Presentation at invited workshop "DIGITAL RESEARCH RESOURCES IN THE ARTS AND HUMANITIES - Achievements and Prospects for Future Collaboration" held at King’s College London, 25 July 2012
2. Research “on” the Web
• Web as an infrastructure for research
• Web as a source of data
• Web as a subject of research
• Web of scholarly discourse
3. ...the imminent flood of
scientific data expected
from the next generation of
experiments, simulations,
sensors and satellites
Tony Hey and Anne Trefethen
Source: CERN, CERN-EX-0712023, http://cdsweb.cern.ch/record/1203203
6. The Problem
INT. VERSE VERSE BRIDG VERSE BRIDG VERSE O .
E E UT
7. Structural Analysis of Large Amounts of Music Information
23,000 hours of Digital Music
recorded music
Collections Music Information
Retrieval Community
Student-sourced Community
ground truth Software
Supercomputer
Linked Data
Repositories
9. PolicyGrid
m Current Nodes
Rural communities
Demonstrators
DE Hubs DAMES d
& Sustainability
ds
Harnessing advances in digital
Social Inclusion
technology and practice to
achieve world-class social highwire NeISS
CQeSS Genesis
s e-Social Science
research with maximum impact m MoSeS
m
Obesity e-Lab ss
HUB
m DReSS Horizon
DE DTCs Creative Industries
Finance
mm
d MiMeG Healthcare Genesis Media
OeSS GeoVUE
mm eStat m d NCRM phase 3
Entertainment m
Web Science
ncrmLifeGuide NCRM phase 2
www.digitalsocialresearch.net
10. New York London Paris Moscow
The Tweet-o-Meter
http://www.casa.ucl.ac.uk/tom/
11. A A
B
B F
+ F
+ -
C
- E
C
E
D
D
Theories of Theories of Theories of
Self interest Exchange Balance
A
A
B F B F
C
+ C - + E
E
D
D
Novice
Expert
Theories of Theories of Theories of
Collective Action Homophily Cognition
12. Anatomy of an observatory
Install
Query Subscribe
analytic
Data flows
ongoing collection
16. The order of social machines
Real life is and must be full of all kinds of
social constraint – the very processes
from which society arises. Computers
can help if we use them to create
abstract social machines on the Web:
processes in which the people do the
creative work and the machine does the
administration… The stage is set for an
evolutionary growth of new social
engines. Berners-Lee, Weaving the Web, 1999
17. An Example Social Machine
• The Kenyan election on the
27th December 2007…
• wave of riots, killings and
turmoil…
• African blogger Erik Hersman
read a post by another blogger
Ory Okolloh…
• Resulted in Ushahidi…
• “Nobody Knows Everything,
but Everyone Knows
Something.”
• Local observers to submit
reports using the Web or SMS
messages from mobile phones
18.
19. The Zooniverse principles
1. Telling people about the Versus…
purpose of the research • The Deficit model – the
and about its context is a layperson is irrational,
good thing ignorant, and even
2. Treat participants as intellectually vacuous
collaborators not as • Human-based computation
subjects – a computer science
3. Do not waste people’s technique in which a
time computational process
4. All volunteers, and their performs its function by
contributions, are of equal outsourcing certain steps to
value to the project humans
25. The users of a website, the website, and
the interactions between them, together
form our fundamental notion of a “machine”
26. “Facebook for Scientists” A probe into researcher
...but different to Facebook! behaviour
A repository of research Open source (BSD) Ruby on
methods Rails app
A community social network of REST and SPARQL interfaces,
people and things supports Linked Data
A Social Virtual Research Influenced BioCatalogue,
Environment MethodBox and SysMO-SEEK
myExperiment currently has 307 groups, 2494 workflows, 643
files and 250 packs - see wiki.myexperiment.org
28. Research
repeat Record repeat
Machine paper Machine
REPRODUCE
paper
software software
Machine Machine
Software
REPRODUCE OR REPEAT?
paper
workflow workflow
wf software
software
Machine Software Machine
blogs.nature.com/eresearch/
31. Discussion
• The underlying themes in this talk have been:
– Web (co-constituted)
– people (expert to lay)
– computation (device to supercomputer)
– automation / assistance
– methods, reuse and value-add
• These reflect significant trends in our
“knowledge infrastructure”, and significant
opportunities for digital humanities
CERN teams up with Leaders in Information Technology to build giant Data GridData accumulation rate: 10 Petabytes per year (equivalent to about 20 million CD-ROMs).http://public.web.cern.ch/press/pressreleases/Releases2001/PR11.01ECERNopenlab.html