February 27, 2020

So much more to see in the data at the first #datavizlive (part 1 of 2)

By Paul Laughlin

This week I had the pleasure of attending the first #datavizlive event to be run in London. There was so much good stuff there that I’m spreading this debrief over two blog posts.

I’ll confess to being drawn to the event by the big-name headline speakers. These included Data Viz gurus Andy Kirk, David McCandless and Cole Nussbaumer Knaflic

But, as is often the case at this sort of event, despite those experts delivering great presentations, I gained as much from the other practitioner speakers and the opportunity to network. It certainly was a buzzing event with several hundred packed into Propero House near Borough station in London.

Anyway, here are my very subjective highlights.  No offence is intended to those whose sessions I did not attend or recall, there really was so much good stuff to take in. These are just the memories that stuck with me, to give you a flavour of this visualisers‘ jamboree…

Kicking us off with the London Tube Map

Andy Kirk, in his familiar no-nonsense down to earth style, launched this event by helping us reflect on the London Tube Map. He made the case for how this might be one of the best designed Data Visualisations in regular use today.

As Andy walked us through the many clever & carefully designed aspects of this visualisation, he also pointed out the irony of its name. Consider for a moment how the London Tube Map is not limited to London, not limited to underground services & not a map!

Despite this, Andy helpfully walked us through the history of developing this visual design (improving on earlier map based versions). Seeing the use of colour, positioning, iconography & layers all gave me a new appreciation of this design classic. I often don’t even notice the gridlines that form a key for the alphabetic list on the reverse.

My abiding memory though was Andy highlighting the slightly different versions used at different places. The horizontal representations on the trains, the added details on large versus small versions & the added layers on a printed copy. It reminded me of the importance of considering where your Data Visualisations are going to be used. Do you need to produce different variants for different contexts? Echos of the learning from my review of the Mobile Mind-shift book.

Andy is a very engaging presenter. To benefit from more of his Data Viz wisdom, check out the 2nd edition of his book:

Data Visualisation

A handbook with exhaustive examples of beautiful visuals.I found most visuals shown are, to say, modern. They are not quite suitable for orthodox business reporting which I am in. I feel that researchers, journalists or bloggers working with big data will find this book very useful.

Don’t forget the story as well as the pictures

With her own unique and important voice in the Data Viz community, Cole was up next and helped us reflect on the power of story. On the importance of words as well as pictures.

Cole started off brilliantly with a parody of a classic boring business presentation. We all laugh because it is sadly still all too familiar. Text-heavy boring slides with lots of bullet points & too much information to see any clear message or relevance to me.

She brings a passion, drama & people focus to improving even your most basic Excel charts. Cole shared her personal stories, including lessons from her young son reading “Larry gets Lost“. A really helpful reminder that a captivating narrative is often needed, as well as a clear visual presentation of the data.

Cole reminded us of the importance of being clear on your audience & your key message. Building on a greater clarity as to their need, how can you craft a narrative arc? How can you use visual highlighting to focus eyes on the most relevant data?

I also had the opportunity to spend the next day on Cole’s ‘Storytelling With Data‘ training course and she is a great trainer. A woman who walks her own talk in terms of using story, repetition & pictures to communicate clearly and help you retain your knowledge.

Check out her workbook, that you also use during that training course: so it really is a training course in a book:

Storytelling with Data

My knowledge of art, design, and how to craft compelling stories pales in comparison to my technical knowledge. As a data scientist, I found the lessons in this book invaluable. No longer shall I waste endless hours toying /testing graph layouts, I now have a systematic approach to communicate results.

Take your pick, streaming the #datavizlive faithful

Next we had opportunity to split into streams, covering one of:

  1. Data Literacy & Leadership,
  2. Story Design & Impact,
  3. Technology & Skills.

The diversity of those topics is an interesting reflection as to the breadth of interests in this audience. Each stream was popular.

