This is definetely a word I’ll remember: data visceralisation.
The term is suggested for data visualization in virtual reality, so that people can better experience differences in data, understand them viscerally.

It is something that I think definitely is useful, not just in virtual reality but also in making data visualisation physical, which I called ‘tangible infographics’ in 2014. You switch the perspective to one or more other senses, thus changing the phenomenological experience, which can yield new insights.

In both, tangible infographics and data visceralisation, the quest is to let people feel the meaning of certain datasets, so they grasp that meaning in a different way than with the more rational parts of their mind. (Hans Rosling’s toilet paper rolls to convey global population developments come to mind too).

Benjamin Lee et al wrote a paper and released a video exploring a number of design probes. I’m not sure I find the video, uhm, a visceral experience, but the experiments are interesting.

They look at 6 experimental probes:

  1. speed (olympic sprint)
  2. distance (olympic long jump)
  3. height (of buildings)
  4. scale (planets in the solar system)
  5. quantities (Hong Kong protest size)
  6. abstract measures (US debt)

The authors point to something that is also true for the examples of 3d printed statistics I mentioned in my old blog post which are much less useful with ‘large numbers’ because the objects would become unwieldy or lose meaning. There is therefore a difference between the first three examples, which are all at human scale, and the other three which aim to convey something that is (much) bigger than us and our everyday sense of our surroundings. That carries additional hurdles to make them ‘visceral’.

(Found in Nathan Yau’s blog FlowingData)

At Re:Publica in a session on data visualization to make sense of globalization, the release of a very cool dataviz project was announced for next week: The OECD Regional Well-Being Index. ‘Truth and beauty operator’ Moritz Stefaner, who contributed to the visual aspects, made this announcement during the session and gave a sneak preview.

It is a follow-up of the OECD Better Life Index (also very cool), and a new incarnation of the statistical regional explorer.

What it allows you to do is explore regional data, on the basis of what you deem relevant, and then find out which regions in other OECD countries have similar profiles. This is important, as until now OECD data was mostly presented on national level, but the more profound differences are usually found within a country, or when comparing regions, not countries.

If you do such a comparison for Berlin, as shown in the pictures, you find out why Peter Rukavina likes Berlin so much: it is statistically similar to his home Prince Edward Island, just more urban and with a wider variety of things on offer.

Re Publica 2014 Berlin
Berlin, with Prince Edward Island mentioned as similar region

Re Publica 2014 Berlin
PEI, statistically similar to Berlin

The existing OECD Regional Well-Being Index is already a great and beautiful project. It moves away from ranking countries, as that has no real meaning (in the sense of scope of interventions or policy consequences). You can create your own set of important indicators, and your choice as well as those of other visitors is used again as data to improve the visualization of the project itself. The top layer of the index is playful, and doesn’t throw all of the statistics in your face at the beginning. If you want you can dig much deeper and get much richer detailed numbers.

For more OECD data visualizatons see their Data Lab. Also check out the dataviz portfolio of Moritz Stefaner, who created the key elements of the OECD visualizations.