DRAFT ABSTRACTS: RESEARCH ARTICLES
Big Data, New Epistemologies and
Paradigm Shifts
Rob Kitchin, National Institute for Regional and
Spatial Analysis, National University of Ireland
This paper 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 big data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted and 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.
Big Data from the Bottom Up
Nick Couldry and Alison Powell, London School of
Economics
Contemporary societies are characterised by the way
that all large-scale processes of strategic management (whether by
corporations, governments or any other entity) increasingly rely on total
surveillance: that is, on the continuous gathering and analysis of, and actions
adjusted for, dynamically collected, individual-level data about what people
are, do and say (big data). Compared to representative sampling, this approach
to data collection is totalizing; it is also characterized by aggregation of
multiple data sets through the use of calculation algorithms. This seemingly
greater role for algorithms has led some commentators to focus on the
alienating quality of the resulting ‘algorithmic power’ (Lash), an approach
which leaves no room for agency or reflexivity on the part of ‘smaller’ actors.
We posit that the emerging culture of data collection deserves to be
examined in a way that foregrounds the agency and reflexivity of individual
actors as well as the variable ways in which power and participation can be
constructed. This article will offer a ‘social’ approach to the
construction/use of data and analytics. The approach improves on current
understandings of ‘big data's' theoretical and empirical qualities by thinking
through how the new aspects of this type of data are relevant for people, their
practices and their politics.
More specifically, the paper will explore,
schematically, some key sites of fieldwork intervention that emerge within such
an approach. First, work within a ‘social analytics’ approach (Couldry and
Fotopoulou forthcoming) which studies the uses by social actors of data
analytics of various sorts (whether generally available or customised) to
sustain the sort of digital presence they need to have and more generally to
achieve their broader social and civic purposes. Second, the study of 'data as media'
that connects with how people are talking about emerging internet
sensor-networks, and the questions about relative structural operations of
power (and indeed participation, when data is media) that can be empirically
investigated through around 'smart' cities, and emerging 'internet of things'
applications. Third, turning to the wider issues for power and its resistance,
we will discuss the increasing importance not just of voice (Couldry 2010) but
also 'visibility' or 'transparency' when we think about the particular
qualities of data as ‘media’.
Changing Topographies and
In/vulnerabilities of Techno-scientific Knowledge Production in ‘The Big Data
Revolution’
David Turnbull, Victorian Eco-Innovation Lab (VEIL), Faculty of
Architecture, University of Melbourne
The idea of accumulating everything, of establishing a sort of general
archive, the will to enclose in one place all times, all epochs, all forms, all
tastes, the idea of constituting a place of all times that is itself outside of
time and inaccessible to its ravages, the project of organizing in this way a
sort of perpetual and indefinite accumulation of time in an immobile place,
this whole idea belongs to our modernity. (Of Other Spaces, Foucault, 1967)
Contemporary databases, seen as the culmination of a long line of
various information technologies, might now be recognized as “perhaps the most
powerful technology in our control of the world and each other.” Memory
Practices in the Sciences, Bowker, 2005)
There is no political power without control of the archive, if not of
memory. Effective democratisation can always be measured by…access to the
archive, its constitution and its interpretation. (Archive Fever,
Derrida, 1995)
In a period of extraordinarily rapid transformation since around 2010
the advanced economies of the world have moved from the relatively immature
stages of what was once celebrated as ‘the information age’, ‘the digital era’,
and ‘the knowledge economy’ to what the IT trade boosters promote as ‘Analytics
3.0’[1] the ‘Fourth Paradigm’[2], the ‘Big Data Revolution.’[3] Now it is
claimed that the entirety of the events in the universe, can be digitally
recorded, quantified, assembled, mapped and analysed algorithmically, enabling
data mining and pattern recognition on the most massive of scales, which in
turn will reveal the answers to many questions including ones not yet asked.[4]
In addition to heralding a profound epistemic transformation in the
effort to create a panoptic archive the ‘Big Data revolution’ also seems
set to introduce massive economic, social and political transformations in
knowledge production, privacy, identity in the massive efflorescence of global
surveillance revealed by Edward Snowden. Economically the Big Data revolution
can be seen as analogous to the industrial revolution where labour and land
were accumulated through dispossession and enclosure of the commons. This time
the object of accumulation is another common good–the previously unrecognised
and unvalued asset class– data.[5] The world is undergoing the latest phase of
socio-technical change that Heidegger described as ‘enframing’– the continual
setting up, ordering, transformation and revealing of everything in the world as
‘standing reserve’– as something ready to be used, and to be transformed and
used again’. But now not only are ‘our everyday lives are turned into data, a
resource to be used by others, usually for profit’’ they are directly accessed
by the world’s security agencies in pursuit of total surveiilance.[6] As
Bruce Rich points out enclosure and framing have reciprocal meanings:
‘enframing has its historical counterpart in the interpretation of western
economic development as a process of enclosure’, and according to the OED one
definition of enclosure is to insert in a frame or a setting.[7] As ever the
terms and conditions of what it means to know and to interact are being shaped
by the technologies that provide communication and information.