As I mentioned in my book review of Alberto Cairo’s “How Charts Lie, there is a crying need for greater graphically amongst today’s leaders. So, I was very glad to see the first stream and promptly attended that to hear from the Bank of England (BoE).

Getting more views than the photos of Mark Carney

That title refers to the achievement of Lyndsey & her team in improving the data visualisations published by the BoE. Lyndsey Pereira-Brereton is Data Visualisation Editor for the BoE and very candidly shared how far they have come. The volume of charts being produced was staggering but the problems all too familiar.

Believing they were producing charts for a technical audience, the graphs were overly complex, busy & painfully technicolour. It was encouraging to see Lyndsey and her team not only produce better examples themselves but also influence a strategy change in the organisation.

As part of their Vision2020 strategy, they are successfully delivering Data Viz education across the organisation. This internal approach is built around the need to think carefully about your audience & approach with respect to:

  • Having a clear Story
  • Selecting an appropriate Chart Type
  • More sparing use of Colour to draw attention
  • Adding Labelling to explain key points
  • Tidying up all the other Numeric aspects (declutter)

I encourage other leaders to think about how they could take a similar approach to embed better Data Viz thinking in their culture. Here is Lyndsey’s summary slide of that strategy:

How to design a good chart (5 aspects)

Checking out the DataViz tools in space

Sorry, it’s not a DataViz version of the muppets Pigs in Space (wouldn’t that be great!) But, it was a much-needed updating of my technical knowledge.

During my own data viz training courses, I am often asked for a view on which data viz tool to use. Although I deliver non-tool-specific principles-based training, it’s worthwhile keeping better abreast of the market (that weather eye I’ve mentioned before).

So, I attended this helpful workshop in the Technology track at which Lars presented his overview. Lars Verspohl is the Owner & Designer of agency Datamake and shared with us his independent view of a number of tools.

Lars did a great view of positioning the different “less commercial” tools available (i.e. beyond Tableau, PowerBI, Qlik and the like). This filtering was very helpful, as so many market overviews are dominated by spending time obsessing over small differences between them.

What sometimes gets neglected are the free to use, or at least freemium to get started, tools. At the other end of the spectrum, nerdy blogs can go into so much technical detail about the latest data viz package for R coders, that it puts off all but the most knowledgable coders.

So, it was encouraging to see Lars position his view of all the tools he covered on a simple scatter plot. Using the axes of complexity versus expressiveness was helpful. You could consider you’re readiness to face a greater learning curve in order to achieve more capabilities to express the data or capture viewer attention with a wow factor.

Another useful aspect to the way Lars talked through each tool & placed it on his scatter plot was his groupings. He divided the market into these types of Data Viz tool:

  • Coding languages (R, Python, Julia, Scala) libraries = including the supreme D3, but also ggplot2, Altair & others
  • Non-Coding tools (Data Illustrator & Charticulate)
  • Online templating tools (Flourish & DataWrapper)
  • Web GL based tools (Pixi.JS, Deck.GL, SandDance)

I learnt a lot and definitely intend to try using Flourish more in practice. They were also exhibiting at this event and it was useful to see more of their tool in usage there, to grasp its ease of use & potential.

As a very brief overview, there is Lars’ simple subjective positioning:

Data Viz ‘tools in space’

Watch the next thrilling instalment of #datavizlive for…

Hope you enjoyed Episode 1 (hopefully better than most Star Wars fans did the equivalently named film). I said I’d be splitting this over two blog posts, so what can expect from part 2?

Well, still to come are debriefs on these engaging sessions:

  • User Testing your Data Viz (from Caroline from Dataveyes)
  • User-centred Design in Data Viz (from Emma Cosh)
  • Emotional Data Viz (from Xaquin, former Guardian graphics editor)
  • Data Is Beautiful from the famous David McCandless

So, lots still to hear about & I will try and do justice to the main learning points from all four. Hope to see you back here soon…