Big Data, new epistemologies and paradigm shifts

Big Data and Society - Tập 1 Số 1 - 2014
Rob Kitchin1
1National Institute for Regional and Spatial Analysis, National University of Ireland, Maynooth, County Kildare, Ireland

Tóm tắt

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.

Từ khóa


Tài liệu tham khảo

Amin A, 2002, Cities: Reimagining the Urban

Anderson C (2008) The end of theory: The data deluge makes the scientific method obsolete. Wired, 23 June 2008. Available at: http://www.wired.com/science/discoveries/magazine/16-07/pb_theory (accessed 12 October 2012).

10.1140/epjst/e2012-01703-3

Berry D (2011) The computational turn: Thinking about the digital humanities. Culture Machine 12. Available at: http://www.culturemachine.net/index.php/cm/article/view/440/470 (accessed 3 December 2012).

10.1073/pnas.0610172104

Bollier D (2010) The Promise and Peril of Big Data. The Aspen Institute. Available at: http://www.aspeninstitute.org/sites/default/files/content/docs/pubs/The_Promise_and_Peril_of_Big_Data.pdf (accessed 1 October 2012).

10.1080/1369118X.2012.678878

Brooks D (2013) What data can’t do. New York Times, 18 February 2013. Available at: http://www.nytimes.com/2013/02/19/opinion/brooks-what-data-cant-do.html (accessed 18 February 2013).

Bryant R, Katz RH and Lazowska ED (2008) Big-data computing: Creating revolutionary breakthroughs in commerce, science and society. In: Computing Research Initiatives for the 21st Century, Computing Research Association, Ver. 8. Available at: http://www.cra.org/ccc/docs/init/Big_Data.pdf (accessed 12 October 2012).

Clark L (2013) No questions asked: Big data firm maps solutions without human input. Wired, 16 January 2013. Available at: http://www.wired.co.uk/news/archive/2013-01/16/ayasdi-big-data-launch (accessed 28 January 2013).

10.2307/25095630

Constine J (2012) How big is Facebook’s data? 2.5 billion pieces of content and 500+ terabytes ingested every day, 22 August 2012. Available at: http://techcrunch.com/2012/08/22/how-big-is-facebooks-data-2-5-billion-pieces-of-content-and-500-terabytes-ingested-every-day/ (accessed 28 January 2013).

Crampton J, Graham M, Poorthuis A, et al. (2012) Beyond the Geotag? Deconstructing ‘Big Data’ and Leveraging the Potential of the Geoweb. Available at: http://www.uky.edu/∼tmute2/geography_methods/readingPDFs/2012-Beyond-the-Geotag-2012.10.01.pdf (accessed 21 February 2013).

Crawford K (2013) The hidden biases of big data. Harvard Business Review Blog. 1 April. Available at: http://blogs.hbr.org/2013/04/the-hidden-biases-in-big-data/ (accessed 18 September 2013).

Cukier K (2010) Data, data everywhere. The Economist, 25 February (accessed 12 November 2012).

10.1632/ade.149.20

10.1068/d378t

Dyche J (2012) Big data ‘Eurekas!’ don't just happen. Harvard Business Review Blog. 20 November. Available at: http://blogs.hbr.org/cs/2012/11/eureka_doesnt_just_happen.html (accessed 23 November 2012).

10.1007/s13347-012-0093-4

10.1111/j.1467-8306.1981.tb01346.x

Han J, 2011, Data Mining: Concepts and Techniques, 3

Haraway D, 1991, Simians, Cyborgs and Women: The Reinvention of Nature

Harvey D, 1972, Social Justice and the City

10.1007/978-0-387-84858-7

Hey T, 2009, The Fourth Paradigm: Data-Intensive Scientific Discovery, xvii

Jenkins T (2013) Don’t count on big data for answers. The Scotsman, 12 February 2013. Available at: http://www.scotsman.com/the-scotsman/opinion/comment/tiffany-jenkins-don-t-count-on-big-data-for-answers-1-2785890 (accessed 11 March 2013).

