The End(s) of e-ResearchRalph Schroeder, Professor, MSc Programme DirectorEric T. Meyer, Research Fellow, DPhil Programme ...
   research using   digital tools and data   for the distributed and collaborative   production of knowledge
   e-Research is not a separate entity; it    consists merely of computational    support for other disciplines, and thes...
Source: Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge. Jour...
 We are all becoming e-Researchers;  successful e-Research will become so  mundane and expected that it will  disappear f...
   Grid computing (the original incarnation    of e-Science) was displaced by web    services, then by the cloud; the clo...
Research computingSupercomputing         The Grid                    Web 2.0                              Clouds          ...
Research computingSupercomputing            The Grid                       Web 2.0                                 Clouds ...
Number of academic articles including mentions of computational approaches to research in their title,abstract, or keyword...
Cloud computing: 3k-4k per monthNumber of news articles including mentions of big data. Source: Lexis/Nexis queries by the...
   Hacking: styles of science (after Crombie)     1. taxonomic     2. statistical     3. modelling     4. observation and...
   Sciences: algorithms across the styles (modelling,    statistics,…), data deluge,...   Social Sciences: statistics, i...
Particle Physics and EGEE: The world’s largest e-Science collaborationSource: CERN, CERN-EX-0712023, http://cdsweb.cern.ch...
Social Sciences: Growing influence of new tools andapproaches              VOSON (NodeXL version)Ackland, R. (2010), "WWW ...
Social Sciences: Search engine behaviour     Waller’s analysis of Australian Google Users     Key findings:            - M...
Humanities: Large-scale text analysis Michel et al. ‘culturomic’ analysis of 5 Million Digitized Google Books and Perc ana...
Fig. 1 Culturomic analyses study millions of books at once.           J. Michel al. Quantitative Analysis of Culture Using...
Evolution of popularity of the top 100 n-grams over the past five centuries.                             Perc M. (2012) Jo...
Digital transformations of research    Computational    Manipulability + Research Technologies  (Mathematization)         ...
See http://www.oii.ox.ac.uk/research/projects/?id=98
Oxford Internet Institute          Ralph Schroeder                             Eric T. Meyer     ralph.schroeder@oii.ox.ac...
The End(s) of e-Research
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The End(s) of e-Research

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Presentation at the 2012 Association of Internet Researchers annual meeting, Salford, UK.

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The End(s) of e-Research

  1. 1. The End(s) of e-ResearchRalph Schroeder, Professor, MSc Programme DirectorEric T. Meyer, Research Fellow, DPhil Programme DirectorOctober 25, 2012 @etmeyer
  2. 2.  research using digital tools and data for the distributed and collaborative production of knowledge
  3. 3.  e-Research is not a separate entity; it consists merely of computational support for other disciplines, and these are where the real research is taking place.
  4. 4. Source: Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge. Journal of Informetrics3(3):246-260
  5. 5.  We are all becoming e-Researchers; successful e-Research will become so mundane and expected that it will disappear from daily notice, like other infrastructures.
  6. 6.  Grid computing (the original incarnation of e-Science) was displaced by web services, then by the cloud; the cloud is now giving way to ‘big data’, which will no doubt be replaced by something else.
  7. 7. Research computingSupercomputing The Grid Web 2.0 Clouds Big Data
  8. 8. Research computingSupercomputing The Grid Web 2.0 Clouds Big Data
  9. 9. Number of academic articles including mentions of computational approaches to research in their title,abstract, or keywords. Source: Scopus queries by the authors. * 2012 only includes data through September.
  10. 10. Cloud computing: 3k-4k per monthNumber of news articles including mentions of big data. Source: Lexis/Nexis queries by the authors.
  11. 11.  Hacking: styles of science (after Crombie) 1. taxonomic 2. statistical 3. modelling 4. observation and measurement 5. historico-genetic development 6. mathematical postulation +7. laboratory (+8. algorithmic?)Styles of science, but also mathematization and other forms ofsymbolic manipulation via cataloguing, image analysis, etc.
  12. 12.  Sciences: algorithms across the styles (modelling, statistics,…), data deluge,... Social Sciences: statistics, image analysis, mapping,… Humanities: patterns in words, numbers, images, sounds,… (ie. Google Books) Arts: audience engagement, new forms of performance, …
  13. 13. Particle Physics and EGEE: The world’s largest e-Science collaborationSource: CERN, CERN-EX-0712023, http://cdsweb.cern.ch/record/1203203
  14. 14. Social Sciences: Growing influence of new tools andapproaches VOSON (NodeXL version)Ackland, R. (2010), "WWW Hyperlink Networks," Chapter 12 in D. Hansen, B. Shneiderman and M. Smith (eds),Analyzing Social Media Networks with NodeXL: Insights from a connected world. Morgan-Kaufmann.
  15. 15. Social Sciences: Search engine behaviour Waller’s analysis of Australian Google Users Key findings: - Mainly leisure - < 2% contemporary issues - No perceptible ‘class’ differences Novel advance: - Unprecedented insight into what people search for Challenge: - Replicability - Securing access to commercial dataV. Waller, “Not Just Information: Who Searches for What on the Search Engine Google?”,Journal of the American Society for Information Science and Technology, 62(4): 761-75, 2011.
  16. 16. Humanities: Large-scale text analysis Michel et al. ‘culturomic’ analysis of 5 Million Digitized Google Books and Perc analysis of the same data Key findings: - Patterns of key terms - Industrialization tied to shift from abstract to concrete words Novel advance: - Replicability, extension to other areas, systematic analysis of cultural materials Challenge: - Data quality
  17. 17. Fig. 1 Culturomic analyses study millions of books at once. J. Michel al. Quantitative Analysis of Culture Using Millions of Digitized Books. Science: Vol. 331 no. 6014 pp. 176-182. 2010.Published by AAAS
  18. 18. Evolution of popularity of the top 100 n-grams over the past five centuries. Perc M. (2012) Journal of the Royal Society Interface doi:10.1098/rsif.2012.0491 See: http://goo.gl/2URVT©2012 by The Royal Society Slide from John Lavagnino, King’s College London
  19. 19. Digital transformations of research Computational Manipulability + Research Technologies (Mathematization) Transformations of Research Front (For different fields) Socio-Technical Organization (Computerization movements)
  20. 20. See http://www.oii.ox.ac.uk/research/projects/?id=98
  21. 21. Oxford Internet Institute Ralph Schroeder Eric T. Meyer ralph.schroeder@oii.ox.ac.uk eric.meyer@oii.ox.ac.ukhttp://www.oii.ox.ac.uk/people/?id=26 http://www.oii.ox.ac.uk/people/?id=120 @etmeyer With support from:

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