IGELU conference, Oxford, UK, 17 September 2014

1. The Social Machines of
Scholarly Collaboration
David De Roure

2. A revolutionary idea…
Open Science!
rstl.royalsocietypublishing.org

3. Overview
1. Shifts in scholarship
2. End of the article
3. Future of the article
4. Scholarly Social Machines

4. The Big Picture
More people
More machines
Big Data
Big Compute
Conventional
Computation
“Big Social”
Social Networks
e-infrastructure
Online R&D
(Science
2.0)
Social
Machines
@dder

5. Edwards, P. N., et al. (2013) Knowledge Infrastructures: Intellectual Frameworks and
Research Challenges. Ann Arbor: Deep Blue. http://hdl.handle.net/2027.42/97552

6. Christine Borgman

7. theODI.org

8. F i r s t

11. New Social Process
http://www.theguardian.com/uk/series/reading-the-riots

12. www.zooniverse.org

13. Talk
Forum
Scientists
Image
Classification
Citizen Scientists
data reduction

14. Digital Music
Collections
Student-sourced
ground truth
Community
Software
Supercomputer
Linked Data
Repositories
23,000 hours of
recorded music
Music Information
Retrieval Community
SALAMI

15. Pip Willcox
Annotated Books Online — http://www.annotatedbooksonline.com
Archive of Early Medieval English — http://aeme.emesoc.org
The Bodin Project — http://sites.tufts.edu/bodinproject
Crowdmap the Crusades — http://dhcrowdscribe.com/crowdmap-the-crusades
The Devonshire Manuscript: A Social Edition — http://en.wikibooks.org/wiki/The_Devonshire_Manuscript

16. Pip Willcox

17. Interdisciplinary and “in the wild”
In it not on it Pull not Push

18. Overview
1. Shifts in scholarship
2. End of the article
3. Future of the article
4. Scholarly Social Machines

19. http://www.scilogs.com/eresearch/pages-of-history/ David De Roure

20. http://www.scilogs.com/eresearch/pages-of-history/ David De Roure

21. 1. It was no longer possible to include the
evidence in the paper – container failure!
“A PDF exploded
today when a
scientist tried to
paste in the
twitter
firehose…”

22. 2. It was no longer possible to reconstruct a
scientific experiment based on a paper alone

23. 3. Writing for increasingly specialist audiences
restricted essential multidisciplinary re-use
Grand Challenge Areas:
• Energy
• Living with Environmental Change
• Global Uncertainties
• Lifelong Health and Wellbeing
• Digital Economy
• Nanoscience
• Food Security
• Connected Communities
• Resilient Economy

24. 4. Research records needed to be readable by
computer to support automation and curation
A computationally-enabled
sense-making network of
expertise, data, models and
narratives.

25. 5. Single authorship gave way to casts of
thousands

26. 6. Quality control models scaled poorly with
the increasing volume
Filter, Publish, Filter, Publish, …
Like big data, publishing has
increasing volume, variety and
velocity
But what about veracity?

27. 7. Alternative reporting necessary for
compliance with regulations
One piece of research
may have multiple
reports and multiple
narratives for multiple
readerships, in multiple
formats and languages
(Computer are readers
too!)

28. 8. Research funders frustrated by inefficiencies
in scholarly communication
An investment is only worthwhile if
• Outputs are discoverable
• Outputs are reusable
…and preferably outputs accrue value through use
Using an obsolete scholarly communication system
impedes innovation and hence return on investment
What are we doing about it?
Trying to fix it using an obsolete scholarly
communication system!

29. Overview
1. Shifts in scholarship
2. End of the article
3. Future of the article
4. Scholarly Social Machines

30. method
data
script
protocol
program
workflow
model
…

31. Neil Chue Hong
Open Source Software as a
model for Open
Scholarship?

32. The Journal of Open Research
Software (JORS) features peer
reviewed Software Metapapers
describing research software with high
reuse potential.
We are working with a number of
specialist and institutional repositories to
ensure that the associated software is
professionally archived, preserved, and is
openly available.
Equally importantly, the software and the
papers will be citable, and reuse will be
trhattcp:k//eodpe.nresearchsoftware.metajnl.com/

33. The Evolution of myExperiment
Research Objects
Workflows
Computational
Research Objects
Packs
OAI
ORE
W3C PROV
Social Objects

