The little of visualisation design: Part 31

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns a sensible way of offering ‘help’ to readers of a visualisation. I’m referring to a project developed by Accurat in partnership with the Google News Lab called ‘World Potus’. This work was developed during the US Elections to track the popularity, trends and locations of topics people from outside the US were most interested searching about on Google relating to the Election.

It is often necessary to provide a degree of functional (how to use it) and perceptual (how to read it) guidance with a visualisation and often this involves maybe a ‘i’ or ‘?’ button taking you to a descriptive page of guidance. The problem with approaches like this (hands up, on reflection I’ve done this almost always) is that as a user/reader you are often taken away from the screen of interest. This makes the guidance somewhat detached and relies on your memory.

What I liked about the solution in this project was the way pressing the ‘HELP’ button simply overlayed the guidance on top of the screen you were looking at getting help with. This proximity cemented the instruction. Additionally, with a seamless switch on/switch off (or clicking ‘Got it’) you could quickly bounce between the help view and normal view without too much obstruction or delay.

The little of visualisation design: Part 30

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns the inclusion of tangible ‘call to action’ instructions/invitations. For this I’m referring to a project developed by FFunction for the ONE campaign titled ‘Making the connection: How the internet can help end extreme poverty‘. This work, presented as a scrollable visual article, explores the inequalities of world wide access to the Internet, focusing on the fact that ~75% of Africa is offline and, of those who are online, there is a clear gender disparity.

lovd-part30a

There are several aspects of design in this project I like but one small component that particularly struck me of interest was the inclusion (after having scrolled through about half the report) of a prominent ‘call to action’ event, initially in the page footer but eventually as the final stop on the scrollable path.

lovd-part30b

Not every visualisation has the intent of driving action to change behaviours, to change beliefs or even to directly influence immediate decision-making processes. Many can only, will only and need only aspire to inform, leaving consequential actions down to the capacity and appetite of the reader. However, when your purpose is clearly aimed at trying to motivate action then making clear what this action is through visible, obvious and seamless instructions is clearly clever thinking.

lovd-part30c

Again, your own work may not involve such tangible or simple actions (as in, ‘logging your email address’ simple) like this but, on those occasions when it is relevant, think about not just what you want your readers to learn from your work but also what you want them to do.

The little of visualisation design: Part 29

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns the use of small annotated marks to help draw a reader towards exceptional ‘values’. For the second consecutive #LittleVis piece I’m referring to work from the Financial Times, this time from an article titled ‘How prepared is Britain for extreme weather?‘ written by Oliver Ralph. The graphic is at the bottom of the page and was produced by John Burn-Murdoch. It looks at the patterns of monthly rainfall across Great Britain up to 2014 and going back to 1960. It is tall in dimension so this is just an excerpt from the top.

lovd-part29a

With such a dense display formed by 660 individual map panels, there is a lot for the readers’ eyes to process. Even with the known capability of the eye to efficiently scan such displays for the key patterns, it significantly helps the reader to include annotated markings (‘editorial overlays’), in this case colour-coded squares, to quickly emphasise the main periods of significance to this story.

lovd-part29b

12 notable US election visualisations

The (nuclear) dust settles at the end of a seismic week in history, as the fallout and angry finger-pointed fall outs continue to dominate the media and social media landscape, with people looking to make some sense of the non-sense by finding that single person or single thing that should be to blame. Pundits, pollsters, polling methods and data modelling techniques are certainly taking lots of heat. Data visualisation may not be directly in the firing line but I suppose there is a guilt by association.

The fact is, of course, that a visual and its underlying data carry a shared responsibility for understanding. A visualisation is only as good as the data it portrays. This principle stands just as important as ever today.

Given the deluge of different visualisations used during the build up, the event itself and now in the post-mortem phase of the election, it is understandable that some people have expressed severe fatigue from seeing so many election-related visuals (I imagine heightened by the outcome, for many). However, I do feel that we should acknowledge some of the excellence that has been produced during this period. After all, this is a 4-yearly event which, for many journalism organisations, represents the biggest platform to mobilise their focus and talents.

I have therefore picked out a collection of twelve projects that I’ve seen from across (some of) the journalism landscape (admittedly I’ve not seen or had access to ALL election graphic work) that I felt demonstrated the best of this art during this event.

I’m not going to provide design commentary for these, it’s more a collection of inspiration. However, the first project listed below does require some further analysis and I will follow up with a piece about the gauge chart specifically. The order of those listed is entirely incidental but loosely grouped around those used during and viewed after the election.

