual world is different from the sum of its parts and cannot be understood by an analytic investigative strategy that adopts a purely local focus. To understand perception, we need to discover the principles that govern global perception. “
Visual Perception: Theoretical and methodological foundations M. Kubovy et al.
“Functions of vision: provide data for memory (maps, objects). Guide action (obstacle avoidance, navigation, homing, reaching, object manipulation).”
(Ohno, 1988)PS 2011/16 Cognitive Psychology. Visual Perception Carlo de Lillo.
“the greatest value of a picture is when it shows us what we never expected to see”
-Parson’s Journal for Information Mapping, 2010. Kennedy, Christopher. Groups and Spaces: Mapping collaborative cultural production and social art practices.
On network diagrams
-Parson’s Journal for Information Mapping, 2010. Peter Bain. Aspects of transit Map Design
On printed transit maps
-Per Mollerup. Slide presentations. Reconsidered, IIID Library
-Mind Map Mastery. Tony Buzan.
“… from this experience, Simonides realised that anyone could improve their memory by selecting locations and forming mental images of the things they wish to remember. If the images were stored in the visualized places in a particular order, it would then be possible to remember anything trough the power of association. The resulting method of loci was described in a number of rhetorical treatises of Ancient Greece and Rome…”
”whereas linear note-taking uses three basic skills of linear patterning, symbols and analysis, image making engages a wide range of cortical skills, from imagination, logic and spatial awareness to the use of colour, form, line dimension and visual patterning”
“ A study into image recognition, carried out by professor Ralph Habber in 1970, found that humans have an almost photographic memory when it comes to the recognition of pictures, making images an excellent memory aid”
“Little did I know at the time, but this technique is similar to chunking, which is a well-known mnemonic technique first described by the American psychologist George Armitage Miller (1920-2012) in 1956. The term came from Miller’s famous paper “ The magical number seven, plus minus two” in which he explained how the short term memory can only store seven items of information efficiently”
-DESMA 103 Visual Communication Handout 1 Prof Erkki Huhtamo
“ According to Stuart Hall, all images are both encoded and decoded. They are encoded in the production process and in the placement within a certain cultural setting.”
“ Definition of schema): the mechanism of recall thorough imagery, a fairly simple, easily memorized structure which exist beyond its diverse manifestations (Jacques Aumont)”
“ Information visualizations are good at providing context and uncovering patterns that can facilitate decision-making”
-Isabel Meirelles. Innovative Approaches to turn statistics into knowledge.
-Robert E Horn Information Design: Emergence of a new profession
“Information design is defined as the art and science of preparing information so that can be used by human beings with efficiency and effectiveness. Its primary objectives are:
To develop documents that are comprehensible, rapidly and accurately retrievable, and easy to translate into effective action…”
Pontis, Sheila. La historia de la esquematica en la visualization de datos
Visual thinking is an activity that take space where no one can see it , inside our heads. There has been a debate about mental imagery and visual thinking for many years. Visual thinking and visual thoughts are visual representations that arise when we think.(…)[Arnheim] described visual thinking as the unity of perception and conception that calls for the ability to see visual shapes as images(pictures, signs and symbols).”
Petterson, Rune. Cognition ,IIID Library
“ To be able to produce a visual message in any medium it is important to understand the major characteristics, the possibilities and the restricitons, of visual languages and pictures. We need to knpw hhow visual languages are constructed, how they are perceived an how they differ from verbal lanfuages.”
Petterson, Rune. Image Design,IIID Library
“… texts and pictures represent different languages that complement each other when they are used at the same time (Petterson,1989;Melin,1999). Both can be designed, presented, perceived and interpreted in many different ways.(….) Text relevant picture facilitate learning when reading from prose(Levin et al,1987). Most pictures are capable of several interpretations until anchored to one by caption (Barthes,1977)”
Petterson, Rune. Message Design,IIID Library
“fixee en un point significatif dans le lan, la tache, a condition d avoir une certaine dimension, peut etre dessinee de differentes manieres. Elle peut varier de:
et exprimer une correspondance entre sa position plane et sa position dans la serie etalonnee de chaque variation (…) le dessinateur dispose ainsi de huit variations sensibles. ce sont les composantes du systeme d expression. Nous les appelerons variables visuelles.”
(fixed at a significant point in the plane, the task, provided it has a certain dimension, can be drawn in different ways. It can vary from: Size/Value/Grain/Color/Orientation/Form and express a correspondence between its plane position and its position in the calibrated series of each variation(…) the designer thus has eight significant variations. they are the components of the expression system. We will call them visual variables.)
Bertin, Jacques. Semiologie des grafiques
“One of the earliest contributions to the science of perception was made by the Gestalt School of Psychology. The original intent of this effort when it began in 1912 was to uncover how we perceive pattern, form, and organization in what we see. The founders observed that we organize what we see in particular ways in an effort to make sense of it. The result of the effort was a series of Gestalt principles of
perception, which are still respected today as accurate descriptions of visual behaviour. Here are a few of the principles that can inform our data visualization efforts:”
Few, Stephen. IDF, the HCI encyclopaedia.
