✏️Peter Turchi - Collected Quotes

"A plot is a piece of ground, a plan (as in the plan of a building), or a scheme; to plot is to make a plan or, in geometry, to graph points on a grid. When we create a story, even a character-rather than event-based story, we make a plot or map out the narrative’s essential moments." (Peter Turchi, "Maps of the Imagination: The writer as cartographer", 2004)

"But there is also beauty in the telling detail, the provocative glimpse, the perfectly framed snapshot. The question of what to include, how much to include, can only be answered with regard to what, precisely, we mean to create. A story isn’t as utilitarian as a map of bicycle paths, but like that map, it is defined by its purpose. To serve its purpose, a story might very well be stripped down to a few spare glittering parts; alternately, it might require, or benefit from, apparently useless observations, conversations, and excursions. Perhaps the only answer is that we can’t know what needs to be in, what needs to be out, until we know what it is that we’re making, toward what end." (Peter Turchi, "Maps of the Imagination: The writer as cartographer", 2004)

"If we attempt to map the world of a story before we explore it, we are likely either to (a) prematurely limit our exploration, so as to reduce the amount of material we need to consider, or (b) explore at length but, recognizing the impossibility of taking note of everything, and having no sound basis for choosing what to include, arbitrarily omit entire realms of information. The opportunities are overwhelming." (Peter Turchi, "Maps of the Imagination: The writer as cartographer", 2004)

"Our mental maps are often not terribly accurate, based as they are on our own selective experience, our knowledge and ignorance, and the information and misinformation we gain from others; nevertheless, these are the maps we depend on every day." (Peter Turchi, "Maps of the Imagination: The writer as cartographer", 2004)

"The world of a story is not merely the sum of all the words we put on a page, or on many pages. When we talk about entering the world of a story as a reader we refer to things we picture, or imagine, and responses we form - to characters, events - all of which are prompted by, but not entirely encompassed by, the words on the page." (Peter Turchi, "Maps of the Imagination: The writer as cartographer", 2004)

"The writer’s obligation is to make rewarding both the reader’s journey and his destination." (Peter Turchi, "Maps of the Imagination: The writer as cartographer", 2004)

"There is no end to the information we can use. A 'good' map provides the information we need for a particular purpose - or the information the mapmaker wants us to have. To guide us, a map’s designers must consider more than content and projection; any single map involves hundreds of decisions about presentation." (Peter Turchi, "Maps of the Imagination: The writer as cartographer", 2004)

✏️Cole N Knaflic - Collected Quotes

"Beyond annoying our audience by trying to sound smart, we run the risk of making our audience feel dumb. In either case, this is not a good user experience for our audience." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"By combining the visual and verbal, we set ourselves up for success when it comes to triggering the formation of long-term memories in our audience." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Concentrate on the pearls, the information your audience needs to know." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Exploratory analysis is what you do to understand the data and figure out what might be noteworthy or interesting to highlight to others." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"First, to whom are you communicating? It is important to have a good understanding of who your audience is and how they perceive you. This can help you to identify common ground that will help you ensure they hear your message. Second, What do you want your audience to know or do?" (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Further develop the situation or problem by covering relevant background. Incorporate external context or comparison points. Give examples that illustrate the issue. Include data that demonstrates the problem. Articulate what will happen if no action is taken or no change is made. Discuss potential options for addressing the problem. Illustrate the benefits of your recommended solution." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Having all the information in the world at our fingertips doesn’t make it easier to communicate: it makes it harder. The more information you’re dealing with, the more difficult it is to filter." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Highlighting one aspect can make other things harder to see one word of warning in using preattentive attributes: when you highlight one point in your story, it can actually make other points harder to see. When you’re doing exploratory analysis, you should mostly avoid the use of preattentive attributes for this reason. When it comes to explanatory analysis, however, you should have a specific story you are communicating to your audience. Leverage preattentive attributes to help make that story visually clear." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"I almost always use dark grey for the graph title. This ensures that it stands out, but without the sharp contrast you get from pure black on white (rather, I preserve the use of black for a standout color when I’m not using any other colors). A number of preattentive attributes are employed to draw attention to the Progress to date trend: color, thickness of line, presence of data marker and label on the final point, and the size of the corresponding text." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"If I had to pick a single go-to graph for categorical data, it would be the horizontal bar chart, which flips the vertical version on its side. Why? Because it is extremely easy to read. The horizontal bar chart is especially useful if your category names are long, as the text is written from left to right, as most audiences read, making your graph legible for your audience." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"If you do succeed in persuading them, you’ve only done so on an intellectual basis. That’s not good enough, because people are not inspired to act by reason alone." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"If you simply present data, it’s easy for your audience to say, Oh, that’s interesting, and move on to the next thing. But if you ask for action, your audience has to make a decision whether to comply or not. This elicits a more productive reaction from your audience, which can lead to a more productive conversation - one that might never have been started if you hadn’t recommended the action in the first place." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"In the field of design, experts speak of objects having 'affordances'. These are aspects inherent to the design that make it obvious how the product is to be used. For example, a knob affords turning, a button affords pushing, and a cord affords pulling. These characteristics suggest how the object is to be interacted with or operated. When sufficient affordances are present, good design fades into the background and you don’t even notice it." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"My base color is grey, not black, to allow for greater contrast since color stands out more against grey than black. For my attention-grabbing color, I often use blue for a number of reasons: (1) I like it, (2) you avoid issues of colorblindness that we’ll discuss momentarily, and (3) it prints well in black-and-white. That said, blue is certainly not your only option (and you’ll see many examples where I deviate from my typical blue for various reasons)." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"One thing to keep in mind with a table is that you want the design to fade into the background, letting the data take center stage. Don’t let heavy borders or shading compete for attention. Instead, think of using light borders or simply white space to set apart elements of the table." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Short-term memory has limitations. Specifically, people can keep about four chunks of visual information in their short-term memory at a given time. This means that if we create a graph with ten different data series that are ten different colors with ten different shapes of data markers and a legend off to the side, we’re making our audience work very hard going back and forth between the legend and the data to decipher what they are looking at." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Sometimes bar charts are avoided because they are common. This is a mistake. Rather, bar charts should be leveraged because they are common, as this means less of a learning curve for your audience." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"[...] tables interact with our verbal system, graphs interact with our visual system, which is faster at processing information." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"The 3-minute story is exactly that: if you had only three minutes to tell your audience what they need to know, what would you say? This is a great way to ensure you are clear on and can articulate the story you want to tell." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"The unique thing you get with a pie chart is the concept of there being a whole and, thus, parts of a whole. But if the visual is difficult to read, is it worth it?" (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"There is a story in your data. But your tools don’t know what that story is. That’s where it takes you - the analyst or communicator of the information - to bring that story visually and contextually to life." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Using a table in a live presentation is rarely a good idea. As your audience reads it, you lose their ears and attention to make your point verbally." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"What do you need your audience to know or do? This is the point where you think through how to make what you communicate relevant for your audience and form a clear understanding of why they should care about what you say." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"What would a successful outcome look like? If you only had a limited amount of time or a single sentence to tell your audience what they need to know, what would you say? In particular, I find that these last two questions can lead to insightful conversation." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"When we’re at the point of communicating our analysis to our audience, we really want to be in the explanatory space, meaning you have a specific thing you want to explain, a specific story you want to tell - probably about those two pearls." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"When you have just a number or two that you want to communicate: use the numbers directly." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Will you be encountering each other for the first time through this communication, or do you have an established relationship? Do they already trust you as an expert, or do you need to work to establish credibility? These are important considerations when it comes to determining how to structure your communication and whether and when to use data, and may impact the order and flow of the overall story you aim to tell." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"You should always want your audience to know or do something. If you can't concisely articulate that, you should revisit whether you need to communicate in the first place." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