Big data does not, of course, exist in isolation, it has come into being
in part through the development of the interconnective network made possible by
the internet, and through the ubiquitous invisible web of digitisation,
software, code, and algorithms that are the calculative framework and
infrastructure of modern society.[8] Big Data in combination with the internet
has generated a new knowledge space, a commons which initially held great
promise as a knowledge democracy in which everyone would have equal, unfettered,
rights, along with open access and participation in all there was to know. But
paradoxically, the interconnectivity and the generation of massive volumes of
data that make the augmented knowledge commons possible also create the
conditions for ‘digital enclosure’.[9] The forms of enclosure of the knowledge
commons are multiple, complex and emergent, but all serve to restrict access,
freedom and innovation through surveillance, territorial control, and
commodification, or through standardization and ontological constriction.
Many would argue that there is nothing new or revolutionary about Big
Data, science and the state have always aimed for accumulating as much data as
possible. What makes it possible to argue that big data is now revolutionising
knowledge production and surveillance is that the development of new modes of
data assemblage and analysis make it seem, not just plausible, but essential to
establish a regime of recording everything and hence to know everything. The
evanescent dream of knowing everything and everyone is reborn as a combination
of the panoptic archive and the ‘surveillance assemblage’[10]. Radically
powerful and insightful new ways of understanding the world are indeed being
opened up, but unsurprisingly the new world of Big Data is attended by
paradoxes, contradictions, exclusions, restrictions, discriminations, and
occlusions.[11]
[1] Davenport, TH. (2013), Preparing for Analytics
3.0, Retrieved Feb 28, 2013, from http://blogs.wsj.com/cio/2013/02/20/preparing-for-analytics-3-0/.
[2] Hey, T, S Tansley, et al., Eds) (2009), The
Fourth Paradigm: Data-intensive Scientific Discovery. Redmond, Microsoft
Research.
[3] Mayer-Schonberger, V and K Cukier (2013) Big
Data: A Revolution That Will Transform How We Live, Work and Think, Boston,
Houghton Miflin.
[4] Steiner, C (2012) Automate This: How Algorithms
Came to Rule The World, New York, Portfolio/Penguin.
[5] Personal Data: The Emergence of a New Asset
Class:
http://www3.weforum.org/docs/WEF_ITTC_PersonalDataNewAsset_Report_2011.pdf
[6] Berry, D (2011) The Philosophy of Software:
Code and Mediation in the Digital Age, New York, Palgrave MacMillan, p2,
citing Heidegger 1993 Question concerning technology, 32
[7] Rich, B (1995) Mortgaging the Earth: The
World Bank, Environmental Impoverishment, and the Crisis of Development,
Boston, Beacon Press, 238.
[8] Graham, SDN (2005) Software-sorted Geographies,
Progress in Human Geography 29: 562-80; Kitchen, R and M Dodge
(2011) Code/space: Software and Everyday Life, Cambridge, MIT Press.
[9] Andrejevic, M (2007) iSpy: Surveillance and
Power in the Interactive Era, University of Kansas Press. Andrejevic, M
(2007) Surveillance in the Digital Enclosure, The Communication Review, 10:
295-317. Schiller, D (2007) How To Think About Information, Urbana,
University of Illinois.
[10] Haggerty, K and R Ericson (2000) The
Surveillant Assemblage, British Journal of Sociology, 51(4):
605-22.
[11] Foucault, M (1986) Of Other Spaces,
Diacritics, 16(Spring): 22-27; Bowker, G (2013) The Theory/Data
Thing, International Journal of Comunication, 7: 1-20.