“ Visual thinking means taking advantage of our innate ability to see-both with our eyes and with ours mind’s eye- in order ideas that are otherwise invisible, develop those ideas quickly and intuitively, and then share those ideas with other people in a way that they simply “get”. That’s it. Welcome to a whole new way of looking at business.”
“There are only three tools that we will need to become great at solving problems with pictures: our eyes, our mind’s eye, and a little hand-eye coordination. I call these our “built-in” visual thinking tools …”
Check preattentive visual properties table:
Proximity, colour, size, orientation, fate, shape, shading
The back of the napkin, p 66, Dan Roam
“Paul Grice was a 20th century philosopher whose work ventured into the realm of linguistics. He is well known for his conversational maxims, which attempt the describe the characteristics of polite conversation.
Grice conversational maxims:
Every one of these maxims of conversation apply equally well to the communication of quantitative information in the workplace. We’ll strive in this workshop to translate these maxims into effective and polite communication via tables and graphs.”
Telling compelling stories with numbers. Stephen Few. SLDS Annual Grantee meeting.
A visual information-seeking mantra for designers: ‘Overview first, zoom and filter, then details-on-demand.’(Readings in Information Visualization: Using Vision to Think, Stuart K. Card, Jock D. Mackinlay, and Ben Shneiderman, Academic Press, San Diego, California, 1999, page 625)
“Various authors have attempted to approach graphics with the linguistic concept of grammar. Let us briefly review a few examples. In 1914, Willard Brinton writes in his book Graphic methods for presenting facts that “The principles for a grammar of graphic presentation are so simple that a remarkably small number of rules would be sufficient to give a universal language”.
“Graphics can be regarded as expressions in visual languages. We have tried to show that specifying such a visual language means a) specifying the syntactic categories of its graphic objects, plus b) specifying the graphic space in which these graphic objects are positioned, plus c) specifying the visual coding rules that determine the graphic properties of these graphic objects”
Engelhardt, Yuri. Syntactic Structures in Graphics
“ El lenguaje visual, independientemente de sus carafteristicas, transmite un mensaje de dos dimensiones. Esto queire decir que al tewner delante una imagen el ojo erra (deambula) libremente por la superficie optica que esta define. Y en el caso de que. La mirada no sea libre, como en un grafico de instrucciones, al menos cree serlo y va donde quiere, no esta disciplinada por unmecanismo de obligacion cultural (apreender a leer) que impone ladireccion de la linea a los movimientos de los ojos (…)El mensaje escrtito conlleva un “pensamiento en linea”, mientras que el mensaje visual un “pensamiento en superficei”. Este concepto lo desarrolla Yves deforge en el libro Imagen didactica, explicando que ambos pensamientos han competido y se han completado en todas las epocas de la historia”
Pontis, Sheila. La historia de la esquematica en la visualizacion de datos.
“Part of the Bauhaus legacy is the attempt to identify a language of the vision,a. code of abstract forms addressed to the inmediate , biological perception rather than to the culturally conditioned intellect. Bauhaus theorists described this language as a system analogous-but isolated from-verbal language. Visual from was seen as a universal and transhistorical script, speaking directly to the mechanics of the yes and brain.(….) In the textbooks of Kandinsky, Klee, Moholy Nagy and others, information graphics function as models for a new aesthetic, an art that is at once didactic and poetic. Scientific grids, graphs and diagrams constituted a privileged branch of the sign; they were seen as the basis of a visual script that is ant illusionistic yet universally comprehensible, a graphic language that avoids the conventions of perspectival realism yet is linked objectively to material facts”
Lupton, Ellen. The ABC of the Bauhaus Design and Theory.
“Suppose we remove words from their meanings and limit them to their actual shapes, i.ie. examine the language as language. The perceptual dimensions of language – its sounds and written appearance-are unstructured. Little information can be communicated to someone who does not know a language just by presenting him with spoken or written words (…)
“most mathematicians visualize their formulae and manipulate them as a structure. (…) the ability to visualize a problem is a useful skill in solving it and that to mathematicians, notation is a form of graphical visualization.”
David Canfield Smith, Pygmalion: a creative programming environment Standford AI Laboratory, 1975.
“The key idea of information visualization is to make use of people’s powerful visual system to efficiently process information that otherwise requires more cognitive effort. Human visual system is powerful because it can process information in parallel, automatically and unconsciously, and it can bypass the bottleneck of human working memory that is limited in capacity.”
Jiajie Zhange et al , Human centered Information Visualization, School of Health Information Sciences.
“Waller (1985:105-108) proposed the concept of a diagram (…) When a text is placed in the form of a diagram, the structure becomes more accessible to a less linear reading, enabling readers to choose ways to understand the tet and crwate your own ready strategy(…)the structure of the diagram, the most typical form of an infographic, is perhaps the key to understand how an infographic is configured. Infographics are essentially diagrams in the way that pictures, words and schematic are arranges in a layout. These multimodal structures are conceived with a nonlinear reading strategy in mind, providing more freedom to the reader(Lima,2009). Each Infographic is arranged according to certain rules of use compatible to its genre.”
