Share on Facebook Tweet on Twitter Share on LinkedIn Share by email
[Big] Data Studies

Data is everywhere. Virtually everything is being treated as data. From consumer behaviour to cellular systems, from the health and care of our bodies to the ecosystems we inhabit, the world is seen to be suffused with data.

Nodes in networks

 This data-centric vision is enabling new discoveries and leading to implications –often significant – in the sciences, healthcare, social policy, and so on. The human genome, the modelling of fossil fuel supplies, global migrations, our tweets and Facebook likes, and even our quests for love and companionship have all been subject to intensive and sophisticated data analysis. The resounding problem has become not how little data there is, but how much we have (and what to do with it all). A turn has thus been made towards big data, data science, analytics and computation.

And yet alongside the productive developments in this turn to data, fundamental questions are raised about how we relate to the world around us and, ultimately, what we imagine ourselves to be. What is it to have a world where virtually everything is considered a source of data to be quantified and computed? What relations and contingencies must we assume and (re)produce to see the world as such? And, critically, what gets excluded from such a world? In what ways are we, in other words, performing an idea of the world (and our relations to it) over and above other possibilities.

In this research we aim to address these kinds of questions. The broad goal is to recover the kinds of entanglements that are put to work in seeing data, everywhere, and to explore ways of enriching and deepening this view.

We’ll be posting details about a new project we’re starting under this broad theme in the coming weeks. In the meantime here are a few articles and links that have helped us along the way:

Batty, Michael. 2012. "Smart cities, big data" Environment and Planning B: Planning and Design 39(2) 191 – 193

boyd, danah and Crawford, Kate. 2012. 'Critical Questions for Big Data', Information, Communication and Society, Volume 15, no 5, pp 662-679.

boyd, danah and Crawford, Kate. 2012. Six Provocations for Big Data. A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society.

Burns, Ryan and Thatcher, Jim. Whither Small Data?: The limits of “big data” and the value of “small data” studies. Session at Association of American Geographers Annual Meeting.

Crawford, Kate(March 2013) Untangling algorithmic illusions from reality in big data, O’Reilly Strata conference, Making Data work.

  • Tim Regan, David Sweeney, John Helmes, Vasilis Vlachokyriakos, Siân Lindey, and Alex S. Taylor, Designing Engaging Data in Communities, in CHI EA '15, Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, ACM – Association for Computing Machinery, April 2015.
  • Alex S Taylor, Siân Lindley, Tim Regan, David Sweeney, Vasillis Vlachokyriakos, Lillie Grainger, and Jessica Lingel, Data-in-Place: Thinking Through the Relations Between Data and Community, in CHI '15, Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, ACM – Association for Computing Machinery, New York, NY, USA, April 2015.
  • Alex Taylor, Jasmin Fisher, Byron Cook, Samin Ishtiaq, and Nir Piterman, Modelling biology – working through (in-)stabilities and frictions , in Computational Culture, November 2014.
  • Alex Taylor, Siân Lindley, Tim Regan, and David Sweeney, Data and life on the street, in Big Data & Society, Sage, July 2014.
  • Alex S. Taylor, Nir Piterman, Samin Ishtiaq, Jasmin Fisher, Byron Cook, Caitlin Cockerton, Sam Bourton, and David Benque, At the interface of biology and computation, in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM, New York, NY, USA, January 2013.