Data beautification, some ‘prototypes’

Recently, as we’ve been doing lately, had the Outbox Hub host us,  to talk about data visualization but also get our hands dirty creating data visualizations with the most unlikely tools- paper, straws, pens, bottle-tops, the floor and wall! The design inclined refer to it as designing data or making it beautiful. So we took a deep dive in.

We organized this mainly to discuss best practices, highlight worst practices from a design standpoint when creating data visualisations. The main goal here is to have your data communicate, clearly to your audience-it could be to children, teenagers or adults.

Take a look at some of the varying interpretations of the data:


Raw dataviz from the meet-up!

From the data design experts:

We had a great mix of design, communications and programmer experts to share their insight, with 25 people in the room: Joe Ssekkono a front end developer and visual artist gave a presentation explaining ‘what data visualisation is’ , ‘how to plan your data visualisation project’ and ‘evaluating and iterating your data visualisation project’. He went on to show us a step-by-step process of how to start data visualization, some tips & tricks, websites and handy software tools. You can find the complete presentation here.

Emmy Van Kleef a Creative Communications and Concepts expert talked about the ‘latest trends and available tools’, the ‘best practices and worst practices of data visualisation’.

ImageAdapted from Emmy Van Kleef’s Presentation

Eve Ndagire a graphics designer talked about what ‘categories of data you could visualize’ (is it linear, discrete, continuous or categorized/numerical)? There are several ways of visualizing data, for example using bar charts, histograms, graphs, maps, pie charts, scatter plots and sometimes very abstract methods. We decided to go traditional and practical, using non digital tools like paper, pen, straws, crayons, bottle-tops, the wall, table and floor.

The workspace was very busy as everybody worked away, trying to visualise crime and number of convicts in the major cities in Uganda. A break did not seem welcome to the participants. Take a look at the dataset we worked with.


This turned out to be an interesting topic, and there was demand for a similar meet-up with more emphasis on using digital tools/code/software to make data beautiful. We hope to explore some of the trending data visualization libraries in the future. This meet-up allowed us to create ‘prototypes’ which we’ll build on, the next time!


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