✏️Brian Suda - Collected Quotes

"A candlestick chart provides an effective overview of the highs and lows within a given period of time. It wonʼt describe every last detail of what happened between the highs and lows, or precisely when they occurred, but it does reveal a trend, something that would be near impossible in a table." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"A sin of omission – leaving something out – is a strong one and not always recognized; itʼs hard to ask for something you donʼt know is missing. When looking into the data, even before it is graphed and charted, there is potential for abuse. Simply not having all the data or the correct data before telling your story can cause problems and unhappy endings." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"An indication that the data is not statistically sound is when it is almost too precise." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"Another way to obscure the truth is to hide it with relative numbers. […] Relative scales are always given as percentages or proportions. An increase or decrease of a given percentage only tells us part of the story, however. We are missing the anchoring of absolute values." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"Be aware that bar charts provide ample opportunities for chart junk. The space within the bars is enticingly empty and it is tempting to put images or textures in the background. Some designers even swap out the standard bars for graphics." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"Colour is a very powerful way to draw attention to specific portions of the design. Colour evokes feelings and emotions, making it an essential component in branding." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"Dealing with a circular visualization and trying to compare its radial portions is always problematic. When designing with data, the story should always be told as clearly as possible. To do so, it is often best to avoid round charts and graphs." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"Good graphic design is not a panacea for bad copy, poor layout or misleading statistics. If any one of these facets are feebly executed it reflects poorly on the work overall, and this includes bad graphs and charts." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"It is tempting to make charts more engaging by introducing fancy graphics or three dimensions so they leap off the page, but doing so obscures the real data and misleads people, intentionally or not." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"One way a chart can lie is through overemphasis of the size and scale of items, particularly when the dimension of depth isnʼt considered." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"Part of the problem with using gauges and dials as alerts is that they become part of the background. If 99% of the time the needle sits in the green, the gauge isnʼt worth looking at; then that one per cent of the time when it is in the red, the gauge will go unnoticed." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"So what is the difference between a chart or graph and a visualization? […] a chart or graph is a clean and simple atomic piece; bar charts contain a short story about the data being presented. A visualization, on the other hand, seems to contain much more ʻchart junkʼ, with many sometimes complex graphics or several layers of charts and graphs. A visualization seems to be the super-set for all sorts of data-driven design." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"Sometimes itʼs better to have fewer choices and focus on the charts that best convey the story. A doughnut chart is not one of these. By removing the centre of a pie chart, it further hinders the ability to judge the weight of each segment. Moving from a healthy wedge to two arcs makes it harder for people to comprehend what value is represented. We know that a full pie chart is one hundred per cent and that any wedge is a fraction of that; if we are presented with only an arc, is it equivalent to the wedge, or is it less because it is missing a portion?" (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"The amount of information rendered in a single financial graph is easily equivalent to thousands of words of text or a page-sized table of raw values. A graph illustrates so many characteristics of data in a much smaller space than any other means. Charts also allow us to tell a story in a quick and easy way that words cannot." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"The biggest difference between line graphs and sparklines is that a sparkline is compact with no grid lines. It isnʼt meant to give precise values; rather, it should be considered just like any other word in the sentence. Its general shape acts as another term and lends additional meaning in its context. The driving forces behind these compact sparklines are speed and convenience." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"Using colour, itʼs possible to increase the density of information even further. A single colour can be used to represent two variables simultaneously. The difficulty, however, is that there is a limited amount of information that can be packed into colour without confusion." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

IT: Privacy (Just the Quotes)

"The personal life of every individual is based on secrecy, and perhaps it is partly for that reason that civilized man is so nervously anxious that personal privacy should be respected." (Anton Chekhov, "A Doctor's Visit", 1898)

"Solitude and privacy have become more essential to the individual; but modern enterprise and invention have, through invasions upon his privacy, subjected him to mental pain and distress." (Samuel D Warren, "The Development of the Right of Privacy in New York", 1954)

"The fantastic advances in the field of electronic communication constitute a greater danger to the privacy of the individual." (Earl Warren, "Concurring in the judgment, Lopez v. United States 373 U.S. 427", 1963)

"Complete and accurate surveillance as a means of control is probably a practical impossibility. What is much more likely is a loss of privacy and constant inconvenience as the wrong people gain access to information, as one wastes time convincing the inquisitors that one is in fact innocent, or as one struggles to untangle the errors of the errant machine." (Victor C Ferkiss, "Technological Man: The Myth and the Reality", 1969)

"Privacy invasion is now one of biggest knowledge industries." (Marshall McLuhan, "Culture Is Our Business", 1970)

"Privacy - like eating and breathing - is one of life's basic requirements." (Katherine Neville, "A Calculated Risk: A Novel", 1992)

"If machines knew as much about each other as we know about each other (even in our privacy), the ecology of machines would be indomitable." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995) 

"Privacy is a type of conversation. Firms should view privacy not as some inconvenient obsession of customers that must be snuck around but more as a way to cultivate a genuine relationship." (Kevin Kelly, "New Rules for the New Economy: 10 radical strategies for a connected world", 1998)

"The first form of semantic data on the Web was metadata information about information. (There happens to be a company called Metadata, but I use the term here as a generic noun, as it has been used for many years.) Metadata consist of a set of properties of a document. By definition, metadata are data, as well as data about data. They describe catalogue information about who wrote Web pages and what they are about; information about how Web pages fit together and relate to each other as versions; translations, and reformattings; and social information such as distribution rights and privacy codes." (Tim Berners-Lee, "Weaving the Web", 1999)

"Privacy is not a static construct. It is not an inherent property of any particular information or setting. It is a process by which people seek to have control over a social situation by managing impressions, information flows, and context." (Danah Boyd, "It's Complicated: The Social Lives of Networked Teens", 2014)

"Arguing that you don't care about the right to privacy because you have nothing to hide is no different than saying you don't care about free speech because you have nothing to say." (Edward Snowden, 2015)

"Data governance policies must not enforce constraints on data - Data governance intends to control the level of democracy within the data lake. Its sole purpose of existence is to maintain the quality level through audits, compliance, and timely checks. Data flow, either by its size or quality, must not be constrained through governance norms. [...] Effective data governance elevates confidence in data lake quality and stability, which is a critical factor to data lake success story. Data compliance, data sharing, risk and privacy evaluation, access management, and data security are all factors that impact regulation." (Saurabh Gupta et al, "Practical Enterprise Data Lake Insights", 2018)

"Metadata is the key to effective data governance. Metadata in this context is the data that defines the structure and attributes of data. This could mean data types, data privacy attributes, scale, and precision. In general, quality of data is directly proportional to the amount and depth of metadata provided. Without metadata, consumers will have to depend on other sources and mechanisms." (Saurabh Gupta et al, "Practical Enterprise Data Lake Insights", 2018)

"Data privacy, data confidentiality, and data protection are sometimes incorrectly diluted with security. For example, data privacy is related to, but not the same as, data security. Data security is concerned with assuring the confidentiality, integrity, and availability of data. Data privacy focuses on how and to what extent businesses may collect and process information about individuals." (Bill Inmon et al, "Building the Data Lakehouse", 2021)