10.1525/bio.2009.59.7.12

10.4135/9781446215432.n2

10.1177/2043820613513388

10.1007/s10708-013-9516-8

Kuhn T, 1962, The Structure of Scientific Revolutions

Laney D (2001) 3D data management: Controlling data volume, velocity and variety. Meta group. Available at: http://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf (accessed 16 January 2013).

10.1126/science.1167742

Lehning M, Dawes N, Bavay M. et al. (2009) Instrumenting the earth: Next-generation sensor networks and environmental science. In: Hey T, Tansley S and Tolle K (eds) The Fourth Paradigm: Data-Intensive Scientific Discovery. Redmond: Microsoft Research, pp. 45–51.

Lehrer J (2010) A physicist solves the city. New York Times, 17 December. Available at: http://www.nytimes.com/2010/12/19/magazine/19Urban_West-t.html (accessed 23 December 2013).

10.1016/j.shpsc.2011.10.001

Loukides M (2010) What is data science? O’Reilly Radar, 2 June 2010. Available at: http://radar.oreilly.com/2010/06/what-is-data-science.html (accessed 28 January 2013).

Manovich L (2011) Trending: The promises and the challenges of big social data. Available at: http://www.manovich.net/DOCS/Manovich_trending_paper.pdf (accessed 9 November 2012).

Marche S (2012) Literature is not data: Against digital humanities. Los Angeles Review of Books, 28 October 2012. Available at: http://lareviewofbooks.org/article.php?id=1040&fulltext=1 (accessed 4 April 2013).

Marz N, 2012, Big Data: Principles and Best Practices of Scalable Realtime Data Systems

Mayer-Schonberger V, 2013, Big Data: A Revolution that Will Change How We Live, Work and Think

10.1111/j.1467-9787.2009.00641.x

Moretti F, 2005, Graphs, Maps, Trees: Abstract Models for a Literary History

Open Data Center Alliance (2012) Big Data Consumer Guide. Open Data Center Alliance. Available at: http://www.opendatacenteralliance.org/docs/Big_Data_Consumer_Guide_Rev1.0.pdf (accessed 11 February 2013).

Pentland A (2012) Reinventing society in the wake of big data. Edge, 30 August 2012. Available at: http://www.edge.org/conversation/reinventing-society-in-the-wake-of-big-data (accessed 28 January 2013).

Porway J (2013) You can’t just hack your way to social change. Harvard Business Review Blog, 7 March 2013. Available at: http://blogs.hbr.org/cs/2013/03/you_cant_just_hack_your_way_to.html (accessed 9 March 2013).

Prensky M (2009) H. sapiens digital: From digital immigrants and digital natives to digital wisdom. Innovate 5(3). Available at: http://www.innovateonline.info/index.php?view=article&id=705 (accessed 12 October 2012).

Ramsay S, 2010, Reading Machines: Towards an Algorithmic Criticism

Ribes D, 2013, ‘Raw Data’ is an Oxymoron, 147, 10.7551/mitpress/9302.003.0010

Rogers S (2013) Twitter's languages of New York mapped. The Guardian, 21 February 2013. Available at: http://www.guardian.co.uk/news/datablog/interactive/2013/feb/21/twitter-languages-new-york-mapped (accessed 3 April 2013).

10.1191/030913297673302122

10.1177/2043820613514321

Schnapp J and Presner P (2009) Digital Humanities Manifesto 2.0. Available at: http://www.humanitiesblast.com/manifesto/Manifesto_V2.pdf (accessed 13 March 2013).

10.1007/978-3-031-01899-2

Siegel E, 2013, Predictive Analytics

Steadman I (2013) Big data and the death of the theorist. Wired, 25 January 2013. Available at: http://www.wired.co.uk/news/archive/2013-01/25/big-data-end-of-theory (accessed 30 January 2013).

10.1016/j.shpsc.2011.10.009

Strom D (2012) Big data makes things better. Slashdot, 3 August. Available at: http://slashdot.org/topic/bi/big-data-makes-things-better/ (accessed 24 October 2013).

10.1086/606126

Wyly E (in press) Automated (post)positivism. Urban Geography.

Zikopoulos PC, 2012, Understanding Big Data

Thông tin
Thông tin xuất bản

Big Data and Society

Tập 1 Số 1

Thông tin tác giả