34. Notifications and automatic re-runs
Autonomic
Curation
Self-repair
New research?
Machines are users too

35. Executable
Documents
http://commons.wikimedia.org/wiki/File:Stacks_in_Michigan_State_University_library.JPG

36. • Will digital libraries provide the infrastructure to execute
documents, or will people deploy them on alternative
infrastructures? What are the implications for discovery, curation,
and its automation?
• Who gains credit and owns the intellectual property generated
when a document runs automatically? Who is liable for damage
that arises? What are the implications of unintended or accidental
assembly of research methods and outcomes?
• What are the implications of research that occurs at very high
speed, possibly speculatively, without human intervention? Where
is the (critical, creative, subversive) human in the loop? Are we
‘burning’ research methods into an automated research platform?
• How do executable documents sit in the social websites of
discovery, authoring, publishing and sharing; i.e. the ecosystem of
scholarly social machines?
De Roure, D, Executable Music Documents, Digital Libraries
for Musicology (DLfM '14), 2014, London, UK, ACM.

37. The R Dimensions
Research Objects facilitate research that is
reproducible, repeatable, replicable, reusable,
referenceable, retrievable, reviewable, replayable,
re-interpretable, reprocessable, recomposable,
reconstructable, repurposable, reliable,
respectful, reputable, revealable, recoverable,
restorable, reparable, refreshable?”
@dder 14 April 2014
sci method
access
understand
new use
social
curation
Research
Object
Principles

39. Overview
1. Shifts in scholarship
2. End of the article
3. Future of the article
4. Scholarly Social Machines

40. 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. The ability to create new forms of
social process would be given to the world at large,
and development would be rapid.
Berners-Lee, Weaving the Web, 1999 (pp. 172–175)

41. SOCIAM: The Theory and Practice of Social Machines is funded by the UK Engineering and Physical Sciences Research Council
(EPSRC) under grant number EPJ017728/1 and comprises the Universities of Southampton, Oxford and Edinburgh. See sociam.org

42. “Yet Wikipedia and its stated ambition to “compile the sum of all
human knowledge” are in trouble. The volunteer workforce that
built the project’s flagship, the English-language Wikipedia—and
must defend it against vandalism, hoaxes, and manipulation—
has shrunk by more than a third since 2007 and is still shrinking…
The main source of those problems is not mysterious. The loose
collective running the site today, estimated to be 90 percent
male, operates a crushing bureaucracy with an often abrasive
atmosphere that deters newcomers who might increase
participation in Wikipedia and broaden its coverage…”
http://www.technologyreview.com/featuredstory/520446/the-decline-of-wikipedia/

43. Scholarly
Machines
David De Roure, JCDL 2013 Ecosystem

44. Richard O’Bierne

45. A computationally-enabled
sense-making
network of expertise,
data, software,
models and narratives
Iain Buchan

47. Fusing Audio and Semantic Technologies for
Intelligent Music Production and Consumption
consume
produce
compose
perform
capture
distribute
Sandler, Benford, De Roure
Future of Research Communication
and e-Scholarship
curate preserve

48. Scholarly practice is changing
profoundly as we embrace new
methods of digital research and
engage society.
Our centuries-old research
communication practices
that underpin scholarship
are to be celebrated —
but are they still fit for
their purpose?

49. 1. Shifts in scholarship
– Machines are users too
2. End of the article
– Don’t retrofit digital, think post-digital
3. Future of the article
– Social Objects in a sensemaking network of humans
and machines
– Evolution or the other side of the road?
4. Social Machines
– Humans in the loop, empowered, creative, subversive
– You are designers of scholarly social machines
– Library as social machines knowledge infrastructure

50. Pip Willcox

51. Thanks to Richard O’Bierne, Christine Borgman, Iain Buchan, Neil
Chue Hong, Carole Goble, Chris Lintott, Nigel Shadbolt, Pip Willcox,
Jun Zhao; FORCE11, myExperiment, Software Sustainability
Institute, wf4ever, SOCIAM; Andrew W. Mellon Foundation, JISC,
EPSRC, ESRC, AHRC.
david.deroure@oerc.ox.ac.uk
www.oerc.ox.ac.uk/people/dder
@dder
http://www.slideshare.net/davidderoure/social-machines-of-scholarly-collaboration
www.oerc.ox.ac.uk
www.force11.org
www.researchobject.org
www.software.ac.uk
sociam.org

52. www.oerc.ox.ac.uk
david.deroure@oerc.ox.ac.uk
@dder