Ecological data is usually abstracted away from the physical world for visualisation. This reinforces our detached relationship to the environment and removes the data from its original context: fuzzy, intimate and weird. This workshop will propose and collaboratively explore an aesthetic and pathway for ecological data visualisation that is rooted in the messy physical world.
We will discuss alternative ways to visualise datasets such as . For example, maybe to visualise the area of Amazon burnt last year, we can burn patches of grass with a magnifying glass. Maybe instead of an x-y graph of predicted sea rise, we can make films of ourselves doing tasks in different heights of water: seeing how hard it is to drink tea with water up to our ankle, to drink tea with water up to our neck.
Current approaches to ecological data visualisation are sterile and reinforce a remove from this vital data about our world. The goal of the workshop is to collaboratively imagine alternative ways of visualising ecological data that keep is connected to the subject.
We're hoping that many efforts and discussions will continue after Mozfest. Share any ideas you already have for how to continue the work from your session.:Some of the workshop will be involved with ideation. As the session ends, I will encourage participants to go and make some of the data visualisations we have thought of. Any results would be curated into a selection on the Radical Data Project site (https://radicaldata.org).
How will you deal with varying numbers of participants in your session?:I will start by introducing some thoughts I have had on the area as well as inspiring examples. This part is the same regardless of the number of participants. Then, the breakout sessions will be in groups of 3-4, again making it independent of the number of participants. The only part that will change is the length of the feedback and full group discussion section at the end which will have to be adjusted from between 5-15 minutes, depending on the size of the group.
Jo is a data scientist, artist and musician. They founded the data science consultancy Citizense, run the research program Radical Data and make dance music with code. https://jokroese.com