Ricardo Cunha Lima, Carla Spinillo et al. “The relation between online and print information graphics for newspapers” Conference paper June 2014.
“The goal is to produce synoptic maps that allow the relationships between the elements of literary narrative to be seen, and specifically, to show complex relationships in a more easily understood way using linear forms.This mapping system improves the model of the map with idea of network, which, as described by Franco Farinelli, President of the Italian Geographers’ Association, “is born precisely when we in-terchange the relation that we are used to between line and plane, and we recognize the priority of the first: (5) “a line is an area with a double limit” (6). A network is “a fabric with multiple threads, all of which are in reciprocal communication, relationship and union” (7). A model based on the multiplicity and the existence of series, which are not parallel but intersect. A system that, compared to the alignment of elements, explicitly opposes the model of the map, on which each element enters into a relationship and contact with all others, which are not limited to precede or follow, but which are placed alongside, exactly “as in the case of territory on a geographical map”
Franchi, Francesco. Graphic literature. 2011. Malofiej17.
INTELLIGENCE literally means being able to understand and quickly comprehend what we see. In order to help us graphic designers use visual metaphors which are a powerful aid to human thinking. During the course of human history people have used numbers, shapes and illustrations to share their ideas with others. Today images play an ever more prominent role and the demand on our creativity to visually convey ideas and meaning has increased proportionally. Diagrams and data graphics have become the language we turn to embody abstract data and at the same time to abstract from complex reality.
Infographics are not just a translation of what can be read to what can be seen. They help us understand, create and experience our reality. They reveal the hidden, explain the complex and illuminate the obscure. They definitely are an exercise of journalism. To construct effective visual representations of information, graphic designers must filter the information, establish relationships, discern patterns and represent them in a way that allows the consumer of that information to process and digest meaningful knowledge.
Designing an infographic means finding a better way to explain a concept, to present it and in the end create a representation that works.
The issue of complexity can be connected to the amount of data to be presented. A huge amount of information brings the necessity to a good space organization, so how the elements are arrange in the space is important. Even if the design is composed of many elements, the structure the graphic designer uses can make it appear simple.
It is a process of sorting elements, labelling them, integrating and prioritizing them.
Franchi, Francesco. The limits of infographics. 2010. Malofiej17.
“In a scientific context, data are generally understood to result from the generation, collection, observation, or registration of objects, events, or processes suitable to serve some analytical purpose. Similarly, in the con-text of data visualization, data can be anything that can be subjected to categorization, abstraction, and translation into graphical representation: persons, places, documents, relations, sentences, salaries, to mention some examples. A main distinction is between qualitative data and quantitative data. While qualitative data are valued for the uniqueness of each individual unit, be it a poem, a sentence, or an interview, quantitative data are valued for characteristics shared by all or many units in a dataset. It is their shared characteristics that make them objects for counting or measuring, and thus for numeric representation and statistical processing.
Both qualitative and quantitative data can be visualized. It is possible to visualize semantic structures in a novel, or networks of relationships between the works in an art collection, as seen, for example, in the work of Stefanie Posavec (http://stefanieposavec.com/). Most, but not all, of the contributions in this book focus on the visualization of quantitative data, for the reasons given above—that is, because their proliferation and increasing openness, and the enhanced availability of related tools, make them a socially and culturally significant phenomenon.
Numeric data can be structured or unstructured. Structured data have been subjected to statistical treatment and are typically represented as numbers in a table, with columns and rows presenting units and variables and numeric values positioned in cells.”
Helen Kennedy and Martin Engebretsen. Introduction: the relationships between graphs, charts, maps and meanings, feelings, engagements. In: Data Visualization and society. Amsterdam University Press. 2020
“In text linguistics, the narrative mode is distinguished from the text modes of description, explanation, and argumentation (Brinker, 2010).(…) A term that often appears in the context of the narrative mode is showing. In journalism, trainers give the normative advice: ‘Show, don’t tell’ (e.g. Mencher, 1997, p. 154). It means not describing a particular subject from the narrator’s point of view (the narrator remains in the background), but allowing the reader to witness the events, to experience the emotion(…)regard a narrative as a textual, visual, or multimodal representation that presents a story. As such, a narrative is the semiotic product of narrating (Genette, 1988, p. 14). Every narrative is based on a story and mediated by a narrator, the person or speech position from which the story originates, or ‘the individual agent who serves as the answer to Genette’s question qui parle?’ (Margolin, 2014).(…) What defines story? On a very basic level, a story is a sequence of events or happenings that are temporally structured and coherently related to each other, involving one or more characters or anthropomorphic agents or objects.”
Wibke Weber. Exploring narrativity in data visualization in journalism. In: Data Visualization and society. Amsterdam University Press. 2020
“A visualization is a graphical representation designed to enable exploration, analysis, or communication”
Cairo, Alberto. The Truthful Art.
“Design for your audience, not for you.
