Slides to my talk at the KMi Podium on July 24, 2012. The video can be found here: http://stadium.open.ac.uk/stadia/preview.php?s=29&whichevent=2011&option=both&record=0

1. www.know-center.at
KMi Podium – July 24, 2012
A tour through four topics related to
The Web in Science and
Research
Peter Kraker
gefördert durch das Kompetenzzentrenprogramm

2. Collaborators
Nicholas Balacheff Barbara Kump
Günter Beham Derick Leony
Erik Duval Stefanie Lindstaedt
Ronald Fellmann Sandra Murg
Angela Fessl Gonzalo Parra
Denis Gillet David Pocivalnik
Nina Grabowski Wolfgang Reinhardt
Michael Granitzer Peter Scott
Eelco Herder Thomas Ullmann
Patrick Höfler Bram Vandeputte
Kris Jack Claudia Wagner
Fleur Jeanquartier Fridolin Wild
Christian Körner Jerome Zeiliger 2

3. Scientific Activity on the Web
Online literature search
Collaborative writing and
reference management
Dissemination via preprints
and open archives
Knowledge transfer
in social networks
3
Crowdsourcing approaches

4. Research 2.0
Research E-Science
Science online
Context …
Studying the
use of the web
in the scientific
process
Web Science
The interdisciplinary science
of the web
Social Privacy
Networks
Online
Learning
4

5. Overview
Practices
The Web
in
Analysis Science Tools
and
Research
Infra-
structure
5

6. The change in
Overview scientific practices
and the open
science movement
Practices
The Web
in
Analysis Science Tools
and
Research
Infra-
structure
6

7. The STELLAR Network of Excellence
The STELLAR Network of Excellence in Technology
Enhanced Learning (http://stellarnet.eu)
Aim: unifying the diverse community of Technology
Enhanced Learning (TEL)
Key activity: supporting researchers with web tools and
infrastructure
7

8. Study on Practices
Two exploratory focus groups with researchers from
Technology Enhanced Learning
 14 participants from all major disciplines involved in TEL
 Qualitative analysis
Goals
 Determine the research process in TEL
 Collect web-based practices within the research process
8

9. Results
9
Kraker, P., & Lindstaedt, S. (2011). Research Practices on the Web in the Field of Technology
Enhanced Learning. Proceedings of the ACM WebSci’11. Koblenz, Germany.

10. Results
10

11. Results
Identified practices are mostly within the design and the
publication process
Existing practices on the web do not necessarily work in
research
Tools and technologies must be backed by existing
practice,
or solve an obvious shortcoming in the existing
practice
11

12. Problems in Technology Enhanced
Learning
Disjoint scientific communities (Gillet et al. 2009)
Low-cross citation rate, low cross-authorship rate (Kirby
et al. 2005, Maurer and Khan 2010)
Multi-disciplinarity instead of inter-disciplinarity
Can an Open Science help?
12

13. Open Science
“Open Science means opening up the research
process by making all of its outcomes, and the
way in which these outcomes were achieved, publicly
available on the World Wide Web”
Open Data Open Source
Open
Science
Open
Open Access
Methodology
Kraker, P., Leony, D., Reinhardt, W., & Beham, G. (2011). The Case for an Open Science in 13
Technology Enhanced Learning. International Journal of Technology Enhanced Learning, 6(3),
643-654.

14. Potential Benefits of an Open Science
Connect research communities – exchange and
discussion
Enables reproducibility of research – increase validity,
efficiency and comparability
Benefits stakeholders – results are earlier available,
fosters open innovation
14

15. Overview
Practices
The Web
in
Analysis Science Tools
and
Research
The provision of
Infra- web tools for
structure opening up the
research process 15

16. Open Archive
E-print archive
Publication metadata
aggregation and dissemination
site
TEL Thesaurus and
TEL Dictionary
http://oa.stellarnet.eu
16

17. TEL Europe
Social network
 Profiles
 Groups
 Blogs
Podcasts
Project results
Personalisable dashboard
http://teleurope.eu
17

18. Widgets on TEL Europe
Stream: Mobile Learning (#mlearning)
18

19. Overview
Practices
The Web
in
Analysis Science Tools
and
Research
The development of Infra-
an online structure
19
infrastructure to
connect the tools

20. Publication Feed System
Publication metadata has to be entered in different
locations all the time
 Institutional repository
 Project reporting
 Social reference management system
Goals
 Entering the details only once
 Web standards compliant
 Can be used with existing infrastructure
20

21. Publication Feed System
Kraker, P., Fessl, A., Hoefler, P., & Lindstaedt, S. (2010). Feeding TEL: Building an Ecosystem 21
Around BuRST to Convey Publication Metadata. Proceedings of the 2nd International
Workshop on Research 2.0.

22. Overview
The analysis of
data generated Practices
by researchers
on the web
The Web
in
Analysis Science Tools
and
Research
Infra-
structure
22

23. Analysis of Science
Information overload is NOT a contemporary
problem in science
Science has been growing exponentially for
the last 400 years (Price 1961)
 Number of papers (Larsen/von Ins 2010)
 Number of researchers (NSF 2010)
Problems
 Missing overview of research fields
 Missing awareness of current
developments
23
Price 1961
Extended by Leydesdorff (2008)

24. Awareness of Current Developments
Kraker, P., Wagner, C., Jeanquartier, F., & Lindstaedt, S. (2011). On the Way to a Science 24
Intelligence: Visualizing TEL Tweets for Trend Detection. Proceedings of the 6th European
Conference on Technology Enhanced Learning (pp. 220-232).

25. Tweet visualisations: Streamgraph
Hashtag: #www2012
25

26. Tweet visualisations: Weighted Graph
Hashtag:
#arv11
26

27. Missing overview
27

28. Missing overview
28

29. Visualisation example
29

30. The usual way of doing visualisations
Basis: Citations
 Co-citations as a measure of subject similarity (Small 1973)
Paper 2 Never cited together
Cited together 10 times
Paper 1
Paper 7
Cited together 2 times
Problem: Citations take very long to appear in meaningful
quantities (~3-5 years)
 Visualisations actually a look into the past!
30

31. A new approach
Visualisations based on the readership of publications
 Assumptions: Publications that are often read together,
are of a similar subject (Rowlands & Nicholas 2007, Bollen
& van de Sompel 2008)
Paper 2 Never read together
Read together 10 times
Paper 1
Paper 7
Read together 2 times
With collaborative reference management systems such
as Mendeley, we can measure readership
Readership statistics are much earlier available than
citations 31

32. Results
Kraker, P., Körner, C., Jack, K., & Granitzer, M. (2012). Harnessing User Library Statistics for 32
Research Evaluation and Knowledge Domain Visualization. Proceedings of the 21st International
Conference Companion on World Wide Web (pp. 1017-1024). Lyon: ACM.

33. The change in
Summary scientific practices
and the open
science movement
The analysis of
data generated Practices
by researchers
on the web
The Web
in
Analysis Science Tools
and
Research
The provision of
The development of Infra- web tools for
an online structure opening up the
infrastructure to research process 33
connect the tools

34. www.know-center.at
Thank you for your
attention!
http://twitter.com/PeterKraker
http://science20.wordpress.com
pkraker@know-center.at
gefördert durch das Kompetenzzentrenprogramm