We generate data all the time – using our phones, swiping our loyalty card, filling in yet another form or buying something online. But what’s our relationship to that data? What is data, what does it look like? Important questions in a time when we’re constantly hearing about its role in our lives.
So, it was good to explore some of this recently at the Producing Data symposium organised by the Design Informatics group at Edinburgh University. These are my digital notes-to-self rather than a comprehensive write up:
Hermann Zschiegner showcased some beautiful visualisations, in particular some work with Artsy, linking tagged art and artists to show relationships and influences – describing it as a genome project for art.
Wendy Moncur described her Emergent Framework for Digital Memorials which considers how digital memories now merge with physical memories. Interesting to hear how the process of exploring what constituted different types of memories appeared to be as important as the finished memorial.
Sophie Woodward from the University of Manchester described a great example of how work in a completely different field is raising the same questions that I’ve been grappling with for a while. She described her work on denim, considering the fact that many of us have a pair of jeans in our wardrobe. Jeans have data associated with them – where and when were they made and bought etc – and a gallery of photos of people wearing denim provoked conversations that, in turn, generated more data. This prompts us to think about the role of data as a provocation, a conversation starter – and how different types of representation might provoke different types of reaction. This chimes with me – the conversations we have around data are often more interesting than the data itself.
Sian Lindley talked about her work exploring what data means for the people living and working on Tenison Road in Cambridge. More interesting examples of collecting data and different ways of playing it back to people to inform and promote further discussion. Again, more questions arising about what kind of data do we capture? who ‘owns’ it and how best to represent it back to the community?
Finally, we played with some data ourselves, taking various sources without context and working in groups to construct a story around facts, figures, pictures and graphs.
A bit abstract? Maybe, but fascinating to talk as a group about the assumptions we make, the biases we have, the stories we are capable of making and the analytical skills we all have within us. Interesting to think about data sources we could use in different domains to explore how people react to varying data representations. What type of data visualisation creates the greatest assumptions?