"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)
"Most authors would greatly resent it if they were told that their writings contained great exaggerations, yet many of these same authors permit their work to be illustrated with charts which are so arranged as to cause an erroneous interpretation. If authors and editors will inspect their charts as carefully as they revise their written matter, we shall have, in a very short time, a standard of reliability in charts and illustrations just as high as now found in the average printed page." (Willard C Brinton, "Graphic Methods for Presenting Facts", 1919)
"The principles of charting and curve plotting are not at all complex, and it is surprising that many business men dodge the simplest charts as though they involved higher mathematics or contained some sort of black magic. [...] The trouble at present is that there are no standards by which graphic presentations can be prepared in accordance with definite rules so that their interpretation by the reader may be both rapid and accurate. It is certain that there will evolve for methods of graphic presentation a few useful and definite rules which will correspond with the rules of grammar for the spoken and written language." (Willard C Brinton, "Graphic Methods for Presenting Facts", 1919)
"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)
"Clear, detailed, and thorough labeling should be used to defeat graphical distortion and ambiguity. Write out explanations of the data on the graphic itself. Label important events in the data." (Edward R Tufte, "The Visual Display of Quantitative Information", 1983)
"Vigorous writing is concise. A sentence should contain no unnecessary words, a paragraph no unnecessary sentences, for the same reason that a drawing should have no unnecessary lines and a machine no unnecessary parts. This requires not that the writer make all his sentences short, or that heavoid all detail and treat his subjects only in outline, but that every word tell." (Edward R Tufte, "The Visual Display of Quantitative Information", 1983)
"Don’t rush to write a headline or an entire story or to design a visualization immediately after you find an interesting pattern, data point, or fact. Stop and think. Look for other sources and for people who can help you escape from tunnel vision and confirmation bias. Explore your information at multiple levels of depth and breadth, looking for extraneous factors that may help explain your findings. Only then can you make a decision about what to say, and how to say it, and about what amount of detail you need to show to be true to the data." (Alberto Cairo, "The Functional Art", 2011)
"It is important to remember that a visual representation of a scientific concept (or data) is a re-presentation, and not the thing itself - some interpretation or translation is always involved. There are many parallels between creating a graphic and writing an article. First, you must carefully plan what to 'say', and in what order you will 'say it'. Then you must make judgments to determine a hierarchy of information - what must be included and what could be left out? The process of making a visual representation requires you to clarify your thinking and improve your ability to communicate with others. Furthermore, the process of making an effective graphic often leads to new insights into your work; when you make decisions about how to depict your data and underlying concepts, you must often clarify your basic assumptions." (Felice C Frankel & Angela H DePace, "Visual Strategies", 2012)
"Write the way you design. If you are a generalist designer, unfettered by a specific style, then follow that method. If you have a particular visual or conceptual stylistic leaning, then your writing voice might echo that. If you decide your design and writing sides are best when they are separate, then you will find the essential balance. But just as you never design without purpose, never write without it either. Your writing should be informative, enjoyable, perhaps even entertaining. The role of the voice is to ensure that your content does these things, and more." (Steven Heller, "Writing and Research for Graphic Designers: A Designer's Manual to Strategic Communication and Presentation", 2012)
"There are myriad questions that we can ask from data today. As such, it’s impossible to write enough reports or design a functioning dashboard that takes into account every conceivable contingency and answers every possible question." (Phil Simon, "The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions", 2014)
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)
Even though data is being thrust on more people, it doesn’t mean everyone is prepared to consume and use it effectively. As our dependence on data for guidance and insights increases, the need for greater data literacy also grows. If literacy is defined as the ability to read and write, data literacy can be defined as the ability to understand and communicate data. Today’s advanced data tools can offer unparalleled insights, but they require capable operators who can understand and interpret data." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)
"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)
"The rise of graphicacy and broader data literacy intersects with the technology that makes it possible and the critical need to understand information in ways current literacies fail. Like reading and writing, data literacy must become mainstream to fully democratize information access." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)
No comments:
Post a Comment