Le Confident

Ideas tête-à-tête

Knowledge Design

As part of my PhD thesis, I’m juggling with the problem of instructive illustration. Have you ever experienced, how a single picture in a textbook can make learning some complex material a matter of a few minutes? The problem is, this is generally a very hard thing to do, because the artist has to do the abstraction in his/her own head and then find the appropriate visual representation, that is both beautiful and correct.

One of the most striking expriences I had in this respect, was reading the first 7 books of Euclids Elements, illustrated by Oliver Byrne in the 19th century. You might know that greek philosophy in general and greek instructions in maths all the more so, are quite a mind-bending read, mostly due to ancient-greek pecularities of syntax and wording. But looking at these illustrations you know instantaneaously what is going on and what is more, you remember the concepts in the form of the illustrations: primary colors, primitives and easily memorizable quantities of visual information: 1-4 different things at once.

Byrne_Angles Byrne_GoldenProportion Byrne_Circle in Square

Another quite compelling figure was Fritz Kahn, first half of the 20th century, who tended to illustrate the workings of the human body and nature by creating metaphors of it as a machine. Some of his drawings are memorable, but they also became obsolete far easier than Byrnes work, given todays possiblities in exact microscopic representation of tissue, cells, and cuts through different parts of our anatomy.

Fritz Kahn - Photosynthesis

Fritz Kahn – Photosynthesis


Fritz Kahn - Veines

Fritz Kahn – Veines


Today of course, snap shot illustrations of individual concepts are as important as ever. But an increasing number of concepts nowadays, are in fact combinations of a number of elements, which can by no means be illustrated individually. Their main qualities even, are relationships of stochastically significant quantities, sometimes not even exactly describeable  So once again I find myself talking about complex systems.

We’ve all seen network graphs, most of us are even using such information to understand what is happening behind the scenes, when we’re going online and presenting our work and lifes to the global village. And the most interesting parts of technology and science take similar shapes: what happens to a computer program after a billion iterations? Can a picture be detected by a computer given such an amount of processes? How many possible stable states will a combustion system have? Where will a limnological system find it’s equilibrium given the output of a nearby large city and so on. The point being, that on such a level of abstraction, predictable effects can be found and many carreers focus on work being done exclusively at this level. Complexity has become a thing to understand, a technical skill if you will. Of course, we have visual representation of data and concepts in textbooks and research papers, but what about the rest of the world? Do kids learn in school about this? Can the layman read a 150 page manual “for dummies” to quickly glimpse what is going on in considerable parts of modern development? It is being done, but not in the same compelling way, in which trigonometry can be taught for example.

Yesterday, Leonore pointed me to an artist, who works exactly in this field. I’ve talked much about scientifically inspired artists lately, but this is entirely different. Tatiana Plakhova works by hand and illustrates complexity. Her results are beautiful, and make you wonder, what it is, that she’s showing you. And when you get deeper into the material, you find out, that it is the essence of our time: networks, connections, interdependence, complex systems and algorithmical approaches to handle them and enhance the scope of human possibilities. What I like about art, is when it gives you a beautiful summary of a culture’s thoughts and dreams. Einstein is attributed with the saying, that humanity is guided by beauty on the way of discovery and this is where I see the artists role in society. Take a look at her style:

Tatiana Plakhova - 1

Tatiana Plakhova – 1

Tatiana Plakhova - 2

Tatiana Plakhova – 2

Tatiana Plakhova - 3

Tatiana Plakhova – 3

Tatiana Plakhova - 4

Tatiana Plakhova – 4


Some of her work, like the last, make use of measurement tools. Leonore showed me another artist, who focuses on the aesthetic of measurement. This of course is also central to today’s sensibility: Joe McDonnell:

McDonnell - 1

McDonnell – 1


Like we saw with Walter Valentini, exactness is in itself beautiful:

McDonnell - 2

McDonnell – 2


But I’m asking myself something else. Being exposed to all kinds of complexity and this includes croud sourcing, twittering, flash mobbing and so on, we must learn above all to adapt quickly to different kinds of problems and situations and processing everything with a set of core functions. Those change only slightly, and slower with growing age. For the moment this is a biological necessity. So one central aesthetic aspect of your daily life and our research, is an erratic, jumping perspective. Insight grows, whith the number of possible vantage points you can take in a minimal amount of time. I wonder, if this gives us a clue for next generation knowledge transfer. Imagine something like a basic logic class, a general education primer and let’s say a 3D interactive environment, where you solve a communication problem quickly in many possible ways. “Make a person happy” or “win an audience” and then you express yourself in words, different languages, different technical jargons, musical styles, in drawing and video, trying to evoke the same effect in your target in all of these. Next generation knowledge design would need to focus on this flexibility.

With this in mind, let’s enjoy a video featuring Tatiana’s work:


Artist’s Pages:

http://metamorphicillustration.com/ – Joe McDonnell

http://www.complexitygraphics.com/ – Tatiana Plakhova


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This entry was posted on March 18, 2014 by in Art, Design, Natural Sciences and tagged , , , , , , .
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