the end(s) of e-research
DESCRIPTION
Presentation at the 2012 Association of Internet Researchers annual meeting, Salford, UK.TRANSCRIPT
April 11, 2023
The End(s) of e-Research
Ralph Schroeder, Professor, MSc Programme DirectorEric T. Meyer, Research Fellow, DPhil Programme Director
@etmeyer
e-Research is defined as:
research using
digital tools and data
for the distributed and collaborative
production of knowledge
End 1: The e-Science Programme
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 Informetrics 3(3):246-260
End 2: Accidental e-Researchers
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.
End 3: The March of Progress
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 computing
The Grid
Supercomputing
Clouds
Big Data
Web 2.0
Research computing
The Grid
Supercomputing
Clouds
Big Data
Web 2.0
Emergent Foci
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.
Emergent Foci: Media Framing
Number of news articles including mentions of big data. Source: Lexis/Nexis queries by the authors.
Cloud computing: 3k-4k per month
Styles of Science
Hacking: styles of science (after Crombie)1. taxonomic
2. statistical3. modelling4. observation and measurement5. historico-genetic development 6. mathematical postulation+7. laboratory(+8. algorithmic?)
Styles of science, but also mathematization and other forms of symbolic manipulation via cataloguing, image analysis, etc.
Disciplinarityand the Uneven Distribution of Computation and Scientization
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, …
Source: CERN, CERN-EX-0712023, http://cdsweb.cern.ch/record/1203203
Particle Physics and EGEE: The world’s largest e-Science collaboration
Social Sciences: Growing influence of new tools and approaches
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.
VOSON (NodeXL version)
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 data
V. 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.
Published by AAAS
J. Michel al. Quantitative Analysis of Culture Using Millions of Digitized Books. Science: Vol. 331 no. 6014 pp. 176-182. 2010.
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
Digital transformations of research
Computational Manipulability +
Research Technologies(Mathematization)
Socio-Technical Organization
(Computerization movements)
Transformations of Research Front
(For different fields)
Big DataAccessing and Using Big Data to Advance Social Science Knowledge
See http://www.oii.ox.ac.uk/research/projects/?id=98
Oxford Internet Institute
With support from:
Eric T. [email protected]
http://www.oii.ox.ac.uk/people/?id=120@etmeyer
Ralph [email protected]
http://www.oii.ox.ac.uk/people/?id=26