✏️Allan C Haskell - Collected Quotes

"All charts should be given a comprehensive title, that there may be no doubt as to what data the chart is intended to cover. This is especially necessary in connection with separate exhibits used for illustrating statements in special reports, as when the charts are not given distinct titles they are valueless as records when detached from the reports." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"An exact knowledge of conditions, and consequent timely application of praise or of constructive criticism, is one of the chief forces of the executive in securing satisfactory results. Undeserved criticism is unjust and destroys-initiative, while unmerited praise tends to render the executive ridiculous in the eyes of his subordinates; both are detrimental to discipline and weaken the power of the executive." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"At the time a chart is drawn explanatory notes should be used unsparingly and all curves or diagrams should be so keyed or lettered that there will be no question as to just what each represents when the chart is referred to later. When it is not necessary to make blue-prints, different colored inks or water-color paints may be used in a drawing-pen to distinguish one curve from another [...]" (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Every business has its own particular sort of rat holes, through which its profits are carried piecemeal, and in quantities hardly noticeable at the time, but which aggregate thousands every year. The best way to plug these sources of loss is by accumulating data in regard to them and then keeping this data prominently before the executive."  (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Failure to succeed greatly in management usually occurs not so much from lack of knowledge of the important principles of the science of management as from failure to apply them. Most of the principles of successful management are old, and many of them have received sufficient publicity to be well known, but managers are curiously prone to look upon managerial success as a personal attribute that is slightly dependent on principles or laws." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"For any manager to utilize graphic methods for visualizing the vital facts of his business, in the first place it must be impressed upon his that the method will produce the results for him and then he must know how to get up a chart correctly, and last, but far from least, he must know what the essential facts of his business are. Charts, in themselves, mean little and like many another force for the accomplishment of good, if misdirected, may result unprofitably." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Generally speaking, the plotting of a curve consists of graphically representing numbers and equations by the relation of points and lines with reference to other given lines or to a given point." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Graphic methods convey to the mind a more comprehensive grasp of essential features than do written reports, because one can naturally gather interesting details from a picture in far less time than from a written description. Further than this, the examination of a picture allows one to make deductions of his own, while in the case of a written description the reader must, to a great degree, accept the conclusions of the author." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Graphic representation by means of charts depends upon the super-position of special lines or curves upon base lines drawn or ruled in a standard manner. For the economic construction of these charts as well as their correct use it is necessary that the standard rulings be correctly designed." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"In working through graphics one has, however, to be exceedingly cautious in certain particulars, for instance, when a set of figures, dynamical or financial, are available they are, so long as they are tabulated, instinctively taken merely at their face value. When plotted, however, there is a temptation to extrapolation which is well nigh irresistible to the untrained mind. Sometimes the process can be safely employed, but it requires a rather comprehensive knowledge of the facts that lie back of the data to tell when to go ahead and when to stop." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"It is not possible to lay down any hard and fast rules for determining what chart is the best for any given problem. Ordinarily that one is the best which will produce the quickest and clearest results. but unfortunately it is not always possible to construct the clearest one in the least time. Experience is the best guide. Generally speaking, a rectilinear chart is best adapted for equations of the first degree, logarithmic for those other than the first degree and not containing over two variables, and alignment charts where there are three or more variables. However, nearly every person becomes more or less familiar with one type of chart and prefers to adhere to the use of that type because he does not care to take the time and trouble to find out how to use the others. It is best to know what the possibilities of all types are and to be governed accordingly when selecting one or the other for presenting or working out certain data." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Many people imagine that graphic charts cannot be understood except by expert mathematicians who have devoted years of study to the subject. This is a mistaken idea, and if instead of passing over charts as if they were something beyond their comprehension more people would make an effort to read them, much valuable time would be saved. It is true that some charts covering technical data are difficult even for an expert mathematician to understand, but this is more often the fault of the person preparing the charts than of the system." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Nothing is so illuminating as a set of properly proportioned diagrams. [...] In addition to the significance of graphics in analytical work, it is likewise a valuable aid to the memory. A picture is manifestly more readily retained in mind than a description of the same subject, no matter how vividly it may have been expressed. A pictorial or diagrammatic illustration usually produces a firmer and more lasting impression than any composition of words or tabulation of figures, however well they may be arranged or set forth." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"One of the most valuable uses to which charts may be put is that of analysis - the analytical study of facts which many times do not adhere to any known mathematical law, but which are nevertheless capable of being reduced to a workable form." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Since a table is a collection of certain sets of data, a chart with one curve representing each set of data can be made to take the place of the table. Wherever a chart can be plotted by straight lines, the speed of this is infinitely greater than making out a table, and where the curvilinear law is known, or can be approximated by the use of the empiric law, the speed is but little less." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"The best-known function of charts is for demonstration purposes, to show up facts. When so presented they do not require a trained mind for their appreciation, since the spatial sense through the optic nerve is among the commonest of the human attributes." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"The practice of drawing several curves on the same sheet is not to be commended except in cases where the curves will not intersect. A crowded chart on which the curves frequently intersect resembles a Chinese puzzle more than a graphic record, and a report submitted in figures is to be preferred to a chart of this kind. Even when the curves do not intersect, they should be made in different colors in order that they may be readily distinguished, one from the other." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"The problem of the executive, then - once his organization is perfected - is to secure live data covering the exact conditions of the business at all times. These data should be arranged so as to give him all the facts, subordinated according to their relative bearing upon net earnings, and do so with the least demand upon his time. Furthermore, these facts must be so exhibited that the general laws underlying the business may be easily and accurately deduced and standards of accomplishment set which will be a continual incentive to greater accomplishment." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"The zero of the scale should appear on every chart, and should shown by a heavy line carried across the sheet. If this is not done the reader may assume the bottom of the sheet to be zero and so be misled. The scale should be graduated from zero to a little over the maximum figure to be plotted on the charts, so that there will be a space between the highest peak on the curve and the top of the chart." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Under certain conditions, however, the ordinary form of graphic chart is slightly misleading. It will be conceded that its true function is to portray comparative fluctuations. This result is practically secured when the factors or quantities compared are nearly of the same value or volume, but analysis will show that this is not accomplished when the amounts compared differ greatly in value or volume. [...] The same criticism applies to charts which employ or more scales for various curve. If the different scale are in proper proportion, the result is the same as with one scale, but when two or more scales are used which are not proportional an indication may be given with respect to comparative fluctuations which is absolutely false." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"When dealing with very large quantities it is not always practicable to use a scale which starts at zero, and is carried up by even steps to a figure representing the highest peak on the curve. Such a chart would either be too large for convenient handling, or else the scale would have to be condensed so that only very large fluctuations would be indicated on the curve. In a ease of this kind the best practice is to start the at zero, and just above this point draw a wavy line across the sheet to indicate that the scale is broken at this point. This line can be very easily drawn with an ordinary serrated edge ruler as used by many accountants. The scale starts again on the upper side of the wavy line at a figure a little lower than the lowest point on the curve, and is carried up by even steps to a figure a little above the highest point to be shown on the curve." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Wherever unusual peaks or valleys occur on a curve it is a good plan to mark these points with a small figure inside a circle. This figure should refer to a note on the back of the chart explaining the reason for the unusual condition. It is not always sufficient to show that a certain item is unusually high or low; the executive will want to know why it is that way." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"With the ordinary scale, fluctuations in large factors are very noticeable, while relatively greater fluctuations in smaller factors are barely apparent. The semi-logarithmic scale permits the graphic representation of changes in every quantity on the same basis, without respect to the magnitude of the quantity itself. At the same time, it shows the actual value by reference to the numbers in the scale column. By indicating both absolute and relative value and changes to one scale, it combines the advantages of both the natural and percentage scale, without the disadvantages of either." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

