Visualizing Complexity: Modular Information Design Handbook

by Darjan Hil, Nicole Lachenmeier

Design system for information design explained step by step How can you turn dry statistics into attractive and informative graphs? How can you present complex data sets in an easily understandable way? How can you create narrative diagrams from unstructured data? This handbook of information design answers these questions. Nicole Lachenmeier and Darjan Hil condense their extensive professional experience into an illustrated guide that offers a modular design system comprised of 80 elements. Their systematic design methodology makes it possible for anyone to visualize complex data attractively and using different perspectives. At the intersection of design, journalism, communication and data science, Visualizing Complexity opens up new ways of working with abstract data and invites readers to try their hands at information design

Genres: Design, Nonfiction

208 pages, Perfect Paperback

Published July 7, 2022

Reviews

[Koen Van den Eeckhout · Rating 4 out of 5]

I love the smell of new dataviz books in the morning… and ‘Visualizing Complexity’ is about as new as it gets! Written by (super-cool) information design agency Superdot from Basel (Switzerland) and published in May 2022, it contains an excellent analytical overview of the modular design system they developed over the past 10 years.

The book

The book, which arrived with a nice and friendly signed postcard, is printed on heavy high-quality paper, with a sturdy cardboard cover. A bit smaller than I expected, at 23 by 16 centimeters, it has a compact and inviting look and feel. The colors, fonts and layout are very reminiscent of the famous Bauhaus design movement, and despite the very intense, saturated color scheme, the design rarely overpowers the actual content. To be honest: it’s been lying on my desk for a week now, just to show off its beautiful design 😇

The highly structured book is divided into five parts:

Data dimensions: different ways of presenting and processing datasets

Diagrammatical dimensions, visual dimensions and structuring dimensions: a total of 80 elements which can be used to create shapes, arrange them, and make them visually distinguishable based on the different data dimensions

Multidimensional visualizations: examples of the Modular Information Design system breaking down powerful data visuals to show how they are built from combinations of these 80 elemental dimensions

The authors

Darjan Hill and Nicole Lachenmeier are the founders of information design agency Superdot (previously Yaay), which has grown into a well-known multidisciplinary team of information designers, developers and storytellers. They combine a background in Business Informatics (Darjan) and Visual Communication (Nicole) into a unique blend allowing them to approach information visualization challenges from a wide variety of perspectives.

Besides serving an impressive list of clients, winning many awards, and being involved in multiple teaching and mentoring program, Superdot is the initiator of the “On Data And Design” event series, and a pioneer in the field of DX – Data Experience Design.

The verdict

⭐⭐⭐⭐

With my background in science, the highly analytical approach of Visualizing Complexity resonates strongly with me. It is a welcome update of Jacques Bertin’s visual variables concept, with a bigger focus on combining different variables/elements to construct multidimensional and multi-layered visualizations.

The exactly 80 elements, consisting of 25 diagrammatical, 40 visual, and 15 structuring dimensions might feel a bit contrived at times, but on the other hand it is also a very complete overview. I'll definitely browse through this book during future projects, to ensure we’ve covered as many different visual ideas as possible.

What I'm missing a little bit in this book is an evaluation of how powerful each of these elements are. In the many examples in the final section of the book, it is clear how some elements (e.g. color hue) are much more prominent than others (e.g. contour details). Therefore, some of them are very logical choices for certain data dimensions, and others are less logical or way to subtle to clearly tell the story we want to tell in our visual. This evaluation is left to the reader to experience as a part of experimentation process – which is probably a good thing, as it could be quite dependent on the exact data.

All in all, this is a book that has definitely earned a prominent place on my dataviz bookshelf – a must have for everyone who wishes to understand the analytical thought processes behind strong data visuals!

[Chris G · Rating 5 out of 5]

Visualizing Complexity is a useful and practical handbook for making sense of complex information and communicating insights. The expert authors have devised what they call the MID system (Modular Information Design). It’s a simple but powerful way of thinking about and designing information visualisations that breaks visualisations down into their key elements.

This book is a great introduction to information visualisation, as well as a useful tool for professional designers to systematically explore visualisation options.

Visualizing Complexity is a beautifully designed book, making it easy to understand and a pleasure to read.

[David · Rating 3 out of 5]

This book on data visualization is so very Swiss/German. (Actually, the authors are Swiss and Austrian.) The authors created a modular system of graphical data presentation and called it MID (Modular Information Design). This book (which I backed on Kickstarter) is basically a catalog of different techniques to present information.

It goes well beyond your basic pie charts, bar charts, histograms, and pivot tables, and shows some really innovative ways of presenting data I hadn't thought of. Shapes, colors, contours, iconography, patterns, line lengths and terminuses and angles,all very methodically and systematically presented.

That said, a lot of the charts were very unintuitive to read, even once I deciphered how the information was being presented. I think the book would have benefited more from including some use cases. Rather than displaying 25 different ways to show a family history, breaking it down by generation, gender, lifespan, origin, and mobility, how about some discussion of which ways are most effective depending on what story you are trying to tell?

The authors do address this critical piece of data visualization - ultimately, you are trying to "tell a story" that is easier to read graphically than by looking at columns of numbers - but they don't really give any advice on actually accomplishing it. Thus, this book would be suitable as a reference for a visualization course, or as a source of inspiration (which is how I will use it, as it definitely can give you some ideas for different ways to present data) but I don't think it's very useful to someone new to visualization and much of the terminology (translated from German) is a little opaque.

[Dan Mendelsohn · Rating 2 out of 5]

I had high hopes for this book, and while it's modular design system is interesting, I personally find its resulting designs to be far less useful than the early table design they create at the beginning of the book. If I need to constantly reference what each design element means in order to interpret the design, the complexity isn't meaningfully visualized in a way that is any better than a table in my opinion. Very disappointed in what I hoped would be a great new way to visualize complexity

[Lewis Ngugi · Rating 5 out of 5]

Accidentally bumped into this book in a Design Museum and no regrets! It’s very practical for every designer especially those who end up analyzing data and presenting it to stakeholders. I wish I had read this at the beginning of my career.

[Peter Narsavage · Rating 3 out of 5]

An interesting framework. There are a few very good examples, but many of the examples result in poor data graphics in my opinion.

[Lisa · Rating 3 out of 5]

One of those design guides that is super useful for when you need it but not something you’d need to read end to end.