3.5.12, Keynote I, Main Hall, Chair: The Internet, Science, and Transformations of Knowledge (Ralph Schroeder) #CeDEM12

1. The Internet, Science, and Transformations of
Knowledge
TITLE
Ralph Schroeder
Oxford Internet Institute, University of Oxford
May 3, 2012

2. Overview
• Definition of e-Research
• The sociology of advancing (online) knowledge
• Examples and Cases
• Implications

3. Research computing
Supercomputing
The Grid
Web 2.0
Clouds
Big Data

4. e-Research
Defined as distributed and collaborative
digital tools and data for knowledge
production
,

5. Digital transformations of research
Computational
Manipulability +
Research Technologies
(Mathematization)
Research Front
(For different fields)
Socio-Technical
Organization
(Computerization
movements)

6. A Model of Transformations
Computational manipulability
+ Research technologies
+ Socio-technical organization
= Transformations
 of research front

7. Computational Manipulability?
• ‘the distinctiveness of the network of mathematical
practitioners is that they focus their attention on the pure,
contentless form of human communicative operations: on
the gestures of marking items as equivalent and of ordering
them in series, and on the higher-order operations which
reflexively investigate the combinations of such operations’
• ‘mathematical rapid-discovery science…the lineage of
techniques for manipulating formal symbols representing
classes of communicative operations’

8. Research Technologies and Driving
Forces
• Off-the-shelf and special purpose, but ‘all-
purpose’ (passport-like) machines across contexts
• A hard core around which researchers can focus
attention on a common research front
• Movements (SIMs, Frickel and Gross) to
computerize (mathematize?) research (Kling)
• Core (research technologies) plus organization
and movements - driving science (and research)

9. The sociology of advancing (online)
knowledge production
• Research instruments plus mathematics ->
high-consensus rapid-discovery science
• Orientation to a community of researchers at the
research front
• Focus of attention limited by law of small
numbers (Collins)
• The extension of computation into research
• The limits of understanding and explaining
research-in-the-making…
…versus a movement that applies across research

10. Varieties of Research
• Humanities: patterns in words, numbers, images,
sounds…
• Social Sciences: statistics, image analysis, mapping…
• Sciences: Hacking’s ‘styles’
• Mathematization, now Cloudified
• All knowledge is digitally manipublable in e-
Research…
• …but relation of the object to the (physical) world or
to the research front varies

11. Examples and Cases
– GAIN = statistical data pooling
– Galaxyzoo = taxonomic crowdsourcing
– Integrative Biology = modelling
– EGEE/LHC = observation and measurement
– SPLASH = taxonomic
– Swedish National Data Service = statistical, combined data
– SwissBioGrid = statistical/modelling
– VOSON = statistical, network analysis
– PynchonWiki = interpretive crowdsourcing
– Cultural genomics with Google Books = statistical/interpretive
– Moretti = distance reading via network analysis
...what type of transformation?

12. GAIN:
Genetic Association
Information Network

14. IB:
Integrative Biology

15. Particle Physics and EGEE: The world’s largest e-Science collaboration
Source: CERN, CERN-EX-0712023, http://cdsweb.cern.ch/record/1203203

16. SPLASH: Structure of
Populations, Levels of
Abundance, and Status of
Humpbacks
Meyer, E.T. (2009). Moving from small science to big science: Social and organizational impediments to large
scale data sharing. In Jankowski, N. (Ed.), E-Research: Transformation in Scholarly Practice (Routledge
Advances in Research Methods series). New York: Routledge.

17. e-Research in Sweden
• Sweden has a major e-Research initiative
• ’Universal’ personal identification
• Uniquely powerful datasets (e.g. twin registry)
• Significance: If Swedes can’t do it, no one can?
• Use of population data in a ’transparent’ society with high trust between
people, authorities and researchers…
• …but, implementation of secure distributed access and ’incidents’ creating
public concerns
• Swedish National Data Service

18. Swiss BioGrid
Novartis

19. 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.

21. Fig. 1 Culturomic analyses study millions of books at once.
J Michel et al. Science 2011;331:176-182
Published by AAAS

22. Source: Moretti, F. (2011). Network Theory, Plot Analysis. New Left Review 68, p. 81

23. 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

24. iTunes U
Google Citations
Microsoft Academic Search
Twitter
YouTube
…
Source: Meyer & Schroeder (2009). The World Wide Web of Research and Access to Knowledge. Journal of Knowledge Management Research
and Practice 7 (3):218-233.

25. What difference does it make?
– A physical core network of digital tools and data
(computational manipulability)
– A research community focuses its efforts
– The expandable (‘clouds’) capacity of research
instruments + new organizational modes
= ongoing diffusion of e-Research across domains
– Limits of this spread = limits of attention on new
fronts towards which there are orientations:
‘advances’ versus existing directions

26. Changing Research Practices
• Communication: searchability/findability, and
(pressure for) increased reflexivity
• Role of Knowledge in society: boundaries vis-a-vis
public and between research communities becomes
more porous
• Knowledge: driven towards computational
manipulability and aggregatability
• The confluence of these three:
 Research becomes an increasingly autonomized
apparatus in society and a complexified socio-
technical one

27. Implications
• Implications for Science Communication:
– Reflexivity changes practices, and the role of knowledge
vis-à-vis public
• Implications for STS, information science and other fields:
– synthesis beyond existing (sub) disciplinary boundaries is
needed
• Implications for policy and practice:
– awareness of positive and negative aspects of
autonomization (or intermediation and disintermediation
of knowledge)
– changing boundaries within knowledge, and between
knowledge and society

28. Oxford e-Social Science
Project
Oxford Oxford Institute for
Internet e-Research Science, Innovation
Institute Centre and Society
at
Saïd Business School
http://www.oii.ox.ac.uk/microsites/oess/