If your audience doesn’t get it, it’s no good for you. Identifying your audience will help determine the tone of your language and the format of your publication.
A user-centered design process starts with lots of questions, rather than answers. The key is identifying the user’s perspective at the outset.
Don’t let your design reflect your institutional structure or bias. Design has a tendency to reflect bureaucracy, especially in NGOs.”
John Emerson. Visualizing Information for Advocacy. 2008
“Visualizing data is to literally create and then consider a visual display of data. Technically, it is not an analysis, nor is it a substitute for analysis. However, visualizing data can be a useful starting point prior to the analysis of data”
Introduction to data Analysis Handbook.TAC-12.2006.
“Data are the facts and figures that are collected, analyzed, and summarized for presentation and interpretation. Data may be classified as either quantitative or qualitative. Quantitative data measure either how much or how many of something, and qualitative data provide labels, or names, for categories of like items. For example, suppose that a particular study is interested in characteristics such as age, gender, marital status, and annual income for a sample of 100 individuals. These characteristics would be called the variables of the study, and data values for each of the variables would be associated with each individual. Thus, the data values of 28, male, single, and $30,000 would be recorded for a 28-year-old single male with an annual income of $30,000. With 100 individuals and 4 variables, the data set would have 100 × 4 = 400 items. In this example, age and annual income are quantitative variables; the corresponding data values indicate how many years and how much money for each individual. Gender and marital status are qualitative variables. The labels male and female provide the qualitative data for gender, and the labels single, married, divorced, and widowed indicate marital status.”
Anderson, D. R. , Williams, . Thomas A. and Sweeney, . Dennis J. (2020, October 20). Statistics. Encyclopedia Britannica. https://www.britannica.com/science/statistics
“ A second area of statistical graphics is graphical methods for data analysis. Such a method consists, essentially, of a choice of a certain quantitative information to show on a graph to help the analyst understand the data or understand the performance or porperties of a statistical model fit to the data(…) Having decided what quantitative information it is useful to display, one need to construct a graph. This is a third area of statistical graphics-graph construction. We must decide what geometric aspects of the graph will encode the quantitative information, choose the scales, choose the parameters, and so forth. Many of the decisions are controlled by conventions(…) but a large amount of the detail of graph construction is nevertheless in the hands of the person making the graph”
W.Cleveland, R. McGill.
Graphical Perception: The Visual Decoding of Quantitative Information on Graphical Displays of Data. In: Journal of the RSS. Series A.Vol 150,N3. 1987
“Although he is concerned with clarity more than with art, Tufte's examples of well-designed diagrams do occasionally resemble comics. In a chapter on "Multiples in Space and Time," for example, he presents a set of Muybridge's motion-analysis photographs on the same page as Huygens's time-series drawing of Saturn's orbital path and a set of maps showing continental drift. As Ware's interest in Muybridge reminds us, each of these time-series diagrams reads, sequentially, like a comic.32 Diagrams of the movement of a seahorse or a gecko also use simplified images (cartoons) in sequence throughout the time-series section of Tufte's chapter on "Graphical Excellence." Notably, Tufte treats these comics or proto-comics as if they are interchangeable with the other, more chart-like diagrams in these chapters. He also analyzes a number of comics or comics-like diagrams in a chapter of Visual Explanations that deals with the diagrams used to explain magic tricks. Because sleight of hand requires several stages of movement, these diagrams typically include multiple images of the same disembodied hands, revealing or suggesting the gestures and manipulations that make the trick work. Nearly all of these diagrams combine drawings with words, and they often also have recourse to other cartooning shorthand: motion lines, impact lines, and ghosted overlapping images. As Tufte points out, these are "device[s] often used in comics."34 The fact that Tufte does not seem to distinguish between explanatory comics and explanatory diagrams could provide his most provocative contribution to the study of comics, even if this contribution is never articulated in those terms. It's natural for comics or comics-like sequences such as Muybridge's photographs to appear in discussions of the diagrammatic representation of events unfolding over time or depictions of time-series data. If a single dimension of information (data about a single variable) is plotted over time, a straightforward two-dimensional graph is the obvious choice. If more than one variable must be correlated over a relatively small number of time samples, time-slice diagrams for the data-one graph per sampled moment-can essentially be read as a comic with graphs or charts for sequential "panels."35 But for diagrams and charts, the measured progress of time is only one of many different sorts of data that the two dimensions of the page can describe. A chart could plot inflation against unemployment, temperature against conductivity, atomic number against atomic volume, or years in Chicago against that Chicagoan's average monthly phone bill. Diagrams use spatial proximity to denote a wide range of connectionslinkages of meaning, and not necessarily of time. Since comics is a narrative medium, it inevitably uses the device of graphic juxtaposition mainly for narrative ends. If comics is such a near cousin to the diagram, however, and if diagrams can borrow the graphic idiom of comics to explain the movements of a seahorse or a sleight of hand, then there can be little reason for comics not to borrow from the wider range of graphic semantics allowed to the diagram. In particular, both Chris Ware's diagrams and Edward Tufte's appropriation of sequential art should remind us of the valuable possibility for literary comics of diagram-like non-chronological juxtapositions, sequences of images that are related in ways that have less to do with time than with other interrelations of meaning: metaphor, options and potentiahties, thematic synopsis, spatial relationships, and many other unplumbed possibilities.”