✏️Robert Lefferts - Collected Quotes

"A flow chart is a graphic method to show pictorially how a series of activities, procedures. operations. events. ideas, or other factors are related to each other. It shows the sequence, cycle. or flow of these factors and how they are connected in a series of steps from beginning to end." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"A good graphic must give the impression that its various parts all belong together. They must be arranged in such a way that the illustration looks like a single entity. A good graphic chart should be more than just the sum of its individual lines, shapes, and shades. It should be more than the individual bars in a bar chart, more than the pieces of a pie chart, more than the boxes in a flow chart. Unity requires the establishment of coherent relationships among the component parts of the drawing. These relationships can be depicted in a very direct manner through the use of connecting lines that serve to connect shapes." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"A graphic is an illustration that, like a painting or drawing, depicts certain images on a flat surface. The graphic depends on the use of lines and shapes or symbols to represent numbers and ideas and show comparisons, trends, and relationships. The success of the graphic depends on the extent to which this representation is transmitted in a clear and interesting manner." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"A pie chart is comprised of a circle that is divided into segments by straight lines within the circle. The circle represents the total or whole amount. Each segment or wedge of the circle represents the proportion that a particular factor is of the total or whole amount. Thus, a pie chart in its entirety always represents whole amounts of either 100% or a total absolute number, such as 100 cents or 5,000 people. All of the segments of the pie when taken together (that is, in the aggregate) must add up to the total." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"An organization chart is a graphic device that uses pictorial methods to show qualitative information about an organization. [...] The organization chart can be used to show one or more of three things: (1) What the various staff positions in the organization are, how they are structurally related to each other and the span of control and chain of command within the organization. (2) What the different units of the organization are and how they are arranged and related to each other. (3) What the various functions are within the organization and how they are organized and related." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"For most line charts the maximum number of plotted lines should not exceed five; three or fewer is the ideal number. When multiple plotted lines are shown each line should be differentiated by using (a) a different type of line and/or (b) different plotting marks, if shown, and (c) clearly differentiated labeling." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Graphic charts are ways of presenting quantitative as well as qualitative information in an efficient and effective visual form. Numbers and ideas presented graphically are often more easily understood. remembered. and integrated than when they are presented in narrative or tabular form. Descriptions. trends. relationships, and comparisons can be made more apparent. Less time is required to present and comprehend information when graphic methods are employed. As the old truism states, 'One picture is worth a thousand words.'" (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Graphic forms help us to perform and influence two critical functions of the mind: the gathering of information and the processing of that information. Graphs and charts are ways to increase the effectiveness and the efficiency of transmitting information in a way that enhances the reader's ability to process that information. Graphics are tools to help give meaning to information because they go beyond the provision of information and show relationships, trends, and comparisons. They help to distinguish which numbers and which ideas are more important than others in a presentation." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"If you want to dramatize comparisons in relation to the whole. use a pie chart. If you want to add coherence to the narrative, the pie chart also helps because it depicts a whole. If your main interest is in stressing the relationship of one factor to another, use bar charts. If you wish to achieve all these effects. you can use either type of chart. and decide on the basis of which one is more aesthetically or pictorially interesting." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"It should be noted that graphics for the purpose of clarity should not be a substitute for words and numbers in the narrative text. The graphics presentation is used to supplement the narrative; otherwise. there wouldn't be anything to clarify." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Some believe that the vertical bar should be used when comparing similar items for different time periods and the horizontal bar for comparing different items for the same time period. However, most people find the vertical-bar format easier to prepare and read. and a more effective way to show most types of comparisons." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

 "The bar or column chart is the easiest type of graphic to prepare and use in reports. It employs a simple form: four straight lines that are joined to construct a rectangle or oblong box. When the box is shown horizontally it is called a bar; when it is shown vertically it is called a column. [...] The bar chart is an effective way to show comparisons between or among two or more items. It has the added advantage of being easily understood by readers who have little or no background in statistics and who are not accustomed to reading complex tables or charts." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"The more complex the shape of any object. the more difficult it is to perceive it. The nature of thought based on the visual apprehension of objective forms suggests, therefore, the necessity to keep all graphics as simple as possible. Otherwise, their meaning will be lost or ambiguous, and the ability to convey the intended information and to persuade will be inhibited." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"The preparation of well-designed graphics is both an art and a skill. There are many different ways to go about the task, and readers are urged to develop their own approaches. Graphics can be creative and fun. At the same time, they require a degree of orderly and systematic work." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"To see is to reason. Thus, the use of visual forms of communication has great potential for influencing what a person thinks. Graphic presentation is always much more than a way to present just facts or information. Rather, it is a way to influence thought, and, as such, graphics can be a powerful mode of persuasion." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Understanding is accomplished through: (a) the use of relative size of the shapes used in the graphic; (b) the positioning of the graphic-line forms; (c) shading; (d) the use of scales of measurement; and (e) the use of words to label the forms in the graphic. In addition. in order for a person to attach meaning to a graphic it must also be simple, clear, and appropriate." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Unlike some art forms. good graphics should be as concrete. geometrical, and representational as possible. A rectangle should be drawn as a rectangle, leaving nothing to the reader's imagination about what you are trying to portray. The various lines and shapes used in a graphic chart should be arranged so that it appears to be balanced. This balance is a result of the placement of shapes and lines in an orderly fashion." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

✏️Dyno Lowenstein - Collected Quotes

"A pie graph is a circle that is divided into wedges, like slices of a pie. It is particularly useful when statistics show as a half or a quarter of a total. The human eye can recognize half of a circle much more easily than half a length of a bar." (Dyno Lowenstein, "Graphs", 1976)

"Just like the spoken or written word, statistics and graphs can lie. They can lie by not telling the full story. They can lead to wrong conclusions by omitting some of the important facts. [...] Always look at statistics with a critical eye, and you will not be the victim of misleading information." (Dyno Lowenstein, "Graphs", 1976)

"Learning to make graphs involves two things: (l) the techniques of plotting statistics, which might be called the artist's job; and (2) understanding the statistics. When you know how to work out graphs, all kinds of statistics will probably become more interesting to you." (Dyno Lowenstein, "Graphs", 1976)

 "What you may call a graph, someone else may call a chart, for both terms are used for the same thing. Actually, however. the word 'chart' was originally used only for navigation maps and diagrams. Most people agree that it is best to leave the term '*chart" to the navigators." (Dyno Lowenstein, "Graphs", 1976)

✏️Rufus R Lutz - Collected Quotes

"A type of error common in both simple and weighted averages is the inclusion of components which have no bearing on or merely distort the summarization. Errors of this kind are frequent in per capita estimates covering the total population."  (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

"An important rule in the drafting of curve charts is that the amount scale should begin at zero. In comparisons of size the omission of the zero base, unless clearly indicated, is likely to give a misleading impression of the relative values and trend." (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

"Averages and percents should not be averaged. The procedure for obtaining a true average of a number of averages or percents is the same as that for the weighted average. The basic values and com- ponent figures from which the individual averages or percents are derived are totaled. The true average is the quotient of the value total divided by the component total." (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

