Tag Archives: data-driven science

New paper: Locative media and data-driven computing experiments

Sung-Yueh Perng, Rob Kitchin and Leighton Evans have published a new paper entitled ‘Locative media and data-driven computing experiments‘ available as Programmable City Working Paper 16 on SSRN.


Over the past two decades urban social life has undergone a rapid and pervasive geocoding, becoming mediated, augmented and anticipated by location-sensitive technologies and services that generate and utilise big, personal, locative data. The production of these data has prompted the development of exploratory data-driven computing experiments that seek to find ways to extract value and insight from them. These projects often start from the data, rather than from a question or theory, and try to imagine and identify their potential utility. In this paper, we explore the desires and mechanics of data-driven computing experiments. We demonstrate how both locative media data and computing experiments are ‘staged’ to create new values and computing techniques, which in turn are used to try and derive possible futures that are ridden with unintended consequences. We argue that using computing experiments to imagine potential urban futures produces effects that often have little to do with creating new urban practices. Instead, these experiments promote big data science and the prospect that data produced for one purpose can be recast for another, and act as alternative mechanisms of envisioning urban futures.

Keywords: Data analytics, computing experiments, locative media, location-based social network (LBSN), staging, urban future, critical data studies

The paper is available for download here.

New paper: Big data, new epistemologies and paradigm shifts

Rob Kitchin’s paper ‘Big data, new epistemologies and paradigm shifts’ has been published in the first edition of a new journal, Big Data and Society, published by Sage.   The paper is open access and can be downloaded by clicking here.  A video abstract is below.  The paper is also accompanied by a blog post ‘Is big data going to radically transform how knowledge is produced across all disciplines of the academy?’ on the Big Data and Society blog.


This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, history, economy and society. It is argued that: (1) Big Data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted; and (2) there is an urgent need for wider critical reflection within the academy on the epistemological implications of the unfolding data revolution, a task that has barely begun to be tackled despite the rapid changes in research practices presently taking place. After critically reviewing emerging epistemological positions, it is contended that a potentially fruitful approach would be the development of a situated, reflexive and contextually nuanced epistemology.