Cates, Isaac. Comics and the Grammar of Diagrams. In: The comics of Chris Ware: Drawing as a way of thinking. University Press, 2010. p 90-103.
“Graphs are essential to good statistical analysis. Ordinary scatterplots and "triple" scatterplots are discussed in relation to regression analysis. (…) The analysis of a two-way table by calculating row means, column means, residuals and what R. A. Fisher called the analysis of variance, may be regarded as a special instance of regression analysis. The structure is now sufficiently rich that graphical presentation in advance of numerical calculation is probably not too useful. But after the calculations the same sorts of graphical treatment as for ordinary regression have the same effectiveness. Residuals may be scatterplotted against fitted values on the same scale. Row effects can be plotted against column effects, on the same scale, in a TSCP with coded residuals. (It was Tukey's elegant use of a kind of TSCP for two-way tables that introduced me to the idea; see Chapter 16 in .) If the rows or columns have a meaningful natural order, the residuals should also be presented in that order.
Rectangular tables (cross-classifications) in two or more dimensions, with some modes of classification perhaps "nested" rather than "crossed", are of common occurrence. Whenever any set of main effects and interactions has been calculated, the residuals should be scatterplotted against the fitted values, and various sorts of TSCP may be interesting. This article is emphatically not a catalog of useful graphical procedures in statistics. Its purpose is merely to suggest that graphical procedures are useful. Only two types of graph have been mentioned, the ordinary scatterplot and the triple scatterplot, and these have been considered in only one sort of context (regression). There are other types of graphs and display devices that can make quantitative relations visible and comprehensible, and other sorts of statistical tasks than regression.”
Anscombe, Francis J. Graphs in Statistical Analysis. The American Statisitcian. Vol 27, N° 1 Feb.1973, p 17-21
“In 1628, van Langren wrote a letter to the Spanish court, in an eﬀort to demonstrate the importance of improving the way longitude was calculated (and of giving him the funding to do so). To make his case, he drew a simple one-dimensional graph. On the left, he drew a tick mark, representing the ancient city of Toledo, in Spain. From this point, he drew a single horizontal line on the page, marking across its length twelve historical calculations of the longitudinal distance from Toledo to Rome. The estimates were wildly diﬀerent, scattered all across the line. There was a cluster of estimates at around twenty degrees, including those made by the great astronomer Tycho Brahe and the pioneering cartographer Gerardus Mercator; others, including the celebrated mathematician Ptolemy, put the distance between the two cities closer to thirty degrees. All the estimates were too large—we now know that the correct distance is sixteen and a half degrees. But the graph was meant to show just how divergent the estimates were. Depending on which one was used, a traveller from Toledo could end up anywhere between sixty miles outside Rome and more than six hundred miles away, on the plains of eastern Bulgaria.(…) Data visualization has progressed from a means of making things tractable and comprehensible on the page to an automated hunt for clusters and connections, with trained machines that do the searching. Patterns still emerge and drive our understanding of the world forward, even if they are no longer visible to the human eye. But these modern innovations exist only because of the original insight that it was possible to think of numbers visually. The invention of graphs and charts was a much quieter aﬀair than that of the telescope, but these tools have done just as much to change how and what we see.”
When graphs are a matter of life and death. Fry, H. New Yorker. June 21,2021.
“Now that you have had a chance to define your goals, identify some supporting data, and consider appropriate visual encodings, it’s time to think about he particulars of how to apply those encodings. That means making some decisions about what placement will signify and where particular visual entities will go on the page, what attributes (such as color, size, and texture) you will assign them, and how you will label and describe them.(….) We’ll start with a discussion of spatial position—axes and placement—because this property defines the scope and visual landscape that your visualization will occupy. For this and other reasons, spatial position is often the most important visual encoding you’ll have to select. Once we have covered basic placement and organization, we’ll move on to color and other visual encoding properties in Chapter 6.(…)
Now that you have a sense of what structure you’ll use to represent your data, and how it will be positioned on the page, it’s time to consider the other visual properties for encoding your data and to fine-tune your choices.
We’ll begin with a discussion of color, including some of the challenges that color selection presents, and the best uses of color. Then we’ll review other visual encoding properties—such as size, shape, lines, and text—and give suggestions for how each should be treated. Finally, we’ll present some common (and slightly humorous) pitfalls, and give advice for how to avoid them.(…) Bear in mind is that the use of color doesn’t always help. Use it sparingly and with a specific purpose in mind. Remember that the reader’s brain is looking for patterns, and will expect both recurrence itself and the absence of expected recurrence to carry meaning. If you’re using color to differentiate categorical data, then you need to let the reader know what the categories are. If the dimension of data you’re encoding isn’t significant enough to your message to be labeled or explained in some way—or if there is no dimension to the data underlying your use of difference colors—then you should limit your use so as not to confuse the reader”
Ilinsky Noah and Steele, Jule. Designing Data Visualizations. O’Reilly Media, 2011. p 65-83 About encoding.
