Now available via DCC website: http://www.dcc.ac.uk/events/research-data-management-forum-rdmf/rdmf10-research-data-management-arts-and-humanities

1. David De Roure
What’s so different about
Arts and Humanities data?

2. ChristineBorgman

3. What is e-­‐Research?
• Research in every domain is increasingly data-­‐ and
computa8onally-­‐intensive, carried out collabora8vely over
distributed infrastructures
• e-­‐Research is the con8nuous technological and
methodological innova8on in digital methods to achieve
new research outcomes – using new forms of data and
emerging infrastructural capabili8es
• The Oxford e-­‐Research Center is a digital methods
incubator hos8ng 40 postdoctoral researchers conduc8ng
early-­‐adopter digital research across all disciplines

4. More people
Moremachines
Big Data and
Computation
Conventional
Computation
Social
Machines
Social
Networking
Cyberinfrastructure
e-infrastructure
Science 2.0
Citizen Science
e-Research
David De Roure

6. Economic and Social Research Council
Shaping Society
• Digital Social Research Program
• Social Machines
• Web Observatories
• Responsible Innova8on
• Centre for Interna8onal Social
Media Analy8cs

7. F i r s t
BioEssays,,26(1):99–105,January2004
http://research.microsoft.com/en-us/collaboration/fourthparadigm/

8. INT. VERSE VERSE VERSE VERSEBRIDGEBRIDGE OUT.

The Problem
signal
understanding
Ich Fujinaga

9. Chris Lintott
Scientists
Talk
Forum
Image
Classification
data reduction
Citizen Scientists

10. The challenge is to foster the co-constituted socio-technical
system on the right i.e. a computationally-enabled sense-
making network of expertise, data, models and narratives.
Big data elephant versus sense-making network?
Iain Buchan

11. data
method

12. Web as lens
Web as artefact
The Observatory Quarter
http://www.w3.org/community/webobservatory/

13. The “Virtual”
Observatory
Technicalandbusiness
interface
Interop
http://www.w3.org/community/webobservatory

15. Digital Music
Collec8ons
Student-­‐sourced
ground truth
Community
SoOware
Linked Data
Repositories
Supercomputer
23,000 hours of
recorded music
Music Information
Retrieval Community
SALAMI

16. 1. From signal to understanding
2. Working with mul8ple sources
of incomplete and inconsistent
data, with new born-­‐digital data
3. Innova8on and sharing of new
digital methods
4. Challenges of resource
discovery and publica8on of
new digital artefacts
5. Importance of provenance
6. Challenges of cura8on
7. Increasing automa8on (and
risks therein)
Commonali8es Differences
1. Specific content types and
their rela8onship to
physical artefacts
2. Curated collec8ons, and an
“infinite archive” of
heterogeneous content,
richly interlinked
3. Specialist digital methods
4. Publica8ons are subjects
and records of research
5. Emphasis on mul8ple
interpreta8ons and cri8cal
thinking

18. Nigel Shadbolt et al

19. Some Social Machines

20. 1. Digital > Digi8sed
2. Machines are users too
3. Digital brings new decay but also opportunity for
automa8on… and community engagement
4. SoOware is part of the problem and part of the
solu8on
5. Disciplinary boundaries are a legacy and
transcended by today’s research ques8ons
6. Towards Social Machines for Digital Cura8on?
Messages

21. david.deroure@oerc.ox.ac.uk
www.oerc.ox.ac.uk/people/dder
www.scilogs.com/eresearch
@dder
Thanks to: Chris8ne Borgman, Ichiro Fujinaga, Stephen Downie, Chris Lintog,
Iain Buchan, Nigel Shadbolt