3. [ web 2.0 stats ]
1.5m users 140m users
39 638 public groups
Data on 85m research papers
150m members (as at 9.02.2012) >25m users
10m in Middle East and Africa reached 10m users in 16 days
Second-biggest search engine 205 444 eBooks, 1 828 622 textbooks,
after Google 55 374 authors, 101 subjects, millions of users
7. In the past 30 years,
the average distance between
collaborators has increased 5-fold
(from 334km in 1980
to 1500km in 2009)
(Waltman, Tijsen & Van Eck 2011)
8. Needs expressed by FoS
• Need for increased collaboration (and removal
of geographic barriers)
• Need for new publishing channels
9. Those who work in collaboration with different
institutions are significantly more likely to be
frequent or occasional users of web 2.0
services associated with producing, sharing or
commenting on scholarly content.
(RIN 2010)
Based on cohort of approx. 1000 UK researchers
10. Effective technology transfer
• UoM has a key role to play as a flagship university
in knowledge creation and innovation
(i.e. knowledge application)
• Effective technology transfer relies not only on
faculty-generated research (and the
organisational/national/regional systems that
support their work), but on relationships with
the private sector and government.
(John Douglass, Center for Studies in Higher Education - UC Berkeley)
11. SCAP assumptions
1. Increasing the visibility of academics, their
expertise and their knowledge outputs increases
their chances of gaining access to networks
2. There are 3 key networks that academics can
access by increasing their online visibility:
1. Academic, discipline-specific networks
2. Academic—industry networks
3. Research funding networks
3. Web 2.0 technologies provide tools that can
increase the online visibility of academics on a
global scale
12. What is PAO?
The use of online/web 2.0 technologies
1. To increase the visibility of academics
2. To make knowledge objects
available, accessible and visible
(Knowledge objects: ‘traditional’ publications
such as journal articles as well as
unpublished or preprint papers,
presentations, teaching resources, lab notes,
data sets, etc.)
13. Examples
PULL (passive) PUSH (active) MEASURE/TRACK
Mendeley Blog Goo.gl
LinkedIn Twitter Google Scholar
ResearchGate Comment ISI
Academia.edu Review Publish or Perish
About.me
UoM page
14. The PAO Process
• Selection of up to 10 participants from FoS for
pilot project
• Meet and brief participants (Wednesday)
• Baseline presence
• Create online profiles and create content
• Maintain and up-date profiles, and online
communication
• Duration: 5 months (May to September 2012)
• Measure presence / assess impact
• Present findings (November 2012)
16. What will participants have to do?
• Follow the steps in the Toolkit provided
• Complete Step 1: Updating CVs by end-May
• Complete Steps 2 to 10 over 4-month period
(June to September 2012)
• Only 4 out of 10 steps compulsory
• Maintain and up-date profiles, and online
communication
• Make CVs and Google Scholar data available
to RA/SCAP team
17. What will SCAP do?
• Provide Toolkits
• Provide participants with 3G cards for the
duration of the project
• Make a research assistant available to provide
support in creating and maintaining profiles
• Provide remote support
18. General comments
• Mindful of varying levels of skills and
expertise. No minimum requirement for
participation.
• Tools suggested in the toolkit are not meant to
be exhaustive or prescriptive. SCAP
encourages exploration of new and alternative
technologies.
Web 2.0 is a loosely defined intersection of web application features that facilitate participatory information sharing, interoperability, user-centered design, and collaboration on the World Wide Web. A Web 2.0 site allows users to interact and collaborate with each other in a social media dialogue as creators of user-generated content in a virtual community, in contrast to websites where usersare limited to the passive viewing of content that was created for them.
From this data, Olivier Beauchesneextracted and aggregated scientific collaboration between cities all over the world from 2005 to 2009. For example, if a UCLA researcher published a paper with a colleague at the University of Tokyo, this would create an instance of collaboration between Los Angeles and Tokyo. The result of this process is a very long list of city pairs, like Los Angeles-Tokyo, and the number of instances of scientific collaboration between them. Following that, I used the geoname.org database to convert the cities’ names to geographical coordinates.The next steps were then similar to those of the Facebook friendship map. I used a Mercator projection to project the geographical coordinates onto the map and used the Great Circle algorithm to trace the lines of collaboration between cities. The brightness of the lines is a function of the logarithm of the number of collaborations between a pair of cities and the logarithm of the distance between those same two cities.