“Another device that Ware seems to delight in using is the diagram (fig. 18). The example here shows the family background of Jimmy’s step–sister, Amy. (…) In this diagram we make a startling discovery that neither Amy nor Jimmy is ever aware of: they’re actually related––they’re distant cousins. The diagram flows in reverse chronological order from top to bottom. Amy’s biological mother is in the hospital with her mother, who we see was married to a soldier. (…) In the lower–right corner we see the old Corrigan homestead that belonged to Jimmy’s great–great–grandmother, while in the lower–left corner we see Amy’s great– grandmother as a toddler picking a flower that is still kept in her family’s Bible. This diagram contains a great deal of information that is economically packed into a small amount of space. The final example (fig. 19), and probably the most ingeniously constructed page that manipulates past and present, is a game of hide–and–seek that James plays around his grandmother’s house(…)I’m going to rely upon Raeburn’s explication:
This page is one drawing subdivided into twelve panels, each representing a different point in space or time––which are the same thing, basically, in comics. As James seeks the red–haired girl his movements form a question mark that curls around the fifth and sixth panels, which ‘exist’ 50 years ago in time. This is more startling because the Italian boy has time–traveled back along with the narrator. Ware eases the reader out of this wormhole into more conventional comics storytelling by using a transitional panel, which shows the time when the Corrigan home was only a frame.
What is so astounding is not that we are transported between decades, but that Ware manages to accomplish this with a single image––James’s grandmother’s lot––that is subdivided into twelve panels. The twelve images portray three different historical periods, in addition to the few minutes of the on–going game of hide–and–seek. “
Dycus ,D. Ware’s Jimmy Corrigan:Honing the hibrydity of the graphic novel.Dissertation.Georgia State University, 2009. p. 125
“In my view, the practice of information visualization from its beginnings in the second part of the 18th century until today relied on two key principles. The first principle is reduction. Infovis uses graphical primitives such as points, strait lines, curves, and simple geometric shapes to stand in for objects and relations between them - regardless of whether these are people, their social relations, stock prices, income of nations, unemployment statistics, or anything else. By employing graphical primitives (or, to use the language of contemporary digital media, vector graphics), infovis is able to reveal patterns and structures in the data objects that these primitives represent. However, the price being paid for this power is extreme schematization. We throw away %99 of what is specific about each object to represent only %1- in the hope of revealing patterns across this %1 of objects’ characteristics.
Information visualization is not unique in relying on such extreme reduction of the world in order to gain new power over what is extracted from it. It comes into its own in the first part of the 19th century when in the course of just a few decades almost all graph types commonly found today in statistical and charting programs are invented.12 This development of the new techniques for visual reduction parallels the reductionist trajectory of modern science in the 19th century. Physics, chemistry, biology, linguistics, psychology and sociology propose that both natural and social world should be understood in terms of simple elements (molecules, atoms, phonemes, just noticeable sensory differences, etc.) and the rules of their interaction. This reductionism becomes the default “meta-paradigm” of modern science and it continues to rule scientific research today. For instance, currently popular paradigms of complexity and artificial life focus our attention on how complex structures and behavior emerge out of interaction of simple elements.(…) Do all these different visualization techniques have something in common besides reduction? They all use spatial variables (position, size, shape, and more recently curvature of lines and movement) to represent key differences in the data and reveal most important patterns and relations. This is the second (after reduction) core principle of infovis practice as it was practiced for 300 years - from the very first line graphs (1711), bar charts (1786) and pie charts (1801) to their ubiquity today in all graphing software such as Excel, Numbers, Google Docs, OpenOffice, etc. This principle can be rephrased as follows: infovis privileges spatial dimensions over other visual dimensions. In other words, we map the properties of our data that we are most interested in into topology and geometry. Other less important properties of the objects are represented through different visual dimensions - tones, shading patterns, colors, or transparency of the graphical elements. ”
Manovich , Lev. What is visualization?. October 2010. http://manovich.net/index.php/projects/what-is-visualization
“Human context: The first step is to understand the context of the narrative. Research shows that our brains think of companies not as objects but as people. Every time someone engages with your brand, they are asking you: “So tell me about your yourself.”
