Big Data for the Social Sciences
David De Roure, Strategic Adviser for Data Resources
@dder

Big Data doesn‟t
respect disciplinary
boundaries
Digital Social Research

theODI.org

Mandy Chessell

The Big Picture
More people
Moremachines
Big Data
Big Compute
Conventional
Computation
“Big Social”
Social Networks
e-infrastructure
online
R&D
Big Data
Production
& Analytics
deeply
about
society

RCUK and Big Data
▶ „Big data is a term for a collection of datasets so
large and complex that it is beyond the ability of
typical database software tools to capture, store,
manage, and analyse them. „Big‟ is not defined as
being larger than a certain number of „bytes‟ because
as technology advances over time, the size of datasets
that qualify as big data will also increase‟ (RCUK)
▶ But why do we want it?
New forms of data enable us to
1. Answer existing research questions in new ways
2. Ask entirely new research questions

NERC Big Data
...as diverse as our science
• From micro- to macro-scale
• Many sources:
• Monitoring campaigns
• Field sites & sensors
• State-of-the-art laboratories
• Ships & aircraft
• Remote Sensing & EO
• Regulator networks
• Volunteers/citizen science
• Model output
• Long-term and unique!
10µm

100 TB
Big data: time-based media including film, tv, cctv
footage - retail data - geospatial data - email and social
media - images and associated metadata -
performance data including raw data of recordings,
choreography, performance structure - open
government data - music - large-scale digital scans -

Research benefits of new data
▶ Undertaking research on pressing policy-related issues
without the need for new data collection
• Food consumption, social background and obesity
• Energy consumption, housing type and climatic
conditions
• Rural location, private/public transport alternatives and
incomes
• School attainment, higher education participation,
subject choices, student debt and later incomes
▶ New data such as social media enable us to ask big
questions, about big populations, and in real time – this is
transformative

Big Data Network

Phase 1 and 2

E-infrastructureLeadership

Mandy Chessell

F i r s t

Interdisciplinary and “in the wild” *
* “in it” versus “on it”

Nigel Shadbolt et al

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)
The Order of Social
Machines

Some Social
Machines
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

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

Web as
lens
Web as
artefact
Web
Observatories
http://www.w3.org/community/webobservatory/

Big data elephant versus sense-making
network?
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.
Iain Buchan

Join the W3C Community Group www.w3.org/community/rosc
Jun
Zhao
www.researchobject.org

Pip

Take homes
▶ New forms of data enable us answer old
questions in new ways and to answer entirely
new questions
▶ There are multiple shifts occurring:
– Volumes of data
– