"If the audience can see all the charts at once, they may get a different story from the one you want them to get. Show the charts one at a time. If you have only one chart, keep it covered until you are ready to use it. Take full advantage of the element of surprise. If you use charts which open like a book, use only one page for the message." (Edward J Hegarty, "How to Use a Set of Display Charts", The American Statistician Vol. 2" (5), 1948)
"While circle charts are not likely to present especially new or creative ideas, they do help the user to visualize relationships. The relationships depicted by circle charts do not tend to be very complex, in contrast to those of some line graphs. Normally, the circle chart is used to portray a common type of relationship" (namely. part-to-total) in an attractive manner and to expedite the message transfer from designer to user." (Cecil H Meyers, "Handbook of Basic Graphs: A modern approach", 1970)
"Arbitrary category sequence and misplaced pie chart emphasis lead to general confusion and weaken messages. Although this can be used for quite deliberate and targeted deceit, manipulation of the category axis only really comes into its own with techniques that bend the relationship between the data and the optics in a more calculated way. Many of these techniques are just twins of similar ruses on the value axis. but are none the less powerful for that." (Nicholas Strange, "Smoke and Mirrors: How to bend facts and figures to your advantage", 2007)
"We tend automatically to think of all the categories represented on the horizontal axis of a column Chart as being equally important. They vary of course on the value axis. Otherwise, there would be little point in the chart, but there is somehow this feeling that they are in other respects similar members of a group. This convention can be put to good use to manipulate the message of the most boring bar or column chart." (Nicholas Strange, "Smoke and Mirrors: How to bend facts and figures to your advantage", 2007)
"What distinguishes data tables from graphics is explicit comparison and the data selection that this requires. While a data table obviously also selects information, this selection is less focused than a chart's on a particular comparison. To the extent that some figures in a table are visually emphasised. say in colour or size and style of print. the table is well on its way to becoming a chart. If you're making no comparisons - because you have no particular message and so need no selection" (in other words, if you are simply providing a database, number quarry or recycling facility) - tables are easier to use than charts." (Nicholas Strange, "Smoke and Mirrors: How to bend facts and figures to your advantage", 2007)
"When displaying information visually, there are three questions one will find useful to ask as a starting point. Firstly and most importantly, it is vital to have a clear idea about what is to be displayed; for example, is it important to demonstrate that two sets of data have different distributions or that they have different mean values? Having decided what the main message is, the next step is to examine the methods available and to select an appropriate one. Finally, once the chart or table has been constructed, it is worth reflecting upon whether what has been produced truly reflects the intended message. If not, then refine the display until satisfied; for example if a chart has been used would a table have been better or vice versa?" (Jenny Freeman et al, "How to Display Data", 2008)
"A beautiful visualization has a clear goal, a message, or a particular perspective on the information that it is designed to convey. Access to this information should be as straightforward as possible, without sacrificing any necessary, relevant complexity. [...] Most importantly, beautiful visualizations reflect the qualities of the data that they represent, explicitly revealing properties and relationships inherent and implicit in the source data. As these properties and relationships become available to the reader, they bring new knowledge, insight, and enjoyment." (Noah Iliinsky, "On Beauty", [in "Beautiful Visualization"] 2010)
"Bear in mind is that the use of color doesn’t always help. Use it sparingly and with a specific purpose in mind. Remember that the reader’s brain is looking for patterns, and will expect both recurrence itself and the absence of expected recurrence to carry meaning. If you’re using color to differentiate categorical data, then you need to let the reader know what the categories are. If the dimension of data you’re encoding isn’t significant enough to your message to be labeled or explained in some way - or if there is no dimension to the data underlying your use of difference colors - then you should limit your use so as not to confuse the reader." (Noah Iliinsky & Julie Steel, "Designing Data Visualizations", 2011)
"[...] you should not rely on social or cultural conventions to convey information. However, these conventions can be very powerful, and you should be aware that your reader brings them to the table. Making use of them, when possible, to reinforce your message will help you convey information efficiently. Avoid countering conventions where possible in order to avoid creating cognitive dissonance, a clash of habitual interpretation with the underlying message you are sending." (Noah Iliinsky & Julie Steel, "Designing Data Visualizations", 2011)
"Communication is the primary goal of data visualization. Any element that hinders - rather than helps - the reader, then, needs to be changed or removed: labels and tags that are in the way, colors that confuse or simply add no value, uncomfortable scales or angles. Each element needs to serve a particular purpose toward the goal of communicating and explaining information. Efficiency matters, because if you’re wasting a viewer’s time or energy, they’re going to move on without receiving your message." (Noah Iliinsky & Julie Steel, "Designing Data Visualizations", 2011)
"An infographic (short for information graphic) is a type of picture that blends data with design, helping individuals and organizations concisely communicate messages to their audience." (Mark Smiciklas, "The Power of Infographics: Using Pictures to Communicate and Connect with Your Audiences", 2012)
"A great infographic leads readers on a visual journey, telling them a story along the way. Powerful infographics are able to capture people’s attention in the first few seconds with a strong title and visual image, and then reel them in to digest the entire message. Infographics have become an effective way to speak for the creator, conveying information and image simultaneously." (Justin Beegel, "Infographics For Dummies", 2014)
"Any presentation of data, whether a simple calculated metric or a complex predictive model, is going to have a set of assumptions and choices that the producer has made to get to the output. The more that these can be made explicit, the more the audience of the data will be open to accepting the message offered by the presenter." (Zach Gemignani et al, "Data Fluency", 2014)
"Data visualizations are designed to emphasize patterns and deviations in data. In fact, each specific chart type is well suited to highlighting particular forms of insight. A skilled author of data products will choose the right visualization to emphasize a message. The data, chart, and supporting descriptions should work in harmony to point out what is interesting. The reader simply goes along for the ride." (Zach Gemignani et al, "Data Fluency", 2014)
"In fact, the analogy to storytelling is limited when applied to communicating with data. Data visualization has fundamental characteristics missing from traditional storytelling. For example, interactive data visualizations let audiences explore information to find insights that resonate with them. Visualizations take shape based to a large extent on the underlying data. And as this data changes, the emphasis and message of the visualization is likely to change." (Zach Gemignani et al, "Data Fluency", 2014)
"It’s the 'message' that decides the presentation. The numbers, visual, or text or a combination of these are to only support the way of putting the message across. This also changes the way one conceptualizes a graphic. The thought starts with the message and then gets into putting other related information together to support it instead of starting with the data and thinking of what to make of it [...] The advantage of taking this route is also that you are not just restricted by topics or numbers or just presenting “news.” You can go a step further and air your “views,” too, to make a point." (Raj Kamal, "Everyday Visuals as News", 2014)
"A signal is a useful message that resides in data. Data that isn’t useful is noise. […] When data is expressed visually, noise can exist not only as data that doesn’t inform but also as meaningless non-data elements of the display" (e.g. irrelevant attributes, such as a third dimension of depth in bars, color variation that has no significance, and artificial light and shadow effects)." (Stephen Few, "Signal: Understanding What Matters in a World of Noise", 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)
"Charts are always an interpretation of data, in the same way that a photo is an interpretation of reality, no matter how objective it may seem. This should be not only recognized but encouraged within an ethical framework that seeks to identify its own subjectivity and minimize its influence on choices. There can be no contradiction between 'what I want to say' and 'what the data say'. This difference is often difficult to detect, especially when the subject’s message is fully determined by his beliefs, ideological position, and activism." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)
"Ideally, the charts are designed in a way that gives your audience clarity and lets them understand the key insights very quickly. Color choices, highlighting, annotations, and other ways of drawing attention to your findings help in the process. By leaving white or blank space around your charts, you are able to keep the focus of your audience on the key message rather than distracting or confusing them." (Andy Kriebel & Eva Murray, "#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time", 2018)
"Simplicity for data visualization often focuses on minimizing the number of elements that do not add value to your display. These include borders, gridlines, axes lines, and boxes, which can easily distract from your core message. This recommendation also relates to the information itself. You should strive to create a visualization that focuses on specific aspects of the data, rather than including all fields and metrics but not saying much about any of them." (Andy Kriebel & Eva Murray, "#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time", 2018)