Consider the scenario of a job interview. You have the candidate’s resume, but what really matters can’t be put on paper. You want to know what inspires them, what they are like to work with, and whether they can be counted on. You want to get a sense for them as a person.“
On the importance of narratives. How to build a strategic narrative. Harvard Business Review. March 25,2016. https://hbr.org/2016/03/how-to-build-a-strategic-narrative
“Similarly, I suggest that non-‐quantitative infographics can often benefit from more overt references to the“what,”“who,” “where” elements. By quickly and almost intuitively tapping into the objects/symbols already stored in most readers heads, they are perhaps more likely to take the next step, and push on to learn more. The first obstacle immediate recognition/connection is surmounted, and deeper engagement with the more challenging details can ensue. This is a particularly salient point when dealing with complex and counterintuitive topics. The specialist reader may be equipped with a preexisting visual vocabulary that allows for immediate engagement with an illustration that aims to describe concepts in quantum mechanics or cosmology. But what about the uninitiated? Adding more cues in the form of words can help with interpretation. As Amanda Cox shows in her 2011 Eyeo presentation, annotation layers can help guide the reader, and help them understand things that they might not already see. I propose that illustrated figurative details can do the same thing, perhaps with even greater immediacy than labels. Information graphics should first and foremost convey information and honor the integrity of core content. But within the context of Scientific American, it is also critical that they engage and inspire the specialist and non-specialist reader alike. The trick lies in finding the perfect balance’’
Christiansen. J. A defense of artistic license in illustrating scientific concepts for a non-specialsits audience. In CO2: Communicating Complexity. p 49-60
“RJ: How does a project like this begin?
Fernando: The process starts with the idea. My first goal is to find the concept of the graphic. I research by myself to get some background. Then I prepare initial ideas to share with the story team. The story team usually includes: text editor, photo editor, researcher, photographer, cartographer, and video producer. We met and figured out each part of the story.
RJ:Tell me more about your process.
Fernando: When the anatomy was approved by the experts I painted each bone and organ, using a mix of pencil, sculptures and photoshop. I built clay models of the giraffe vertebrae and stomach for light and perspective reference.The art begins with a first layer of pencil and then color with photoshop.This kind of graphic—with a cutaway showing the anatomy—is pretty complicated. It needs to be easy to understand. To show the different layers it takes time to figure out the transparency, layers, colors. Sometimes I have more than 1000 layers in Photoshop. I try to give some kind of scale to readers. For that reason I put a vertebra in the background in actual size, pretty impressive size! We can do it in print but not on the web. I try to do this often in my graphics. I showed my graphic in process to my bosses and coworkers and I got comments that help me understand how the readers use the graphics. It is very helpful. Sometimes we spend a lot of time working in a graphic and we don't read the graphic like a reader.”
Andrews, R.J. Infowetrust: Dissecting the anatomy of a giant. Interview to Fernando Baptista. https://infowetrust.com/project/giraffe.
“Perhaps the best known, and most often cited aspect of Bertin’s work is his delineation of a set of fundamental graphic variables (location, size, value, texture/grain, color, orientation, and shape) and rules for their use. These variables have been analyzed, critiqued and extended by a series of authors (e.g., Spiess, 1970, Morrison 1974, MacEachren 1994a). Research directed to critique and assessment of Bertin’s graphic variables and associated application rules has focused on four questions: (1) are the variables he delineates sufficient to account for all possible graphic variations, (2) are his contentions about the appropriate application of the graphic variables correct, (3) what are the implications of combinations of variables, and (4) how, if at all, does evolution in graphic display technology change the number or characteristics of graphic variables that are considered to be “fundamental.”(…) In relation to the first question, attention has been directed primarily to aspects of color and texture (or pattern). For the latter, arrangement of elements has been proposed as a variable (MacEachren 1994a, Morrison 1974) and a distinction has been made between density of texture elements and their size (MacEachren 1995). Size of texture elements corresponds to Bertin’s “grain,” while density of elements (lines per inch) is unaccounted for in Bertin’s system. For color, most cartographers (and those in other graphic fields) recognize three attributes (hue, saturation or chroma, and lightness or value). Bertin chose to omit saturation, perhaps because he thought it less important than the others (or because existing printing technology did not enable its precise control). Saturation, however, is easily controlled independently using current computer technology and is often used to create a distinction between foreground and background information (Brewer 1992). Several authors have also pointed to the logic of using saturation (sometimes called purity of color) as a device to represent data certainty, with highly saturated colors for certain data and unsaturated, grey, washed out colors for uncertain data (MacEachren 1992, McGranaghan 1993)”
An evolving cognitive -semiotic approach visualization and knowledge construction. Information Design journal.
“Communicating thoughts, facts and narratives through visual devices such as allegory or symbolism was fundamental to early map making and this remains the case with contemporary illustration. Drawing was employed then as a way of describing historic narratives (fact and folklore) through the convenience of a drawn symbol or character. The map creators were visionaries, depicting known discoveries and anticipating what existed beyond the agreed boundaries. As we now have photographic and virtual reality maps at our disposal, how can illustration develop the language of what a map is and can be? How can we break the rules of map design and yet still communicate the idea of a sense of place with the aim to inform, excite and/or educate the ‘traveller’? As Illustrators we need to question the purpose of creating a ‘map’: what do we want to communicate and is representational image making the only way to present information of a location? Is creating a more personal interpretation a form of cartouche, reminiscent of elements within the Hereford Mappa Mundi and maps of Blaeu, and can this improve/hinder the communicative aspect of the map? Looking at a variety of historical and contemporary illustrated maps and artists (such as Grayson Perry), who track their journeys through drawing, both conventional journeys and emotional, I will aim to prove that the illustrated map is not mere decoration but is a visual language providing an allegorical response to tangible places and personal feelings. (…) Fact, feeling and fiction can coexist within the format of a map and the resulting imagery can be both entertaining and provocative. The map can also be used and subverted within other formats such as the satirical image. A map is a device that helps define groups of people and their respective cultures within a tangible graphic shape. It helps communicate ideas and views about a particular group and location and therefore enables a visual dialogue between the commentator, illustrator and viewer. A map can be employed to communicate the simplest and the most profound messages. It is not purely a decorative image that has to sit alongside text, it can communicate facts, a sense of place and understanding of geographical properties, in its own right. It can be used as a format for communicating stories, myths, legends and complex narrative structures, and it can transfer a sense of emotion to the viewer-how the illustrator felt/feels when in the place they are drawing. Maybe it is the map itself, the artwork being created, that is the place being ‘mapped’. The reader is, in turn, creating their own mind-map of the location through the process of interaction and it is this interaction between creator, created and observer that makes the map such an intriguing form for illustrators to investigate.”