"Charts to be shown with a public address should be extremely simple in design. Colors, shading, and curve patterns designating components and categories should be chosen with an eye to strong contrasts. It is essential that the meaning and purpose of the chart be obvious at a glance. If they are not, the attention of the audience is divided between deciphering the chart and listening to what the speaker has to say about it." (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

"Column charts are bar charts arranged vertically. Their most frequent use is for picturing com- parisons of similar components at different times, while bar charts are generally employed to compare different components at the same time. The column design is particularly effective for the presentation of series which comprise a small number of time periods with few subdivisions of value. It is not well suited for comparisons of several time series nor for those which cover an extended period of time and have many plottings."  (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

"If a chart contains a number of series which vary widely in individual magnitude, optical distortion may result from the necessarily sharp changes in the angle of the curves. The space between steeply rising or falling curves always appears narrower than the vertical distance between the plotting points." (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

"The grid lines should be lighter than the curves, with the base line somewhat heavier than the others. All vertical lines should be of equal weight, unless the time scale is subdivided in quarters or other time periods, indicated by heavier rules. Very wide base lines, sometimes employed for pictorial effect, distort the graphic impression by making the base line the most prominent feature of the chart." (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

"The use of two or more amount scales for comparisons of series in which the units are unlike and, therefore, not comparable [...] generally results in an ineffective and confusing presentation which is difficult to understand and to interpret. Comparisons of this nature can be much more clearly shown by reducing the components to a comparable basis as percentages or index numbers." (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

"There is probably a higher percentage of errors in the drafting of circle charts than is found in any of the other graphic types, chiefly because of the complicated procedure for calculating the diameters of circles." (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

✏️Steve Wexler - Collected Quotes

"A dashboard is a visual display of data used to monitor conditions and/or facilitate understanding. (Steve Wexler et al, "The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios", 2017)

"A good test of how effective your data visualizations are: can you remove all or most of the numbers and still understand the visualization and make comparisons?" (Steve Wexler, "The Big Picture: How to use data visualization to make better decisions - faster", 2021)

"A good visualization can do more than just answer questions; it can help you see that there are other questions you need to answer." (Steve Wexler, "The Big Picture: How to use data visualization to make better decisions - faster", 2021)

"Data visualization isn’t just about informing, it’s also about persuading." (Steve Wexler, "The Big Picture: How to use data visualization to make better decisions - faster", 2021)

"Most organizations are drowning in data but are thirsty for understanding." (Steve Wexler, "The Big Picture: How to use data visualization to make better decisions - faster", 2021)

"The best way to engage people and drive adoption is to provide something useful and meaningful, and one of the best ways to do this is to make it personal." (Steve Wexler, "The Big Picture: How to use data visualization to make better decisions - faster", 2021)

"The goal of using data visualization to make better and faster decisions may lead people to think that any data visualization that is not immediately understood is a failure. Yes, a good visualization should allow you to see things that you might have missed, and to glean insights faster, but you still have to think." (Steve Wexler, "The Big Picture: How to use data visualization to make better decisions - faster", 2021)

"The problem is that a pie chart does one thing well, and most people don’t use it for that one thing. Specifically, they’re great at giving you a fast and accurate estimate of the part-to-whole relationship for two of the slices. Other than that, pie charts are terrible. [...] The same strengths and shortcomings that apply to the pie chart also apply to the donut chart." (Steve Wexler, "The Big Picture: How to use data visualization to make better decisions - faster", 2021)

"What is the secret to getting people to use charts and dashboards? Personalization. Inserting the audience into the visualization, and making it especially meaningful and relevant to the user, never fails." (Steve Wexler, "The Big Picture: How to use data visualization to make better decisions - faster", 2021)

"A dashboard is not a good place to tell a story. But it's a great place to find a story worth telling!" (Steve Wexler) [in media]

✏️Joel Katz - Collected Quotes

"By understanding why things don’t work, you can figure out how to design them so that they do." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012) 

"Color can modify - and possibly even contradict - our intuitive response to value, because of its own powerful connotations." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012)

"If the user can’t understand it, the design and the designer have failed." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012)

"Information design, when successful - whether in print, on the web, or in the environment - represents the functional balance of the meaning of the information, the skills and inclinations of the designer, and the perceptions, education, experience, and needs of the audience." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012)

"Geographic maps have the advantage of being true to scale - great for walking. Diagrams have the advantage of being easily imaged and remembered, often true to a non-pedestrian experience, and the ability to open up congestion, reduce empty space, and use real estate efficiently. Hybrids 'mapograms' ? - often have the disadvantages of both map and diagram with none of the corresponding advantages." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012) 

"Many concepts and relationships are difficult to grasp because of enormous or microscopic sizes and distances or because of huge disparities of scale. Representing these things with objects with which we have all had experience is a way to start working on the problem." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012)

"Notational complexity almost always results in informational inefficiency." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012) 

"Successful information design in movement systems gives the user the information he needs - and only the information he needs - at every decision point." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012) 

"The more dimensions used in quantitative comparisons, the larger are the disparities that can be accommodated. As irony would have it, however, the ease of comparison generally diminishes in direct proportion to the number of dimensions involved." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012) 

"The universal intelligibility of a pictogram is inversely proportional to its complexity and potential for interpretive ambiguity." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012) 

"Use the form that most clearly connotes the differentiations within the data to be visualized; avoid forms that intuitively contradict the data." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012) 

"Violating established and functional color conventions makes it more difficult for the audience to understand an information graphic or a map. Respecting them gives the user that much less on which to expend unnecessary energy." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012) 

✏️Walter E Weld - Collected Quotes

"'A chart is a graphic presentation of numerical data'. In other words, a chart is a picture of a set of figures, but a picture the making and understanding of which calls for neither artistic nor mathematical skill. The only requirements arc ordinary common sense and the ability to draw a straight line with the aid of a ruler." (Walter E Weld, "How to Chart; Facts from Figures with Graphs", 1959)

"A time series is a record of the magnitude of a variable (a quantity that may increase or decrease) as observed at regular intervals of time." (Walter E Weld, "How to Chart; Facts from Figures with Graphs", 1959)

"According to the standard definition, a chart is a graphic presentation, or picture, of numerical data, and since numerical data invariably record magnitudes, that is, the measurements of various things, it follows that a graphic chart, in its simplest form, is a picture of the size of something as expressed in the standard unit of measurement." (Walter E Weld, "How to Chart; Facts from Figures with Graphs", 1959)

"Besides being easier to construct than a bar chart, the line chart possesses other advantages. It is easier to read, for while the bars stand out more prominently than the line, they tend to become confusing if numerous, and especially so when they record alternate increase and decrease. It is easier for the eye to follow a line across the face of the chart than to jump from bar top to bar top, and the slope of the line connecting two points is a great aid in detecting minor changes. The line is also more suggestive of movement than arc bars, and movement is the very essence of a time series. Again, a line chart permits showing two or more related variables on the same chart, or the same variable over two or more corresponding periods." (Walter E Weld, "How to Chart; Facts from Figures with Graphs", 1959)

"Business executives, to be efficient, must constantly plan ahead, but there are pitfalls in attempting to estimate the future growth of a business from a chart of its past history. In the first place, there are too many uncontrollable factors entering into the situation to make the most careful estimate of future growth anything more than a shrewd guess, dependent upon all internal and external conditions remaining the same. To project the growth curve of a business into the future provides a good mark to shoot at, but a bank loan is seldom obtainable on the strength of such a projection."  (Walter E Weld, "How to Chart; Facts from Figures with Graphs", 1959)