"First, from an ethos perspective, the success of your data story will be shaped by your own credibility and the trustworthiness of your data. Second, because your data story is based on facts and figures, the logos appeal will be integral to your message. Third, as you weave the data into a convincing narrative, the pathos or emotional appeal makes your message more engaging. Fourth, having a visualized insight at the core of your message adds the telos appeal, as it sharpens the focus and purpose of your communication. Fifth, when you share a relevant data story with the right audience at the right time (kairos), your message can be a powerful catalyst for change." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 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)
"Another problem is that while data visualizations may appear to be objective, the designer has a great deal of control over the message a graphic conveys. Even using accurate data, a designer can manipulate how those data make us feel. She can create the illusion of a correlation where none exists, or make a small difference between groups look big." (Carl T Bergstrom & Jevin D West, "Calling Bullshit: The Art of Skepticism in a Data-Driven World", 2020)
"Beyond basic charts, practitioners must also learn to compose visualizations together elegantly. The perceptual stage focuses on making the literal charts more precise as well as working to de-emphasize the entire piece. Design choices start to consider distractions, reducing visual clutter and centering on the message. Minimalism is espoused as a core value with an emphasis on shifting toward precision as accuracy. This is the most common next step for practitioners. Minimalism is also a key stage in maturation. It is experimentation at one extreme that helps practitioners distill down to core, shared practices." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)
"Beyond the design of individual charts, the sequence of data visualizations creates grammar within the exposition. Cohesive visualizations follow common narrative structures to fully express their message. Order matters. " (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)
"Chart choices can also create weight within the entire composition. Presenting information as a comprehensive visualization, such as in a dashboard, requires thinking beyond individual charts. In writing, we not only craft sentences, but write the composition as an entire piece. Certain sentences may drive the writing more, but all sentences play a role in conveying the message." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)
"Communication requires the ability to expand or contract a message based on norms within a given culture or language. Expansion provides more detail, sometimes adding in information that is culturally relevant or needed for the person to understand. Contraction preserves the same intent but discards information that isn't needed by that person. Some concepts in certain situations require greater detail than others." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)
"The sizes of charts in space reflect how we convey information to a reader. In a dashboard context, the content, size, and space that the various charts occupy should reflect the form and function of the main message. As you saw with the bento box metaphor from the introduction, there needs to be deliberate thought put into the placement and size of each individual chart so that they all work together in harmony." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)
"When integrating written text with charts in a functionally aesthetic way, the reader should be able to find the key takeaways from the chart or dashboard, taking into account the context, constraints, and reading objectives of the overall message. " (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)
"A perfectly relevant visualization that breaks a few presentation rules is far more valuable - it’s better - than a perfectly executed, beautiful chart that contains the wrong data, communicates the wrong message, or fails to engage its audience." (Scott Berinato, "Good Charts : the HBR guide to making smarter, more persuasive data visualizations", 2023)
"The lack of focus and commitment to color is a perplexing thing. When used correctly, color has no equal as a visualization tool - in advertising, in branding, in getting the message across to any audience you seek. Data analysts can make numbers dance and sing on command, but they sometimes struggle to create visually stimulating environments that convince the intended audience to tap their feet in time." (Kate Strachnyi, "ColorWise: A Data Storyteller’s Guide to the Intentional Use of Color", 2023)
"Graphic design is not just about making things look good. It is a powerful combination of form and function that uses visual elements to communicate a message. Form refers to the physical appearance of a design, such as its shape, color, and typography. Function refers to the purpose of a design, such as what it is trying to communicate or achieve. A good graphic design is both visually appealing and functional. It uses the right combination of form and function to communicate its message effectively. Graphic design is also a strategic and thoughtful craft. It requires careful planning and execution to create a design that is both effective and aesthetically pleasing." (Faith Aderemi, "The Essential Graphic Design Handbook", 2024)
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