ON-THE-NIGHT

New York Times – Forecast Gauges

nyt-gauge

FiveThirtyEight – Snake Chart

538-snake

The Guardian – Election Dashboard

guardian-dashboard

Financial Times – Weighted Dot Map

(Inspired by The Guardian)

ft-dotmap

AFTERMATH

New York Times – Arrows Map

(Building on their previous work for the 2012 Election)

nyt-arrows

Washington Post – Vote peaks

wapo-peaksdetail

New York Times & Wall Street Journal – Scribble Plots

nyt-scribble

wsj-scribble

Financial Times – Tower Chart

Inspired by this 2000 Election Graphic by NYT

ft-tower

Wall Street Journal – Scatter Plot

wsj-scatter

STORIES

ABC – Story of the Night

abc-story

Financial Times – Video Explainer

ft-video

New York Times – Precint Stories

nyt-mapjourney

The little of visualisation design: Part 28

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns the use of reading guides to help the reader understand how to interpret the meaning of a heatmap display. The project in focus here was produced by the Financial Times and from an article titled ‘Frankfurt vies for UK banking jobs post-Brexit‘ and shows analysis of the presence of different banks across a range of major European cities.

lovd-part28a

To some readers, the task of parsing meaning through the colours at the intersection of two categorical variables can be a little tricky. Knowing this, the creators include a small guide above the chart (and therefore, through its placement, intended to be seen before reading) that quickly indicates the interpretation to draw from seeing specific patterns down each column and across each row.

lovd-part28b

7 innovative, interactive static visualisations

Hmmm, you’re thinking, this post title smacks of cynical click bait? “You won’t believe the ways people are interacting with static visualisations!” was the first option but I eventually toned it down. Anyway, as the title suggests, this is a small collection of five six seven innovative ways that I’ve seen applied to make static, non-digital visualisations become ‘interactive’ in different ways. I’d love to see other examples you might have seen too.

1. SCRATCH OFF GRAPHS

Developed by Stephanie Evergreen, these charts are printed on thick paper or card and then the category value labels are painted over using a scratch-off paint mix. This allows them to then be scratched off using a coin perhaps as the big reveal associated with asking people to guess the values associated with each bar.

nondiginteractives-scratch

2. THROWING A DART

A well-known piece by the Economist, this printable sheets uses the likelihood of a thrown dart landing in different red regions to represent the statistic of the likelihood of being murdered in different countries during a given year.

nondiginteractives-dart1

nondiginteractives-dart2

3. ASSEMBLABLE 3D STATISTICAL BALL

From the Times of Oman, this frankly incredible concept involves 32 international football team profiles that are printable, foldable and assemblable as truncated pyramids that collectively create the form a ball but individually display statistics about world cup performances that can be paired with other countries to facilitate comparison. It deservedly jointly-won the ‘best in show‘ award at the 2015 Malofiej awards.

1_ON THE BALL COVER 1.indd

4. PRINTED, LIFE-SIZED COMPARATOR

Produced by the Hollywood Reporter, this is a printable, life-sized outline of Donald Trump’s hand so you can overlay your own hand to measure up against the orange one’s apparently tiny paws.

nondiginteractives-trumphands

5. TACTILE WOOD MAP

I profiled these in a post from 2013 but worth including in this collection. The Inuit wood maps provide(d) a hand-held tactile mapped representation of the relief of the coastline of Greenland, allowing the Inuit to appreciate and identify the contours, islands and glaciers (etc.) of the coastline.

nondiginteractives-woodmap

6. DIY DATA COLOURING BOOK

Created by Chelsea Carlson, motivated by the sense of the US election debates causing people to stress out, this project allows you to download a colouring ‘book’ of three different data visualiation templates for you to record your data feelings as while you watch the debate.

nondiginteractives-colouringbook

7. POP-UP INFOGRAPHICS

Created by Elena Turtas, this project about ‘The Four Books of Visualising Sustainability’ covers important data relating to subjects like global warming, emissions, resources, forests, water, energy, food via the form of pop-up infographics that leap from the flat of the page, offering different interactive mechanics to play and customise the experience.

OLYMPUS DIGITAL CAMERA


It goes beyond just being interactive non-digitals but here’s a super collection of (currently 256) physical visualisations.

The little of visualisation design: Part 27

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns the inclusion of a ‘reset’ button. The project in focus here was produced by FiveThirtyEight and is titled ‘What Would It Take To Turn [Red/Blue] States [Blue/Red]?‘, offering an amazing (and rightly celebrated) multi-faceted tool to simulate the 2016 presidential election outcome based on the potential party preferences and turnout % of different demographic groups.

lovd-part27a

The main interactive operators exist as draggable scatterplotted marks, representing the turnout % (y-pos) and overall party voting % (x-pos) for several major demographic groups. When you reposition the point markers the red/blue state swings in the grid maps above are modified accordingly as is the overall outcome. As you change the positions a feint ghost marker is left behind indicating the starting values (I guess based on current polling).

lovd-part27b

I believe the inclusion of the ‘Reset’ button is of critical value here. In offering the means to intricately alter several value settings, it is very useful to be quickly able to return the state of an interactive right back to its starting calibration (and do it in a way that doesn’t require an inelegant browser page refresh). Surprisingly, I find this is an oft-neglected feature but certainly very useful.

