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Big Data: Some Initial Reflectons

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Slides from presentation to AHRC internal staff seminar, April 2014
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Professor Andrew Prescott, Theme Leader Fellow AHRC Digital Transformations Strategic Theme Big Data: Some Initial Reflections
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Page 1: Big Data: Some Initial Reflectons

Professor Andrew Prescott, Theme Leader Fellow

AHRC Digital Transformations Strategic Theme

Big Data: Some Initial Reflections

Page 2: Big Data: Some Initial Reflectons

• The Met Office currently generates about 20TB of data each day

• ‘The problems which confront the meteorologist today will be faced by the humanities scholar within ten years’

Page 3: Big Data: Some Initial Reflectons

• Large Hadron Collider: 600 million ‘collision events’ per second

• One million jobs run by servers each day, with over 10 GB of data per second transferred at peak times

• Approx. 20 petabytes of data produced annually• Over 70 universities involved in processing the data

Page 6: Big Data: Some Initial Reflectons

• Some working definitions of big data• Big data exceeds the capacity of existing

desktop machines and networks: you need help to deal with it

• Data that is so large that existing methods of analysis simply don’t work: you have to change your methodology (probably to something quantitative)

• Gartner definition: “Big data” is high-volume, -velocity and –variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.

Page 7: Big Data: Some Initial Reflectons

Examples of everyday big data of research value

• Retail data generated by supermarkets• Online retail data: Amazon• Transport information: Oyster card• Hospital data• Data from utility companies• Social media

Page 8: Big Data: Some Initial Reflectons

Visualisation of languages used in tweets in London in Summer 2012: Centre for Advanced Spatial Analysis, UCL:

http://mappinglondon.co.uk/2012/londons-twitter-tongues/

Page 9: Big Data: Some Initial Reflectons

Wolphram Alpha analytics of my Facebook friends

Page 10: Big Data: Some Initial Reflectons

Analytic of my friend network

Page 11: Big Data: Some Initial Reflectons

Does Big Data Yet Exist for the Humanities?

Page 12: Big Data: Some Initial Reflectons

Letter of Gladstone to Disraeli, 1878: British Library, Add. MS. 44457, f. 166

The political and literary papers of Gladstone preserved in the British Library comprise 762 volumes containing approx. 160,000 documents.

Page 13: Big Data: Some Initial Reflectons

George W. Bush Presidential Library:200 million e-mails

4 million photographs

Page 15: Big Data: Some Initial Reflectons

‘Big data’ has already been an issue for linguists for many years

Page 16: Big Data: Some Initial Reflectons

Another familiar example of big data in the humanities: censuses

Page 17: Big Data: Some Initial Reflectons

Moving images and sound present some of the most challenging big data issue for arts and humanities

Page 18: Big Data: Some Initial Reflectons

Archives and library catalogues as big data: Visible Archive browser: visiblearchive.blogspot.com

Page 19: Big Data: Some Initial Reflectons

Visualisation by Jon Orwant of Google of Library of Congress subject categorisations of books published

between 1600 and 2010: winedarksea.org

Page 20: Big Data: Some Initial Reflectons

Commons Explorer: experimental interface to allow exploration of large quantities of images in Flickr

Commons: http://mtchl.net/cex/

Page 21: Big Data: Some Initial Reflectons

The Anglo-American Legal Tradition: web site holding seven million images of medieval

legal records in the National Archives: www.aalt.law.uh.edu

Page 22: Big Data: Some Initial Reflectons

Fabio Lattanzi Antinori,The Obelisk (2012): Open Data Institute: http://www.theodi.org/culture/obelisk-2012

Page 23: Big Data: Some Initial Reflectons
Page 24: Big Data: Some Initial Reflectons

Asia Trend Map: predicting popularity of games, manga and anime: www.asiatrendmap.jp

Page 25: Big Data: Some Initial Reflectons

Some Big Data Issues

• Research has historically been hypothesis-driven; is a more data-driven research required?

• How valid are predictive and probabilistic techniques in arts and humanities research?

• Data quality issues: do we lose a sense of the context and stratigraphy of the data?

• Danger of thinking that data=truth

Page 26: Big Data: Some Initial Reflectons

Digital Transformation theme and Big Data

• Theme seeks to promote new research methods: using digital tools and materials to develop completely new type of scholarship

• Additional funding of £4m has been allocated to work on big data

• Following this workshop, call for big data projects will be issued

• Smaller projects (up to £100k)• Larger projects (up to £600k)


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