We 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, 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 we 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 our 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

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.

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With our background in science, the highly analytical approach of Visualizing Complexity resonates strongly with us. 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. We’ll definitely browse through this book during future projects, to ensure we’ve covered as many different visual ideas as possible.

What we’re 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 too 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 our dataviz bookshelf – a must have for everyone who wishes to understand the analytical thought processes behind strong data visuals!

More dataviz book reviews? We have already covered:

• Dear Data
• Storytelling with Data
• Visualizing Complexity