Science 2.0
(A new modus operandi for science and research)
Its potential impact on excellence
Excellence in Research Estonian academy of Sciences, Council of Estonian Centres of excellence in research,
Estonian Research Council
22-23 October 2013.
Talinn
JC.Burgelman (DG R&I) (not speaking on behalf of the EC)
&
D. Osimo (Open Evidence)
We lack scientific evidence of what the future will be…..
Three stories
Galaxyzoo (citizen science)
Synaptic Leap (networked science)
Excel-gate (open data)
2
Key question:
• Are we at the beginning of a change in modus operandi of science
and research ("Perez change")?
• If so, it implies the need to rethink our institutional facts of scientific life:
- curricula development, ‘’high impact’’ measures, education,
- Scientific methods, approaches and publishing,
- …
• And thus….research and innovation strategies & policies
(Perez change: rewards and risks, new players emerge, old have to adapt/innovate or
risk losing relevance,..)
1. What is going on?
2. Impact on the science and research system?
3. Irreversible?
4. Policy implications?
1. What is going on?
Observable explosive growth of data, authors (data & intelligence
producers) and publication platforms Authorship: growing
10–fold each year
vs typical 10–fold
each hundred years
(Pellis & Bigelow
2009)
Data: “Every 2
Days We Create As
Much Information
As We Did Up To
2003” (Schmidt
2008)
Analysis
Publication
Review Conceptualisation
Data gathering
Open
access
Scientific
blogs Collaborative
bibliographies
Alternative
Reputation
systems
Citizens
science Open
code
Open
labbook
s /
wflows
Open
annotat
ion
Open
data
Pre-
Data-
intensive
6
Where does it come from?
Analysis
Publication
Review Conceptualisation
Data gathering
Open
access
Scientif
ic blogs
Collaborativ
e
bibliographi
es
Alternativ
e
Reputatio
n systems
Citizen
s
science Open
code
Open
labboo
ks /
wflows
Open
annotat
ion
Open
data
Pre-
Data-
intensive
7
Datadryad.org
Myexperiment.
org
Runmycode
.org
ArXiv
Sci-
starter.com
Openannotation.
org
Altmetric.com
Mendeley.com Researchgate.
com
Figshare.com
Roar.eprints.org
An emerging "ecosystem "of services
and standards
Its is real!
In one word: much more than Open Access!
Analysis
Publication
Review Conceptualisation
Data gathering
Open
access
8
2. Impact: More than a marginal change: the modus
operandi for R&S is changing
CKAN
Science blogs
25K on
Research
Blogging
platform
Mendeley
(2000K
users,2013)
Examples: Arxiv OpenAire Openannotation.org DataNet
Manual
Computational
Deductive
2nd paradigm: theoretical
(Newton)
3rd paradigm: computational
(Von Neumann)
Inductive
1st paradigm: empirical
(Bacon)
4th paradigm: data-
intensive (Venter, DNA sequencing)
A 4th paradigm of data-intensive science?
Data explosion only starting (internet of things!)
Greater role for inductive, not only hypothesis driven science: “Here’s
the evidence, now what is the hypothesis?”
Observable impact:
More productive science
•New type of scientific outputs
•Using the same data sets for multiple research
•Crowdsourcing
•Faster circulation of high-quality ideas
• “We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.” (Anderson 2007)
Better science
•Greater falsifiability: move towards reproducible science thanks to publishing data + code in addition to article
•Easier to follow the process, no need to wait for the product
•Rapidly uncover mistaken findings
•Greater availability of data collection and datasets increases the utility of inductive methods.
11
3. Irreversible? Science 2.0 is driven by:
- Explosion of knowledge and science
producing actors (globally)
- Demand for “faster” science
- Demand for catching up
- Demographics (“digital natives” go global)
- Cheap and easy to use ICT (low entry
barriers)
Irreversible trend
The old ideal of ‘’les encyclopedistes’’ is gone (but Wittgenstein would have it
easier to publish his thinking today and we have wikipedia…)
The "Scientific Powers That Be", disappear or adapt?
How important will Nature remain? (11% of world output in Open access journals)
New ways to determine reputation, CV’s? (DFG – only 5 publications to mention,
NSF asks PI to list research “products”)
New gatekeepers (intermediaries) will come.
More Creative Commons? Open access?
More citizen (as scientist) science?
Faster science (google scholar…), beta science a valid status?
Data-visualisation as a key language and statistics as a key science
Knowledge manager skills and services vital part of education?
Due to data abundance: more time to think the questions, but also “Learn to think”?
New curricula needed? With more attention to multi disciplinarity? And to product
development (+/- 10% of all scientific work goes to SW dev, Nature)
New metrics needed
4. Important (policy) implications?
Towards a green paper
DG RTD with DG Connect, the CSA and DG JRC
• Work on better mapping the business model and policy implications of
Science 2.0.
• European wide consultation to be launched focussing on which policy
actions for the European Commission to take….or not.
• Green paper by spring 2014
CONTRIBUTE!