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Functional Aesthetics for Data Visualization Kindle Edition

by Vidya Setlur (Author), Bridget Cogley (Author) Format: Kindle Edition
4.5 4.5 out of 5 stars 13 ratings
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What happens when a researcher and a practitioner spend hours crammed in a Fiat discussing data visualization? Beyond creating beautiful charts, they found greater richness in the craft as an integrated whole.

Drawing from their unconventional backgrounds, these two women take readers through a journey around perception, semantics, and intent as the triad that influences visualization. This visually engaging book blends ideas from theory, academia, and practice to craft beautiful, yet meaningful visualizations and dashboards.

How do you take your visualization skills to the next level? The book is perfect for analysts, research and data scientists, journalists, and business professionals. Functional Aesthetics for Data Visualization is also an indispensable resource for just about anyone curious about seeing and understanding data. Think of it as a coffee book for the data geek in you.

https://www.functionalaestheticsbook.com

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  1. Print length
    323 pages
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    English
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    Wiley
  5. Publication date
    May 18, 2022
  6. File size
    104589 KB
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Editorial Reviews

Review

"Straight away, you can tell this is a labour of love – the enthusiasm and validity with which the authors describe elements from the three elements of theory, academia and practice really shine through. With backgrounds covering all three of these areas, it makes for a complete publication, full of examples not just from practical situations as a practitioner, but from theory – focusing in particular on theory of presentation, psychology, conversation and cognition. All things which influence creation of functional and aesthetic dashboards, most of which, like me, you probably hadn't considered in requisite depth until now..."
―Neil Richards, four time Tableau Visionary and Director of Editorial for Viz For Social Good

From the Back Cover

This is not another book about charts

What happens when a researcher and a practitioner spend hours crammed in a Fiat discussing data visualization? Beyond creating beautiful charts, they found greater richness in the craft as an integrated whole.

Drawing from their unconventional backgrounds, these two women take readers through a journey around perception, semantics, and intent as the triad that influences visualization. This visually engaging book blends ideas from theory, academia, and practice to craft beautiful, yet meaningful visualizations and dashboards.

Product details

  • ASIN ‏ : ‎ B0B1TRCHZ1
  • Publisher ‏ : ‎ Wiley; 1st edition (May 18, 2022)
  • Publication date ‏ : ‎ May 18, 2022
  • Language ‏ : ‎ English
  • File size ‏ : ‎ 104589 KB
  • Text-to-Speech ‏ : ‎ Enabled
  • Enhanced typesetting ‏ : ‎ Enabled
  • X-Ray ‏ : ‎ Not Enabled
  • Word Wise ‏ : ‎ Not Enabled
  • Sticky notes ‏ : ‎ Not Enabled
  • Print length ‏ : ‎ 323 pages
  • Customer Reviews:
    4.5 4.5 out of 5 stars 13 ratings

About the authors

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  1. Bridget Cogley

    Bridget Cogley

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    Interpreter turned analyst, Bridget Cogley brings an interdisciplinary approach to data analytics. As Chief Visualization Officer at Versalytix, her role uplifts data visualization within the organization and helps shape the vision. Her dynamic, engaging presentation style is paired with thought-provoking content, including ethics and data visualization linguistics. She has a deep interest in the nuances of communication, having been an American Sign Language Interpreter for nine years. She is currently a Hall of Fame Tableau Visionary. Her work incorporates human-centric dashboard design, an anthropological take on design, ethics, and language. She extensively covers speech analytics and open text.

    See more on the author's page
  2. Vidya Setlur

    Vidya Setlur

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    Full content visible, double tap to read brief content.

    Vidya is the director of Tableau Research. She leads an interdisciplinary team of research scientists in areas including data visualization, multimodal interaction, statistics, applied ML, and NLP. She earned her doctorate in Computer Graphics in 2005 at Northwestern University. Prior to joining Tableau, she worked as a principal research scientist at the Nokia Research Center for seven years. Her personal research interests lie at the intersection of natural language processing and computer graphics. She combines concepts and methods from information retrieval, human perception, and cognitive science to help users effectively interact with devices and information in their environment. A significant portion of her work covers the investigation, prototyping, and evaluation of such novel concepts.

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Customer reviews

4.5 out of 5 stars
4.5 out of 5
13 global ratings
Fits a Niche in the Data Viz Book space Between Theory, Research, and Practice
5 Stars
Fits a Niche in the Data Viz Book space Between Theory, Research, and Practice
Perhaps I am the target audience for this book being a former cognitive scientist turned data viz specialist. Still, I think it fits a hole that was not previously covered in previous books that are primarily about the "how to" part of the data viz development process. If you are interested in the "why" part of the data visualization process and how science informs practice, you should read this book. I also appreciated the image quality and illustrations throughout as the book's design also mirrors the content within.
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Top reviews from the United States

Christina Poulin
5.0 out of 5 stars Fits a Niche in the Data Viz Book space Between Theory, Research, and Practice
Reviewed in the United States on October 12, 2022
Verified Purchase
Perhaps I am the target audience for this book being a former cognitive scientist turned data viz specialist. Still, I think it fits a hole that was not previously covered in previous books that are primarily about the "how to" part of the data viz development process. If you are interested in the "why" part of the data visualization process and how science informs practice, you should read this book. I also appreciated the image quality and illustrations throughout as the book's design also mirrors the content within.
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Christina Poulin
5.0 out of 5 stars Fits a Niche in the Data Viz Book space Between Theory, Research, and Practice
Reviewed in the United States on October 12, 2022
Perhaps I am the target audience for this book being a former cognitive scientist turned data viz specialist. Still, I think it fits a hole that was not previously covered in previous books that are primarily about the "how to" part of the data viz development process. If you are interested in the "why" part of the data visualization process and how science informs practice, you should read this book. I also appreciated the image quality and illustrations throughout as the book's design also mirrors the content within.
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Sarah Nell
5.0 out of 5 stars Needed book
Reviewed in the United States on September 25, 2022
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Not only is this women written, but it’s a book that dives into the language and thought of data visualization. It’s form and function. Highly recommend.
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Chase Stokes
5.0 out of 5 stars Fantastic combination of research and practice
Reviewed in the United States on October 27, 2023
"Functional Aesthetics for Data Visualization" has a compelling narrative and a delightful voice that provides critical insights for features of visualization and visualization design. The book merges on findings from research and applications from design practice to encourage an updated look at how we should communicate data. As a visualization researcher, it's enlightening to see the breadth and depth of knowledge presented here. It's a must-have resource for those looking to learn more about data visualization.
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Nicole Mark
5.0 out of 5 stars A compelling and refreshing approach to dataviz
Reviewed in the United States on January 12, 2023
My data visualization library contains many books authored by and geared toward data practitioners. Many good books. But Functional Aesthetics for Data Visualization is the first I’ve read that combines theory, research, and practice into its singular vision of data visualization as a medium yet remains accessible to a more general audience.

It's a refreshingly different dataviz text. Integral to what makes it different from other books is the synthesis of perspectives of two women with very different backgrounds--Bridget Cogley was an American Sign Language interpreter prior to her data career, and Vidya Setlur is a researcher particularly interested in natural language processing (NLP). The give and take between perspectives makes the book read like a conversation.

The material presented, particularly in later chapters, is complex, but the method and order of presentation makes it easily consumable. Since it is, in fact, a book about visual communication, it’s unsurprising that there are visual cues in the book. What’s remarkable is the effectiveness of the choices of subtle visual cues. They gently guide you through the material, making sure you’re following the conversation. The bottom of each page is bordered with one of four colors each mapped to one of the four parts of the text–Perception, Semantics, Intent, and Putting It All Together. Next to each important concept, there’s a rounded rectangle with some explanatory text and an accompanying triangle with the word “research” at one point, and “practice” and “theory” at the other two points, respectively. There is a circle inside the triangle, placed to orient the reader to where the concept is currently situated in the landscape of the field of data visualization.

You’re not getting any freebies from Bridget Cogley and Vidya Setlur. No new “best” practices, no “nevers” or “always”, no five easy steps to he perfect dashboard. This book makes no assumptions about your profession, your industry, or your opinion about pie charts. In fact, the only assumption it makes is that you’re a human who can read or be read to. For those of us who are practitioners, Functional Aesthetics challenges us to not only follow the conversation contained within, but to continue it. It subtly nudges us to engage in a conversation between ourselves as creators of data visualizations, our established processes, our assumptions, and our workflows. I took my time reading it because each section left me wanting time to integrate and experiment with some of the ideas in my own visualizations and to re-examine my long-held notions of the “right” ways to approach dataviz.

If you’re new to data visualization, I can’t think of a better book to start with. If you’re a long-time practitioner, Functional Aesthetics will freshen your perspective, leaving you excited to approach your next viz with a beginner’s mind. Everyone’s needs are considered here, and all are invited to the conversation.

Many, if not most, data visualization books focus on the data visualization creator's perspective and goals for their work almost exclusively. This emphasis on the practitioner’s goals is not wrong and doesn’t mean that the user, viewer, or audience is excluded. They’re very much top of mind–as a consumer of what the practitioner wants to serve up, in terms of both graphs and insights. Considerations about the user’s goals with respect to interaction with data visualizations are mostly limited to cases where the user is a business person consuming a business data visualization ("dashboard").

