So why are there three
lack of uptake?
...and a theme in the
Adoption of e-Research Technologies
How did we get here?!
Early adopter success
Then rollout of infrastructure services
And then wondering where the users are
Heard at another repositories event...
“How do we persuade
researchers to populate
e-Science is about global collaboration
in key areas of science, and the next
generation of infrastructure that will
Due to the complexity of the software
and the backend infrastructural
requirements, e-Science projects usually
involve large teams managed and
developed by research laboratories,
large universities or governments.
What are we really trying to
A. Everyone using the
B. Research advances on
an everyday basis that
would not have
Not just accelerated but new
How do we move from heroic scientists doing
heroic science with heroic infrastructure to
everyday scientists doing science they couldn’t
do before? humanists
on of e-
Jim Downing came up with the idea of “Long Tail
Science”... So we are exploring how big science and
long-tail science work together to communicate
their knowledge. Long-tail science needs its domain
repositories - I am not sanguine that IRs can provide
the metalayers (search, metadata, domain-specific
knowledge, domain data) that are needed for
effective discovery and re-use.
The social process Environment
of science 2.0
Results & Analyses
1 Everyday researchers doing
• Not just a specialist few doing
heroic science with heroic
• Chemists are blogging the lab
• Everyone is mashing up
• Everday hardware – multicore
machines and mobile devices
2 A data-centric perspective, like
• Data is large, rich, complex and
• There is new value in
data, through new digital
artefacts and through metadata
context, provenance, workflows
• This isn’t “anti-computation” –
design interaction around data
3 Collaborative and participatory
• The social process of science
revisited in the digital age
• Collaborative tools – blogs
• e-Science now focuses
on publishing as well as
• Scholarly lifecycle perspective
4 Benefitting from the scale of digital
science activity to support science
• This is new and powerful!
• Community intelligence
• Usage informing
• e.g. OpenWetWare
• e.g. myExperiment
5 Increasingly open
• Preprints servers and
• Open journals
• Open access to data
• Science Commons
• Object Reuse & Exchange
6 Better not Perfect
• The technologies people
are using are not perfect
• They are better
• They are easy to use
• They are chosen by
7 Empowering researchers
• The success stories come
from the researchers who
have learned to use ICT
• Domain ICT experts are
delivering the solutions
• Anything that takes away
autonomy will be resisted
8 About pervasive computing
• e-Science is about
the intersection of
the digital and
• Sensor networks
• Mobile handheld
Onward and Upward
• e-Research is now
researchers to do
• As the individual
pieces become easy
to use, researchers
can bring them
together in new
“Standing on the
ways and ask new
shoulders of giants”
• “The next level”
(Everyday researchers are giants
• Absolutely key role in future research. So
think of a better word!
• Think of a park / reserve / gardens / zoo
– Visitors, rangers, wardens, gardeners, experts,
security, volunteers, ...
– Curation by providers,
experts and consumers
Those 8 Repository points
1. Not just a specialist few doing heroic science with heroic
infrastructure – repositories for all!
2. There is new value in data, through new digital artefacts and
through metadata e.g. context, provenance, workflows
3. e-Science now focuses on publishing as well as consuming
4. Usage informing recommendation
5. Researchers work with collections - Object Reuse &
6. They are easy to use
7. Anything that takes away autonomy will be resisted
8. e-Science is about the intersection of the digital and physical
worlds (not 1970s library catalogue interfaces)
And we needprocess processes too!
Curation of to curate
Goble & De Roure Educause Review Sep/Oct 2008
• Find a process based on what it and find copies or
similar services usable as alternates.
• Understand how and when it works, how to
operate it correctly and predict its performance.
• Know the conditions for use: permissions, licenses,
platforms, and costs.
• Judge the benefits of adoption based on its
reputation, provenance and validation by peers.
• Estimate the risk of adoption based on its
reliability and stability.
• Get assistance for its incorporation into
applications and workflows.
Transformation is already underway
• To understand where we’re going, look at
communities which have been early to embrace
• e-Science is one. What can we learn?
• Incidentally, so is music and broadcast!
– Vinyl was like books
– Now the process is digital from the studio through to
playback on an iPod
– People create content
– People publish content
– Has the business adapted?
Note to Reader. The next slides are not intended to be
anti-grid. Everyone working on Grid is doing great work.
Don’t think rollout of technologies...
Think roll-in of researchers...
Knowledge co-production vs Service Delivery!
Without middleware we need lots of bits of software to join things together
With middleware there are fewer arrows!
N2 and M
But this is what happened. Now the picture with lots of thin arrows isn’t quite so scary!
use Web 2.0 here
Web is being embraced for usability and programmability e.g. mashups
And Grid is trying to come to terms with multicore and clouds!
A Thought Experiment
Imagine Eprints/Dspace/Fedora isn’t
something you download and run on a local
Imagine instead that you just go to the cloud
and make one*
How would this repository ecosystem
self-organise to support Research 2.0?
Would there be institutional repositories?
* (Actually you can!)
Is it a wave or is it a particle?
Tension between data being “out on the
Web” (user view) or in an institutional
machine room (provider view)
What is the curator view?
Issues perceived differently for metadata
servers and data servers
How Repositories can avoid Failing like the Grid
1. Understand what the users will need by
going on the journey together
2. Be open-minded: are we solving the right
problem? (Don’t forget curation of process!)
3. Don’t create artificial distinctions from Web
4. Beware standards as a barrier to adoption
5. Think cloud, outside the institutional box:
imagine the repository factory
6. Think of a new name for repositories!
David De Roure
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