the end(s) of e-research

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7/3/22 The End(s) of e-Research Ralph Schroeder, Professor, MSc Programme Director Eric T. Meyer, Research Fellow, DPhil Programme Director @etmeyer

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

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Page 1: The End(s) of e-Research

April 11, 2023

The End(s) of e-Research

Ralph Schroeder, Professor, MSc Programme DirectorEric T. Meyer, Research Fellow, DPhil Programme Director

@etmeyer

Page 2: The End(s) of e-Research

e-Research is defined as:

research using

digital tools and data

for the distributed and collaborative

production of knowledge

Page 3: The End(s) of e-Research

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.

Page 4: The End(s) of e-Research

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

Page 5: The End(s) of e-Research

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.

Page 6: The End(s) of e-Research

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.

Page 7: The End(s) of e-Research

Research computing

The Grid

Supercomputing

Clouds

Big Data

Web 2.0

Page 8: The End(s) of e-Research

Research computing

The Grid

Supercomputing

Clouds

Big Data

Web 2.0

Page 9: The End(s) of e-Research

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.

Page 10: The End(s) of e-Research

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

Page 11: The End(s) of e-Research

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.

Page 12: The End(s) of e-Research

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, …

Page 13: The End(s) of e-Research

Source: CERN, CERN-EX-0712023, http://cdsweb.cern.ch/record/1203203

Particle Physics and EGEE: The world’s largest e-Science collaboration

Page 14: The End(s) of e-Research
Page 15: The End(s) of e-Research

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)

Page 16: The End(s) of e-Research

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.

Page 17: The End(s) of e-Research

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

Page 18: The End(s) of e-Research

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.

Page 19: The End(s) of e-Research

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

Page 20: The End(s) of e-Research

Digital transformations of research

Computational Manipulability +

Research Technologies(Mathematization)

Socio-Technical Organization

(Computerization movements)

Transformations of Research Front

(For different fields)

Page 21: The End(s) of e-Research

Big DataAccessing and Using Big Data to Advance Social Science Knowledge

See http://www.oii.ox.ac.uk/research/projects/?id=98

Page 22: The End(s) of e-Research

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