A significant obstacle needed to be overcome before the team could get to work. ECESR's data was all in Arabic. The data scientist working with the team had to partner with her Arabic-speaking teammates to translate and subsequently recategorise the data. At first there were 100s of possible variables, but the team was able to regroup these and find the stories at the heart of the statistics.
Right off the bat the focus was on finding stories that could explain the insights provided through analysing the data. The team had different entry points for different target audiences, and came up with strong concepts involving CSS animations and drill-down filtering that could be applied on-the-fly.
From sketch to story
On the left you can see one of the stories the ECESR team uncovered in the data. They've highlighted the important words, and then simplified the narrative to present it in visual form. The visualisation is dynamic and provides the user with a way to engage with the data and drive their own story.
This closeup of one of their working documents shows the first time we're introduced to the idea of giving each protest event a 'pixel' (or two). These pixels are then manipulated by adding or removing filters, changing time periods, or focusing on specific protest groups. It was wonderful seeing this idea moving gradually from paper to screen over the course of the workshop.