To quote my good friend, speculative architect Liam Young “Data Dramatization, as opposed to data visualization, presents a data set with not only legibility or clarity, but in such a way as to provoke an empathetic or emotive response in its audience.”
The following text expands on Data Dramatization in context of my own practise.
To dramatize data, you must first understand it. You analyse it, play with it, try to find relationships, try to infer the events that took place, and extract stories and meaning.
And then you throw it all away. Chuck it in the bin, and wipe your hands clean. All that’s left is your understanding of the processes that gave rise to the data and the events and relationships within.
Then you create something new, from scratch perhaps, inspired by those same underlying principles and rules and processes that you've just discovered.
Your motivation is not to tell the story of what happened in that particular instance, the story of the specific events that gave rise to that particular dataset. Your motivation is first to understand and absorb what happened, and then communicate what is happening. And more importantly, what that means to you. You create a fiction which is driven by those same processes that you've just discovered — at least the aspects of those processes that you select, as is relevant to you. You may or may not use any of the original data. You will probably generate new, fictitious data, to tell the story you want. This new data will be generated through similar — perhaps simulated — processes. These simulations might be supported and shaped by not only quantitive research and data, but qualitative research and data too. You might project these newly discovered processes into a different context. You might even inject them into another story, from another time, another dramatization.
You create an abstraction, a personal interpretation, of the processes, not the numbers. You tell a story about the cogs and wheels that underpin the events that gave rise to the data, not the events themselves. You create a behavioural abstraction, not just a visual or sonic one. This also isn't a data fiction. You’re not just telling a fictional story through fictional data. You’re inventing a new context for a fictional story, with fictional data — inspired by real life stories, events and processes.
In that respect, the scientific value of Data Dramatization in proving or disproving hypotheses is likely to be close to zero. It’s purely a subjective, artistic endeavour and should be treated as such. It is as functionally useful for shedding light on scientific research as is sitting on a cliff watching the sunset refract through the spray generated by giant waves crashing on the rocks below.
It’s simply a view onto the world, using the tools of science as a lens, to draw inspiration from the processes that shape our lives. And through visual, sonic and behavioural metaphors, create artefacts that reveal, extract, amplify and abstract the unseen harmonies and tensions found within.
Thank you please.