Why create an unnecessary data visualisation?

This post is inspired by this recent publication (note – I started and procrastinated on the post weeks ago, so I’ll edit this to “fairly recent”) publication from Andy Kirk. Many of you will know him for running visualisingdata.com with its regular feast of industry related resources, or will have benefitted from his book or training courses (right, that’s enough of a plug!). But this is very much a personal project (and not a project for personal gain, since profits have been donated to charities), which is billed as an “unnecessary data exploration”. Why would anyone undertake an unnecessary exploration? Surely the clue as to why not is in the title – it’s unnecessary, after all?

An “unnecessary” data exploration?

For my employer (and I have a new job, since my last post on here), I am involved in making necessaryvisualisations. Or, at least, visualisations that have been deemed necessary in discussion between our clients and our team. They help give insight, which enables our clients to make data driven decisions. All the things you have probably heard that data visualisations are supposed to do. These things drive me to do well, to promote best practices and to channel my time and experience into helping my clients. 

But outside of the professional environment, when exploring a new project it’s easy to get bogged down in how “necessary” it is. I think for me it’s quite obvious that I favour the unnecessary. Did we gain any new insight from 31 days of Flood? I doubt it – for me it was an exercise in creativity, expression and fun, and the aim for my audience wasn’t for them to glean anything useful from the fact that “shipwreck” was the biggest-scoring word in Scrabble, rather just for them to enjoy the visualisations for what they were, and to find (or re-find) joy from the album itself. 

And that can be the case even in visualisations with more serious topics. I’d give context to this example from the fact that as a data community challenge from Makeover Monday, there are always going to be a number of superb creations from talented designers that do a much better job of communicating the key takeaways. But that notwithstanding, my inclination was to explore a new graphical way of displaying the data. Inspired, as so often, by Sonja Kuijpers, I set about the challenge of emulating a new (to me) visual form of displaying data.


I am happy with the focus given to the important subject – as a passionate follower of the initiative to promote visualising gender inequality, I have participated regularly throughout. I’m happy also to negotiate the trade-off, that what a visualisation lacks in storytelling impact, it can gain in other ways through exposure via interest in its design or chart form. So, to me, unconventional design does not necessarily correlate to unnecessary data exploration.

Andy’s book is a reminder of fun elements to visualise. My unfinished visualisations that I’ve struggled to find the inspiration to complete through this year’s unique situation include those around my favourite book (and others in the series), personal “quantified self” data about me, and a chess tournament from the year I was born (which, readers, was not a recent event by any stretch of the imagination), along with a handful of others. None of these are necessary explorations (or necessary explanations – so we’ve covered both types of visualisation!). But these are what motivate me to get out of creative slumps and have fun visualising. And it’s when I do that, that blog posts ensue (eventually – even this post was started weeks ago!)

Here’s a visualisation I completed recently on the Hitchhiker’s Guide to the Galaxy. 

Yes, this is the “book” project I mentioned above. I’d prevaricated long enough, I know this probably qualifies as “unnecessary” – the very fact that I had to tell you what it was about shows that I admit it was not immediately obvious. But I’ve acknowledged that in order to overcome a creative block and to take inspiration from things I love. In this case, geometric style generated art, and my favourite book of all time. The art I mentioned comes from Saskia Freeke (@sasj_nl) who creates a daily image – every single one of these sparks curiosity in me, wondering if the ideas could form the basis of a data visualisation. Perhaps not surprisingly for me, it’s another example of “Design Driven Data”, which is a theme I have referred to many times when citing inspiration for my work. Some of Saskia’s examples are below – it’s easy to see where the inspiration for my viz may have come from!

I love being involved in data visualisation. The last couple of months, in particular, have brought our field to the forefront, through COVID charts and election maps, probably more than ever before. My advice for those of us looking for projects and ideas in such a high profile time for the field is twofold.

Either embrace the times and acknowledge the opportunities to be involved in such important global issues …

Or, celebrate the unnecessary!

Times are hard right now – we are all living through the protracted elections and global pandemics that our industry are visualising. And if your mental health benefits less from being immersed in these issues and more from escapism, then join me in visualising a wide array of meaningful or meaningless issues, in ways as conventional or unconventional as you enjoy most. And share them – there will always be those who enjoy your output. After all, I know very little about Seinfeld (when I received the book with a note addressed “Hello Nooooman”, I thought I’d got some other guy’s book – there, I’ve admitted it!), but I loved Andy’s joy and enthusiasm expressed through data visualisation in his book – and I know a little more about Seinfeld now!

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