"But while charts are always useful and often necessary, they can never be anything more than a means to an end. Let no executive assume that charts, however numerous or complete, can ever serve as an effective substitute for managerial ability or personal effort. No manner or number of charts will enable an incompetent person to run a business successfully, nor insure the efficiency of remote control by even the most competent management. Charts are a help to, not a substitute for executive ability." (Walter E Weld, "How to Chart; Facts from Figures with Graphs", 1959)

"In form, the ratio chart differs from the arithmetic chart in that the vertical scale is not divided into equal spaces to represent equal amounts, but is divided logarithmically to represent percentages of gain or loss. On the arithmetic chart equal vertical distances represent equal amounts of change; on the ratio chart equal vertical distances represent equal percentages of change." (Walter E Weld, "How to Chart; Facts from Figures with Graphs", 1959)

"The great trouble with all business data upon which the statisticians and economists base their forecasts is that they are ancient history before they ever become available. They pertain to conditions which existed some weeks or months previous. The figures for what is going on at the moment in all lines of business are never available. A business index, while of great interest and value, is always historical and never predictive." (Walter E Weld, "How to Chart; Facts from Figures with Graphs", 1959)

"The probability chart, as its name indicates, not only presents a record of what has occurred in the past, but furnishes a sound and scientific basis for estimating what is likely to hap- pen in the future, providing things take their normal course. This is far better than any mere guess or rough estimate, especially in all unprecedented cases." (Walter E Weld, "How to Chart; Facts from Figures with Graphs", 1959)

✏️Michael Friendly - Collected Quotes

"Like good writing, producing an effective graphical display requires an understanding of purpose - what is to be communicated, and to whom." (Michael Friendly, "Gallery of Data Visualization", 1991)

"It is common to think of statistical graphics and data visualization as relatively modern developments in statistics. In fact, the graphic representation of quantitative information has deep roots. These roots reach into the histories of the earliest map-making and visual depiction, and later into thematic cartography, statistics and statistical graphics, medicine, and other fields. Along the way, developments in technologies (printing, reproduction) mathematical theory and practice, and empirical observation and recording, enabled the wider use of graphics and new advances in form and content." (Michael Friendly. "A brief history of data visualization", 2006)

"The graphic portrayal of quantitative information has deep roots. These roots reach into histories of thematic cartography, statistical graphics, and data visualization, which are intertwined with each other." (Michael Friendly. "Milestones in the history of thematic cartography, statistical graphics, and data visualization", 2008) 

"Algorithmic calculation can give only pseudo-random numbers, but some methods come closer than others in behaving like quantities that are truly random, such as numbers obtained from tossing a very large number of dice." (Michael Friendly. "Milestones in the history of thematic cartography, statistical graphics, and data visualization", 2008) 

"But to a ballet dancer, the art is in getting all the body parts to do those things in sync with a musical score to tell a wordless story of emotion entirely through change in position over time. In data visualization, as in physics and ballet, motion is a manifestation of the relation between time and space, and so the recording and display of motion added time as a fourth dimension to the abstract world of data." (Michael Friendly. "Milestones in the history of thematic cartography, statistical graphics, and data visualization", 2008) 

"Correlation does not imply causation: often some other missing third variable is influencing both of the variables you are correlating. […] The need for a scatterplot arose when scientists had to examine bivariate relations between distinct variables directly. As opposed to other graphic forms - pie charts, line graphs, and bar charts - the scatterplot offered a unique advantage: the possibility to discover regularity in empirical data (shown as points) by adding smoothed lines or curves designed to pass 'not through, but among them', so as to pass from raw data to a theory-based description, analysis, and understanding." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"However, just as in cooking, the details matter: the wrong spice can ruin the stew. In graphing data, different methods or graphical features can make it easier or harder to perceive and understand relationships or comparisons from the same data." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"Indeed, among all forms of statistical graphics, the scatterplot may be considered the most versatile and generally useful invention in the entire history of statistical graphics. Essential characteristics of a scatterplot are that two quantitative variables are measured on the same observational units (workers); the values are plotted as points referred to perpendicular axes; and the goal is to show something about the relation between these variables, typically how the ordinate variable, y, varies with the abscissa variable, x." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"Its primary function was to make previously invisible phenomena subject to direct inspection in a graphic display […] The graphic method had another function, that of communication to the scientific community and educated readers. These displays made complex phenomena palpable and concrete." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"Our central questions in this book are 'How did the graphic depiction of numbers arise?' and more importantly, 'Why?' What led to the key innovations in graphs and diagrams that are commonplace today? What were the circumstances or scientific problems that made visual depiction more useful than mere words and numbers? Finally, how did these graphic inventions make a difference in comprehending natural and social phenomena and communicating that understanding?" (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"[...] scatterplots had advantages over earlier graphic forms: the ability to see clusters, patterns, trends, and relations in a cloud of points. Perhaps most importantly, it allowed the addition of visual annotations (point symbols, lines, curves, enclosing contours, etc.) to make those relationships more coherent and tell more nuanced stories." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"The general principles of starting with a well-defined question, engaging in careful observation, and then formulating hypotheses and assessing the strength of evidence for and against them became known as the scientific method." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"The plotting of real data had a remarkable, and largely unanticipated, benefit. It often forced viewers to see what they hadn’t expected. The frequency with which this happened gave birth to the empirical modern approach to science which welcomes the plotting of observed data values with the goal of investigating suggestive patterns." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"Visual displays of empirical information are too often thought to be just compact summaries that, at their best, can clarify a muddled situation. This is partially true, as far as it goes, but it omits the magic. […] sometimes, albeit too rarely, the combination of critical questions addressed by important data and illuminated by evocative displays can achieve a transcendent, and often wholly unexpected, result. At their best, visualizations can communicate emotions and feelings in addition to cold, hard facts."  (Michael Friendly. "Milestones in the history of thematic cartography, statistical graphics, and data visualization", 2008) 

"We are accustomed to intellectual diffusion taking place from the natural and physical sciences into the social sciences; certainly that is the direction taken for both calculus and the scientific method. But statistical graphics in particular, and statistics in general, took the reverse route." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"We live on islands surrounded by seas of data. Some call it 'big data'. In these seas live various species of observable phenomena. Ideas, hypotheses, explanations, and graphics also roam in the seas of data and can clarify the waters or allow unsupported species to die. These creatures thrive on visual explanation and scientific proof. Over time new varieties of graphical species arise, prompted by new problems and inner visions of the fishers in the seas of data." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

✏️William Playfair - Collected Quotes

"As knowledge increases amongst mankind and transactions multiply, it becomes more and more desirable to abbreviate and facilitate the modes of conveying information from one person to another, and from one individual to the many." (William Playfair, "The Commercial and Political Atlas", 1786)

"As to the propriety and justness of representing sums of money, and time, by parts of space, tho’ very readily agreed to by most men, yet a few seem to apprehend there may possibly be some deception in it, of which they are not aware […]" (William Playfair, "The Commercial and Political Atlas", 1786)

"Figures and letters may express with accuracy, but they can never represent either number or space. A map of the river Thames, or of a large town, expressed in figures, would give but a very imperfect notion of either, though they might be perfectly exact in every dimension." (William Playfair, "The Commercial and Political Atlas", 1786)

