Ponder this… You’re teaching a class or educating a group and you want to use something visual (perhaps interactive). Should you go for the sandwich or the onion approach?
Let’s come back to that analogy later!
In my opinion, evolutionary leaps in the way information has been visualised has contributed to leaps in knowledge and understanding. Whether you subscribe to the concept of learning styles (or one or more of the many variants thereof) or swim against that tide based on the lack of study-based evidence is, in this case, irrelevant. The point of visualisation is not primarily to assist greater understanding by being more visual, but to do so by making complex connections, components and patterns more digestible.
For this main part of this blog entry, which serves to make you aware of some cool useful stuff out there as well as give my thoughts, I’ll be making use of visualisations from Places & Spaces: Mapping Science, a curation of visualisations by the Cyberinfrastructure for Network Science Center or CNS (snazzy name, eh?)
To back up my thoughts on this, let’s start with some of the earliest visualisations which attempt to compile a lot of information in a spatial way: maps.
Maps of the New World helped the average European to bring the discovery of America out from a fantasy and into a concept they could see and grasp. It is argued that mapping America created it’s own positive feedback: the more that was mapped, the more people were encouraged to colonise the new land, which boosted the need for greater and more detailed mapping… (Not to forgot all this being to the detriment of the natives. So perversely, visualisation and mapping helped destroyed many cultures, and not just in America).
So now to have a look at some of my visualisation picks from scimaps.org. I enjoyed spending the time browsing their catalogue, not just to see potential teaching resources, but also purely for my own fascination. I strongly encourage you to browse its map collection yourself to see what floats your visualisation boat. I think there is a lot there for teachers of many subjects, particularly Maths, Science, Art, History, Geography, Philosophy…
Clicking on the title below each visualisation will take you to the scimaps.org website where you can read more about it and zoom into a high resolution image.
So they are all my favourite ‘static’ visualisations. Now onto the interactive ones. These visualisations are part of what are called macroscopes. Rather than penning a definition, I think the way IBM uses the term is more helpful instead:
In five years, we will use machine-learning algorithms and software to help us organize the information about the physical world to help bring the vast and complex data gathered by billions of devices within the range of our vision and understanding. We call this a “macroscope” – but unlike the microscope to see the very small, or the telescope that can see far away, it is a system of software and algorithms to bring all of Earth’s complex data together to analyze it by space and time for meaning. – IBM Research
Macroscopes are increasingly becoming a major component to the newest visualisations, thanks to big data in particular. Here’s some for you from scimaps.org, but to get the full benefit of each, you’d best go play with them!
Earth. This really is a thing of beauty. Since the pioneering platform of Google Earth, there have now been numerous but more specialised off-shoots. This one from nullschool in particular focuses on atmospheric and oceanic patterns. It’s not as flashy or complex as Windy, but that’s its charm in my opinion. Just don’t stare at it too long; it’s hypnotic (for the right reasons!)
Here are a few more macroscopes that you may find interesting or useful:
AcademyScope – If you are an active researcher or like dipping into the more academic literature of something that interests you, this interactive database will show you the wealth of journals and publications (and their links) in each area of study.
The GDELT Project – To quote the website: Supported by Google Jigsaw, the GDELT Project monitors the world’s broadcast, print, and web news from nearly every corner of every country in over 100 languages and identifies the people, locations, organizations, themes, sources, emotions, counts, quotes, images and events driving our global society every second of every day, creating a free open platform for computing on the entire world.
CultSci (then click on ‘nature video’) – An excellent video charting and visualising cultural links. You can go into more depth by reading up about the study by clicking on the links under the video.
There’s an app for that!
If you want to play around with visualisations on your smartphone… well, there’s an app for that! Check out the highly rated Information Visualization MOOC Flashcards for iPhone and Android.
Back to the sandwich and the onion…
This analogy particularly resonates with me, as I am a fan of visualisations that allow you to turn on and off different layers and components (GIS for example). How you utilise these layers can make a difference to how well the visualisation is understood by those trying to interpret it.
The ‘sandwich’ approach is to have everything in a visualisation turned off at first, so the only thing you see to start with is the base layer (like a street map) or the foundation information. Then, once you’ve grasped that base layer/information, you then turn on another layer, and interpret that in relation. And again if there are more layers available. The base layer is the bread, the information layers, keys, legends etc are the filling.
The ‘onion’ approach is to start by having everything in a visualisation turned on first. Everything including any labels and keys are already visible. Then you turn off one or more layers at a time until you see something you can interpret. Once having the hang of that, you can turn layers back on again.
The City of London interactive map is an example of the ‘sandwich’ approach. You start with a base map and then you can click on individual layers to turn them on and see where their features are located.
This Norfolk (UK) highways map however is an example where all the layers are turned on to start. With this approach you have to interpret the key and the labels first and deconstruct (peel the onion) from there.
Which method do you think is more effective in helping users to understand and interpret the visualisation? Well, studies suggest that the sandwich approach works best. With the Norfolk highways map, I can certainly see that with all the layers turned on to start with, people could confuse the parish boundaries (in grey) for roads, given the title of the visualisation. Onions make us cry anyway…