Davies, A. Visualising Spaces: The illustrated map as a mode of communicating fact, fiction and feeling. 2016. VaroomLab Journal. pg 40-55.
“We must reconcile these fields as parts of a single process. Graphic designers can learn the computer science necessary for visualization, and statisticians can communicate their data more effectively by understanding the visual design principles behind data representation. The methods themselves are not new, but their isolation within individual fields has prevented them from being used together. In this book, we use a process that bridges the individual disciplines, placing the focus and consideration on how data is understood rather than on the viewpoint and tools of each individual field.
The process of understanding data begins with a set of numbers and a question. The following steps form a path to the answer:
Acquire:Obtain the data, whether from a file on a disk or a source over a network.
Parse:Provide some structure for the data’s meaning, and order it into categories.Filter:Remove all but the data of interest.
Mine: Apply methods from statistics or data mining as a way to discern patterns or place the data in mathematical context.
Represent:Choose a basic visual model, such as a bar graph, list, or tree.
Refine:Improve the basic representation to make it clearer and more visually engaging.
Interact:Add methods for manipulating the data or controlling what features are visible.
Of course, these steps can’t be followed slavishly. You can expect that they’ll be involved at one time or another in projects you develop, but sometimes it will be four of the seven, and at other times all of them.“
Fry,Ben . Visualising Data. O’Reilly Media Inc. 2007
“Como lo veremos de inmediato con mayor claridad, toda imagen es polisémica; implica, subyacente a sus significantes, una de significados, entre los cuales el lector puede elegir algunos e ignorar los otros. La polisemia da lugar a una interrogación sobre el sentido, que aparece siempre como una disfunción, aún cuando la sociedad recupere esta disfunción bajo forma de juego trágico (Dios mudo no permite elegir entre los signos) o poético (el -pánico- de los antiguos griegos). Aún en el cine, las imágenes traumáticas están ligadas a una incertidumbre (a una inquietud) acerca del sentido de los objetos o de las actitudes. Por tal motivo, en toda sociedad se desarrollan técnicas diversas destinadas a fijar la cadena flotante de los significados, de modo de combatir el terror de los signos inciertos: el mensaje lingüístico es una de esas técnicas. A nivel del mensaje literal, la palabra responde de manera, más o menos directa, más o menos parcial, a la pregunta: ¿qué es? (…) corresponde pues, a un anclaje de todos los sentidos posibles (denotados) del objeto, mediante el empleo de una nomenclatura. (…), constituye una suerte de tenaza que impide que los sentidos connotados proliferen hacia regionales demasiado individuales (es decir que limite el poder proyectivo de la imagen)”
Barthes, Roland. Retorica de la Imagen.
“In many instances, order is apprehended ﬁrst of all by the senses. The observer perceives an organized structure in the shapes and col-ors or sounds facing him. But it is hard, perhaps impossible, to ﬁnd examples in which the order of a given object or event is limited to what is directly apparent in perception. Rather, the perceivable order tends to be manifested and understood as a reﬂection of an under-lying order, whether physical, social, or cognitive. Our kinesthetic sense tells us through our muscular reactions whether a device or engine works with a smooth ordering of its parts; in fact, it informs us similarly about the perfect or imperfect functioning of our own bodies. The spatial layout of a building reﬂects and serves the distri-bution and interconnections of various functions; the groupings of the cans and packages on the shelves of a store guide the customer to the ordered varieties of household goods, and the shapes and col-ors of a painting or the sounds of a piece of music symbolize the interaction of meaningful entities.”
Arnheim, Rudolph. Entropy and Art: an essay on disorder and order. University of Califonia Press, 1971. Pg 3.
Visualizing Financial Data. Rodriguez J and Kazmareck P. Wiley Publishing. 2016. p10-12
Bertini, Enrico. Visualization in Data Science, what is it for?. NYU Polytechnic School of Engineering. 2014.
Anderson, D. R., Williams, Thomas A. and Sweeney, Dennis J. (2020, October 20). Statistics. Encyclopedia Britannica. https://www.britannica. com/science/statistics