"Geography is only a branch of statistics, a knowledge of which is necessary to the well-understanding of the history of nations, as well as their situations relative to each other." (William Playfair, "The Commercial and Political Atlas", 1786)

"Information that is imperfectly acquired, is generally as imperfectly retained; and a man who has carefully investigated a printed table, finds, when done, that he has only a very faint and partial idea of what he has read; and that like a figure imprinted on sand, is soon totally erased and defaced." (William Playfair, "The Commercial and Political Atlas", 1786)

"It remains only for me to request that those who do not, at the first sight, understand the manner of inspecting the Charts, will read with attention the few lines of directions facing the first Chart, after which they will find all the difficulty entirely vanish, and as much information may be obtained in five minutes as would require whole days to imprint on the memory, in a lasting manner, by a table of figures." (William Playfair, "The Commercial and Political Atlas", 1786)

"Men in general are very slow to enter into what is reckoned a new thing; and there seems to be a very universal as well as great reluctance to undergo the drudgery of acquiring information that seems not to be absolutely necessary." (William Playfair, "The Commercial and Political Atlas", 1786) 

"[...] the eye is the best judge of proportion, being able to estimate it with more quickness and accuracy than any other of our organs [...] this mode of representation gives a simple, accurate, and permanent idea, by giving form and shape to a number of separate ideas, which are otherwise abstract and unconnected." (William Playfair, "The Commercial and Political Atlas", 1786)

"This Chart is different from the others in principle, as it does not comprehend any portion of time, and it is much inferior in utility to those that do; for though it gives the extent of the different branches of trade, it does not compare the same branch of commerce with itself at different periods; nor does it imprint upon the mind that distinct idea, in doing which, the chief advantage of Charts consists: for as it wants the dimension that is formed by duration, there is no shape given to the quantities." (William Playfair, "The Commercial and Political Atlas", 1786)

"To give insight to statistical information it occurred to me, that making an appeal to the eye when proportion and magnitude are concerned, is the best and readiest method of conveying a distinct idea." (William Playfair, "The Commercial and Political Atlas", 1786)

"In the course of executing that design, it occurred to me that tables are by no means a good form for conveying such information. [...] Making an appeal to the eye when proportion and magnitude are concerned is the best and readiest method of conveying a distinct idea." (William Playfair, "The Statistical Brewery", 1801)

"No study is less alluring or more dry and tedious than statistics, unless the mind and imagination are set to work, or that the person studying is particularly interested in the subject; which last can seldom be the case with young men in any rank of life." (William Playfair, "The Statistical Brewery", 1801)

"Statistical accounts are to be referred to as a dictionary by men of riper years, and by young men as a grammar, to teach them the relations and proportions of different statistical subjects, and to imprint them on the mind at a time when the memory is capable of being impressed in a lasting and durable manner, thereby laying the foundation for accurate and valuable knowledge." " (William Playfair, "The Statistical Brewery", 1801)

"Statistical knowledge, though in some degree searched after in the most early ages of the world, has not till within these last 50 years become a regular object of study." (William Playfair, "The Statistical Brewery", 1801)

"The advantages proposed by [the graphical] mode of representation, are to facilitate the attainment of information, and aid the memory in retaining it: which two points form the principal business in what we call learning. Of all the senses, the eye gives the liveliest and most accurate idea of whatever is susceptible of being represented to it; and when proportion between different quantities is the object, then the eye has an incalculable superiority. (William Playfair, "The Statistical Breviary", 1801)

"No study is less alluring or more dry and tedious than statistics, unless the mind and imagination are set to work, or that the person studying is particularly interested in the subject; which last can seldom be the case with young men in any rank of life." (William Playfair, "The Statistical Brewery", 1801)

"Regarding numbers and proportions, the best way to catch the imagination is to speak to the eyes." (William Playfair, "Elemens de statistique", 1802)

✏️Robert Grant - Collected Quotes

"A map by itself requires little explanation, but once data are superimposed, readers will probably need labels on the maps, and legends explaining encodings like the color of markers." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"A recurring theme in machine learning is combining predictions across multiple models. There are techniques called bagging and boosting which seek to tweak the data and fit many estimates to it. Averaging across these can give a better prediction than any one model on its own. But here a serious problem arises: it is then very hard to explain what the model is (often referred to as a 'black box'). It is now a mixture of many, perhaps a thousand or more, models." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"Any fool can fit a statistical model, given the data and some software. The real challenge is to decide whether it actually fits the data adequately. It might be the best that can be obtained, but still not good enough to use." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"Apart from the technical challenge of working with the data itself, visualization in big data is different because showing the individual observations is just not an option. But visualization is essential here: for analysis to work well, we have to be assured that patterns and errors in the data have been spotted and understood. That is only possible by visualization with big data, because nobody can look over the data in a table or spreadsheet." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"As a first principle, any visualization should convey its information quickly and easily, and with minimal scope for misunderstanding. Unnecessary visual clutter makes more work for the reader’s brain to do, slows down the understanding (at which point they may give up) and may even allow some incorrect interpretations to creep in." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"Cross-validation is a useful tool for finding optimal predictive models, and it also works well in visualization. The concept is simple: split the data at random into a 'training' and a 'test' set, fit the model to the training data, then see how well it predicts the test data. As the model gets more complex, it will always fit the training data better and better. It will also start off getting better results on the test data, but there comes a point where the test data predictions start going wrong." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"Dashboards are collections of several linked visualizations all in one place. The idea is very popular as part of business intelligence: having current data on activity summarized and presented all inone place. One danger of cramming a lot of disparate information into one place is that you will quickly hit information overload. Interactivity and small multiples are definitely worth considering as ways of simplifying the information a reader has to digest in a dashboard. As with so many other visualizations, layering the detail for different readers is valuable." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"Decision trees show the breakdown of the data by one variable then another in a very intuitive way, though they are generally just diagrams that don’t actually encode data visually." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"Estimates based on data are often uncertain. If the data were intended to tell us something about a wider population (like a poll of voting intentions before an election), or about the future, then we need to acknowledge that uncertainty. This is a double challenge for data visualization: it has to be calculated in some meaningful way and then shown on top of the data or statistics without making it all too cluttered." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"One very common problem in data visualization is that encoding numerical variables to area is incredibly popular, but readers can’t translate it back very well." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"The relevance to data visualization is that we are always conveying a message to some extent, and in the case of associations between variables, that message is sometimes a step removed from the data itself. If you are making visualizations, be careful not to impose your own interpretation too much when showing associations. If you are reading them, don’t assume that the message accompanying the data is as sound and scientifically based as the data themselves." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"The term 'infographics' is used for eye-catching diagrams which get a simple message across. They are very popular in advertising and can convey an impression of scientific, reliable information, but they are not the same thing as data visualization. An infographic will typically only convey a few numbers, and not use visual presentations to allow the reader to make comparisons of their own." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"There is often no one 'best' visualization, because it depends on context, what your audience already knows, how numerate or scientifically trained they are, what formats and conventions are regarded as standard in the particular field you’re working in, the medium you can use, and so on. It’s also partly scientific and partly artistic, so you get to express your own design style in it, which is what makes it so fascinating." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"With skewed data, quantiles will reflect the skew, while adding standard deviations assumes symmetry in the distribution and can be misleading." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"Random forests are essentially an ensemble of trees. They use many short trees, fitted to multiple samples of the data, and the predictions are averaged for each observation. This helps to get around a problem that trees, and many other machine learning techniques, are not guaranteed to find optimal models, in the way that linear regression is. They do a very challenging job of fitting non-linear predictions over many variables, even sometimes when there are more variables than there are observations. To do that, they have to employ 'greedy algorithms', which find a reasonably good model but not necessarily the very best model possible." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

