by Martin Zaltz Austwick, a lecturer in data visualisation and programming at the Bartlett Centre for Advanced Spatial Analysis (CASA) at UCL, with an interest in cities and networks, having previously studied quantum physics and worked as a medical laser physicist.
I’m excited to be chairing a session on Data Visualisation for Public Engagement at the British Science Association’s annual Science Communication conference , which is in sunny Guildford this year. It’s not until May, but when you keen scicommers, academics, science journalists, students, museums people and scicurious freelancers sign up , you’ll need to tell the nice people that you want to come to our session  and not one of the equally awesome other ones, so I thought I’d get in ahead of time.
Data visualisation (aka “datavis”) is in the news constantly. The British Library are currently running an exhibition of scientific visualisation, books about visualisation and infographics sell by the truckload , and broadsheets  and tabloids  alike are running data journalism and visualisation blogs . What does this mean for public engagement with research, and science in particular? I’ve put together this session because I want to understand these issues. I’m a lecturer in spatial analysis and visualisation  – which means I teach students (mainly from an architecture or geography background) techniques for visualising “human” data (like demographics, transport , twitter data , research funding data) and models (networks, agent-based, cellular automata, neural nets). I think datavis is already having a massive impact in social sciences, but I’m a physicist at heart, and I am really curious about how this all works in the natural sciences.
To this end, I’ve put together what I think is a really exciting panel. Damien George  is the most focussed on communicating research outputs from natural science  – not only that, but his efforts to map the research landscape in physics  articulates what research is for both publics and practitioners. Andrew Steele  has done great work visualising government science spending with his Scienceogram , and continues to find ways to communicate and challenge science policy via datavis. Artemis Skarlartidou  has worked with communities in mapping potential sites for nuclear waste disposal, and has particular expertise around building trust through visualisation. Together, I want to explore what I think are key questions about datavis – what can it articulate that other ways of communicating cannot? How can it be used for meaningful engagement? Who can use these tools? What opportunities are we missing? And what are the limits of these techniques?
But of course, it won’t just be the panel doing all the talking. Each panellist will discuss datavis in general, and visualisations they’ve worked on, for about ten minutes each, leaving a generous 45 minutes for a decent discussion – technical, ethical, practical, or otherwise. Because datavis is fairly current, I’m expecting a lot of interesting views in the room – but we don’t require attendees to be experts, so even if you don’t know the right end of a visualisation from the wrong one, come along to question, debate and see what the fuss is about.
The session runs from 3.30pm on Thursday May 1st - I hope to see you there.
If you’re a newcomer, I recently wrote a post recommending some introductory books , as well as one which has my thoughts about which languages you might consider using  if you want to get into the nitty-gritty programming side of things.