Business stakeholders occupy little space in Functional Aesthetics for Data Visualization, except as users of visualizations like any other user. We now live in a world where we all look at charts and graphs for a variety of reasons. Functional Aesthetics is very much a book for chart creators, but also for chart consumers who might be curious about how charts work and want to increase their level of graphicacy (chart literacy).
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Anonymous
5.0 out of 5 stars GREAT BOOK!
Reviewed in the United States on October 8, 2022
Very Informative!
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Top reviews from other countries

Nick Cox
3.0 out of 5 stars Most useful for particular readers; intriguing on AI applications, but uneven presentation
Reviewed in the United Kingdom on February 21, 2023
Verified Purchase
Functional aesthetics for data visualization? That's working well and looking good, I take it. Many visualizations do poorly on one or other score, and so guidance towards reaching those goals is always welcome. Here the broad aim is "semantically resonant data-centric creations" (p.xviii). Good visualizations give good vibrations?

This book seems most aimed at, and most suitable for, people who

have already read several books on visualization, and especially have some experience of the field

have as their main responsibility preparing visualizations for others, say in a business, consultancy, non-profit or government support role

are using Tableau or something similar (although there is no specific detail on software use, mentions of Tableau dominate; on p.285 departure from Tableau defaults without a strategy is flagged as a possible problem)

are most interested in dashboards (composite visualizations with two or more graphs or maps, often contrasting, and perhaps some text too; students and academics in many fields are more likely to think in terms of posters)

are working with fairly simple graphs and maps, such as bar or line charts or dot or patch maps (and so using basic statistical or cartographic methods).

As a teacher and researcher in a university with a long-term interest in statistical graphics (data and information visualization too), I fit the first criterion well, but most of the others barely or not at all. That kind of misfit isn't crucial: the book might be interesting or useful far beyond its most obvious target readership. But see how far you match that little list.

As indications of what is not here, as well as what is: There is no recognition that many, indeed I suspect most, visualizations are devised in spreadsheets such as MS Excel, presentation software such as MS PowerPoint, or statistical and GIS software. The statistical level is shown by the authors twice alluding (pp.144, 270) to box plots as more advanced, which will surprise students meeting them in a first statistics course. Logarithmic scale appears briefly on p.62. To be clear, I am all for simple methods when they suffice, but be advised accordingly.

The authors' tone is informal and friendly. Generous acknowledgments include affectionate mentions of one dog and three cats. Their expertise and enthusiasm are evident. But I found their writing often hard to follow. I had to read many sentences twice. Sometimes my puzzle was whether I was missing a nuance wrapped up in a very simple statement that seemed too obvious. Sometimes I had to disentangle the message from jargon, metaphor, or analogy. Sometimes the problem was just awkward or cryptic writing.

Technical writing often raises tensions between authors who use terminology that you are expected to know or to be willing to learn and readers who struggle with what may seem unfamiliar or unnecessary jargon. My concern here is that the authors' style varies so much, as purple patches are mixed with much that is clear and even vivid. As so often happens, they have been let down by their publishers. Copy editing should have fixed many of the small problems I had, and fixed many awkward sentences using parallel constructions. Uses of both ... and ..., either ... or ..., and not only ... but also ... often need to be read twice too. Copy editing should have hacked at the paradigms, parameters and ecosystems mentioned again and again, all those words being stretched way beyond their customary meaning. It should have found simpler alternatives for de-emphasize and deduplicating.

Some outright errors, most but not all trivial: Ansel Adam on p.1 should be Adams. The reference to astrology on p.38 looks like a slip for astronomy, although I can't guess at what is meant by the reference to cryptology on p.39. On p.41 Fisher's T test is presumably Student's t test, an error that compounds a profoundly unhistorical aside. The Mercator projection used on p.177 is utterly inappropriate as exaggerating areas in polar latitudes as compared with the tropics.

Despite some informality, this is mostly a serious and fairly academic book. Make sure that you note from p.xxii that references are to be found on the publishers' website, a puzzling and inconvenient arrangement. The authors want to tell you about the present frontier in data visualization, including their own work. Sections on research using artificial intelligence, and in particular natural language processing, are among the most intriguing contributions, although little is ever discussed in any real detail or depth. Typically there is an allusive paragraph, then a reference or two, and then we move on.

In a book on visualization, almost everything stands or falls on the graphics themselves. Graphics here divide about half and half into two groups. There are direct examples of visualizations showing data or results of analysis. There are also various supporting images. The latter include many triangle icons in which the current focus is plotted in terms of addressing research, practice, theory or a mix. Sorry, but I didn't find these helpful. There are some splendid photos of landscapes and food (no spoiler from me explaining why). The visualizations themselves are often unreadable in detail, although that isn't always crucial to the points being made.

My biggest surprise I leave to last. Although it wouldn't be his wording at all, functional aesthetics is a major theme running through Edward Tufte's first book on graphics, "The Visual Display of Quantitative Information", published originally 40 years ago, and four sequels to date. It doesn't rate even a mention here, but Tufte's work could be a far better starting point for anyone interested in the themes raised in this book.
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