✏️Nathan Yau - Collected Quotes

"A common mistake is that all visualization must be simple, but this skips a step. You should actually design graphics that lend clarity, and that clarity can make a chart 'simple' to read. However, sometimes a dataset is complex, so the visualization must be complex. The visualization might still work if it provides useful insights that you wouldn’t get from a spreadsheet. […] Sometimes a table is better. Sometimes it’s better to show numbers instead of abstract them with shapes. Sometimes you have a lot of data, and it makes more sense to visualize a simple aggregate than it does to show every data point." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"After you visualize your data, there are certain things to look for […]: increasing, decreasing, outliers, or some mix, and of course, be sure you’re not mixing up noise for patterns. Also note how much of a change there is and how prominent the patterns are. How does the difference compare to the randomness in the data? Observations can stand out because of human or mechanical error, because of the uncertainty of estimated values, or because there was a person or thing that stood out from the rest. You should know which it is." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Area can also make data seem more tangible or relatable, because physical objects take up space. A circle or a square uses more space than a dot on a screen or paper. There’s less abstraction between visual cue and real world." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Context (information that lends to better understanding the who, what, when, where, and why of your data) can make the data clearer for readers and point them in the right direction. At the least, it can remind you what a graph is about when you come back to it a few months later. […] Context helps readers relate to and understand the data in a visualization better. It provides a sense of scale and strengthens the connection between abstract geometry and colors to the real world." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Data is an abstraction of real life, and real life can be complicated, but if you gather enough context, you can at least put forth a solid effort to make sense of it." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Data is more than numbers, and to visualize it, you must know what it represents. Data represents real life. It’s a snapshot of the world in the same way that a photograph captures a small moment in time. […] The connection between data and what it represents is key to visualization that means something. It is key to thoughtful data analysis. It is key to a deeper understanding of your data. Computers do a bulk of the work to turn numbers into shapes and colors, but you must make the connection between data and real life, so that you or the people you make graphics for extract something of value." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Early exploration of a dataset can be overwhelming, because you don’t know where to start. Ask questions about the data and let your curiosities guide you. […] Make multiple charts, compare all your variables, and see if there are interesting bits that are worth a closer look. Look at your data as a whole and then zoom in on categories and individual data points. […] Subcategories, the categories within categories (within categories), are often more revealing than the main categories. As you drill down, there can be higher variability and more interesting things to see." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Good visualization is a winding process that requires statistics and design knowledge. Without the former, the visualization becomes an exercise only in illustration and aesthetics, and without the latter, one of only analyses. On their own, these are fine skills, but they make for incomplete data graphics. Having skills in both provides you with the luxury - which is growing into a necessity - to jump back and forth between data exploration and storytelling." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"It’s tempting to look at data as absolute truth, because we associate numbers with fact, but more often than not, data is an educated guess. Your goal is to use data that doesn’t have large levels of uncertainty attached." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Most data is linked to time in some way in that it might be a time series, or it’s a snapshot from a specific period. In both cases, you have to know when the data was collected. An estimate made decades ago does not equate to one in the present. This seems obvious, but it’s a common mistake to take old data and pass it off as new because it’s what’s available. Things change, people change, and places change, and so naturally, data changes." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Most important, the range of data literacy and familiarity with your data’s context is much wider when you design graphics for a general audience." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Numbers seem concrete and absolute, but estimates carry uncertainty with them. Data is an abstraction of what it represents, and the level of exactness varies." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"People often skip methodology because it tends to be complex and for a technical audience, but it’s worth getting to know the gist of how the data of interest was collected."  (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Put everything together - from understanding data, to exploration, clarity, and adapting to an audience - and you get a general process for how to make data graphics."  (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Readability in visualization helps people interpret data and make conclusions about what the data has to say. Embed charts in reports or surround them with text, and you can explain results in detail. However, take a visualization out of a report or disconnect it from text that provides context (as is common when people share graphics online), and the data might lose its meaning; or worse, others might misinterpret what you tried to show." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"The best way to learn where people are is to show your work to those who don’t know your data. You get an immediate sense of understanding just from first impressions." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"The connection between data and what it represents is key to visualization that means something. It is key to thoughtful data analysis. It is key to a deeper understanding of your data. Computers do a bulk of the work to turn numbers into shapes and colors, but you must make the connection between data and real life, so that you or the people you make graphics for extract something of value." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"The data is a simplification - an abstraction - of the real world. So when you visualize data, you visualize an abstraction of the world, or at least some tiny facet of it. Visualization is an abstraction of data, so in the end, you end up with an abstraction of an abstraction, which creates an interesting challenge. […] Just like what it represents, data can be complex with variability and uncertainty, but consider it all in the right context, and it starts to make sense." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Visualization can be appreciated purely from an aesthetic point of view, but it’s most interesting when it’s about data that’s worth looking at. That’s why you start with data, explore it, and then show results rather than start with a visual and try to squeeze a dataset into it. It’s like trying to use a hammer to bang in a bunch of screws. […] Aesthetics isn’t just a shiny veneer that you slap on at the last minute. It represents the thought you put into a visualization, which is tightly coupled with clarity and affects interpretation." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Visualization is a medium: a way to explore, present, and express meaning in data. […] Visualization is often framed as a medium for storytelling. The numbers are the source material, and the graphs are how you describe the source. When referring to stories or data narrative, I don’t mean novels (but great if that’s what you’re after). Rather, I mean statistical stories […]" (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Visualization is often thought of as an exercise in graphic design or a brute-force computer science problem, but the best work is always rooted in data. To visualize data, you must understand what it is, what it represents in the real world, and in what context you should interpret it in." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Visualization is what happens when you make the jump from raw data to bar graphs, line charts, and dot plots. […] In its most basic form, visualization is simply mapping data to geometry and color. It works because your brain is wired to find patterns, and you can switch back and forth between the visual and the numbers it represents. This is the important bit. You must make sure that the essence of the data isn’t lost in that back and forth between visual and the value it represents because if you can’t map back to the data, the visualization is just a bunch of shapes." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"What is good visualization? It is a representation of data that helps you see what you otherwise would have been blind to if you looked only at the naked source. It enables you to see trends, patterns, and outliers that tell you about yourself and what surrounds you. The best visualization evokes that moment of bliss when seeing something for the first time, knowing that what you see has been right in front of you, just slightly hidden. Sometimes it is a simple bar graph, and other times the visualization is complex because the data requires it." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Without context, data is useless, and any visualization you create with it will also be useless. Using data without knowing anything about it, other than the values themselves, is like hearing an abridged quote secondhand and then citing it as a main discussion point in an essay. It might be okay, but you risk finding out later that the speaker meant the opposite of what you thought."  (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"You have to know the who, what, when, where, why, and how - the metadata, or the data about the data - before you can know what the numbers are actually about. […] Learn all you can about your data before anything else, and your analysis and visualization will be better for it. You can then pass what you know on to readers."  (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"We often think of visualization as a design and programming task, but the process starts further back with the data. You have to understand the data - its trends and patterns, along with its flaws and imperfections - and the rest follows." (Nathan Yau)