The little of visualisation design: Part 26

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns small-multiple grid maps and a neat way of providing a state legend. The project in focus here was produced by Nathan Yau and maps the spread of obesity across the US over the past 30 years.

lovd-part26a

As you can see, in the top left there is a reference guide that explains which grid cell relates to which state. With any grid map there will always be some degree of state position/neighbour compromise so this helps the reader to immediately (being the first thing you logically see) orientate themselves before they then move through the sequence of yearly patterns.

lovd-part26b

This feels a far less repetitive solution and not as visually intrusive as it would be to include the 2-digit state labels in each map and in cell. I can imagine Nathan toyed with the idea of having cell borders around each state label but I like that he didn’t do this – it is sufficiently legible through just relying on white space.

The little of visualisation design: Part 25

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns the decisions involved when including arrows in your work to act as pointing or directional devices. A recent project that uses arrows comes from the Guardian, titled ‘Where is the riskiest place to live?‘ by Josh Holder, based on the world risk index. As you can see in the project there are several features of the chart that have associated captions, connected by arrows, to help draw to the surface some key or interesting insights from the data. (Note, there is a second use of arrows to indicate the general ‘Low’ or ‘High’ risk direction along the x-axis but I’m going to focusing on the ‘pointer’ arrows in the body of the chart.)

lovd-part25a

There isn’t an instruction manual for the most effective way to design and integrate arrows into your display. Instead, as with many things in data visualisation, it is about judging what will offer the most legible and elegant solution to suit the overall visual balance. There is a really nicely judged lightness to the visual weight of the arrows in this piece. They are short in length and consistent in appearance, which ensures they supporting the display not dominate it. Perhaps the most unusual feature is how the arrow head points towards the caption, rather than the other way round.

lovd-part25c

Arriving at the ‘best’ choice involves a surprisingly high number of decisions: What arrowhead* to use? What colour? How long/how far away should the caption be from the item of interest? What weight to apply to the line? Will it be straight or curved? Which is the start and which is the end? Where specifically to point the arrow to and where from? The next time you see an arrow, just remember how much thought has gone into what you might otherwise think is a straightforward choice.

(* Reminds me that Jane Pong ran a quick survey on peoples’ preferences for the arrows available in Illustrator)

The little of visualisation design: Part 24

This is part of a series of posts about the ‘little of visualisation design’, respecting the small decisions that make a big difference towards the good and bad of this discipline. In each post I’m going to focus on just one small matter – a singular good or bad design choice – as demonstrated by a sample project. Each project may have many effective and ineffective aspects, but I’m just commenting on one.


The ‘little’ of this next design concerns the challenges of handling long labels. In this post I’m possible breaking the theme of this series as I’m not so much offering a solution, rather more a ‘heads up’ to flag the possibility of this issue in your work. I’m referring to one of my own recent projects here, ‘Filmographics‘, looking at the ebb and flow of the fortunes of actors’ movie careers. As you can see in the screen shot below, when you choose an actor from the menus at the top an illustration of their face is displayed in the page body and their name is presented within this image.

lovd-part24a

The challenge faced in this case was judging the best font size for the actor’s name label within the (self-imposed) space constraint of the image width. We found a nice size for working with 59/60 values but then we had Arnie: at 21 characters in length, ARNOLD SCHWARTZENEGGER would be the single instance whereby the preferred label font size would cause the surname to be split over two lines. To make it small enough to accommodate Arnie would have the consequence of the name’s being (in our view) an insufficiently prominent title/identifier for all the other actors in the dataset.

lovd-part24b

In the end, with time running out, we made a decision to accept the rather inelegant compromise of sticking with our preferred font size that would be suitable for all except Arnie: ‘Good enough’, ‘It’ll do’ is often a call you have to embrace when time resources diminish.

lovd-part24c

With the benefit of hindsight we maybe could have looked to programmatically handle a custom font size for Arnie alone. We could also have handled the placement of the actor’s name entirely differently so as not to present us with a challenge of dealing with this spatial constraint. The main point to make here is to reinforce the importance of developing a deep and early acquaintance with all the physical properties of your data values, not just the range of quantitative values you’re facing but also the length of potential labelling assets.

It’s the little things like this that cause the big headaches.