How can we take inspiration from textile dataviz?

I first wanted to call this post “What is steganography?”. I chose against it, because this post acts as a review of “Record, Map & Culture in Textile Art” by Jordan Cunliffe, a book I have had the pleasure of reading and taking inspiration from. And I didn’t want the subject of this review to be hidden behind what might seem to be a more cryptic title question. So, we’ll come to steganography soon, and my reason for initially considering it the key subject of this post. But let’s return to the book itself.

The first thing that you will notice and appreciate about this book if you are fortunate enough to have a copy in your hands (literally) is that it is tactile. Textured, in fact. I’m not sure if the cover is baize, or suede, or an artificial material of some sort. My ignorance of fabric and textiles is already pretty evident here, and we haven’t opened the book yet. But it’s a book you can stroke – how cool is that?!

From a personal perspective, the moment I can specifically recall that I became hooked on data visualisation was when I realised that data visualisation didn’t have to just be a traditional 2D medium – a computer screen or a print/drawing on paper. Though several years on those two media remain pretty much the only media I have dabbled with, I was instantly struck by the realisation that inspiration and practical creative examples took such a wide variety. That dawning for me was this 3D necklace by Miriam Quick and Stefanie Posavec, representing data quality emissions in Sheffield. From that moment on, I knew that possibilities were almost endless!

And so I already knew that textile data art, including Jordan’s work in particular, would appeal to me. If you were to sum up the kind of creative visualisation that most represents my own favourite style, both in terms of visualisations I appreciate consuming most and those I enjoy creating, they would probably have the following characteristics: static, geometric, grid based, eye-catching, disaggregated representations of data. Sometimes the encoding would be obvious, but often it would be abstract or even tenuous where design and visual appeal is more important than underlying data. Something that would, in my opinion at least, look good as a large, printed poster. For me, textile data visualisations are likely to tick most or all of those boxes. After all, it is a (not well enough known) fact that the iconic “warming stripes” visualisations developed by Ed Hawkins and used globally to highlight rising temperatures were inspired by a crocheted blanket of temperature stripes.

In Record, Map and Capture, the book is divided principally into three sections: 1. Data Visualization, 2: Steganography and 3: Algorithms. The Data Visualization section of course begins by explaining the concept of data visualisation to those less familiar, with a number of examples of Jordan’s work interspersed with works from other contributors. In addition, we learn and appreciate the time and craft that has gone into each creation. This brings an additional element of data humanism into the work. As a consumer of each piece of textile data art, contemplate the process of creation, not just the end process – something we are far less likely to consider when viewing more traditional online data visualisations.

For example, this pair of images from “Overlapping Lives”. The work is described and featured within the book, although this pair of images comes from Jordan’s portfolio website at https://jordancunliffe.co.uk/home/work as they better depict the detail than my phone camera can do from physical book page photos – the appreciation of every hand-stitched datapoint emphasises the human dimension of “time taken to create” alongside the more standard representations of dimensions of quantity and area depicting time.

As mentioned in the intro to this blog, it’s the introduction and definition of steganography that further struck a chord with me. Steganography is defined as the act of concealing secret information within something public, in order to avoid detection, in other words hiding something in plain sight. Jordan mentions that she was working in this way before she even knew the word, and that is something I can very much relate to. In terms of data visualisation / data art, steganography in this sense is representing data that has first been coded, and then had additional visual encoding applied in order to depict in visual form, to the extent that the data behind the final visualisation is not interpretable without additional deciphering. This further allows us to appreciate the final visualisation piece knowing that it is encoded using data, and we are deliberately encouraged either to do more work to understand the data behind the piece … or to do less work by simply appreciating the aesthetics of the final piece. Here’s an example from Jordan entitled “Scrabble Alphabet” where every coloured bead represents a different letter of the alphabet.

I can relate that to some of my own visualisations that I have enjoyed creating the most, such as Truchet tiles, where I used a complex (and almost arbitrary) coding system to encode the first few words of a number of classic literary texts in mosaic tile form. Below was my “how to read” page to decipher each mosaic – I’ve detailed the process and shown the final visualisations in my blog post and book chapter.

I also want to shout out one of my absolute favourite pages of the book. Yes, a small section devoted entirely to graph paper, for the user to use or copy, followed by some sample codes and ciphers such as Morse code. I love that this is included, whether as inspiration or for practical use! So many of my personal favourite projects start with graph paper, where I design my grid layouts and tile maps. Textile visualisations require the forethought of design stitch by stitch, in the same way that static visualisations can be planned pixel by pixel – this is another nod to the common mindset of textile visualisations and static poster-style geometric visualisations.

I would love to say this book has inspired me to take up cross-stitching or weaving in the name of dataviz. I have to admit that’s unlikely – my previous attempt at cross-stitching over forty years ago didn’t hint at a great unfulfilled talent in the field. However, I should add, that in addition to the sections described above, if you are interested in taking it up, the book offers practical advice on how to get started, and which kind of materials to use. 

The book’s conclusion states that the aim of the book is to “encourage you to find a new and playful means of storytelling using your personal data.” And I can vouch for the fact that the book achieved its aim. For me, that means the inspiration to return to the viz styles I love. A return to eye-catching, disaggregated visualisations, often showcasing data humanism examples. A return, though I didn’t know before I read this book that it was somewhere I’d been before, to steganography.