The End(s) of e-Research
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The End(s) of e-Research



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

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



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The End(s) of e-Research The End(s) of e-Research Presentation Transcript

  • The End(s) of e-ResearchRalph Schroeder, Professor, MSc Programme DirectorEric T. Meyer, Research Fellow, DPhil Programme DirectorOctober 25, 2012 @etmeyer
  •  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 these are where the real research is taking place.
  • 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
  •  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.
  •  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.
  • Research computingSupercomputing The Grid Web 2.0 Clouds Big Data
  • Research computingSupercomputing The Grid Web 2.0 Clouds Big Data
  • 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.
  • Cloud computing: 3k-4k per monthNumber of news articles including mentions of big data. Source: Lexis/Nexis queries by the authors.
  •  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.
  •  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, …
  • Particle Physics and EGEE: The world’s largest e-Science collaborationSource: CERN, CERN-EX-0712023,
  • 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.
  • 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.
  • 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
  • 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
  • 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:©2012 by The Royal Society Slide from John Lavagnino, King’s College London
  • Digital transformations of research Computational Manipulability + Research Technologies (Mathematization) Transformations of Research Front (For different fields) Socio-Technical Organization (Computerization movements)
  • See
  • Oxford Internet Institute Ralph Schroeder Eric T. Meyer @etmeyer With support from: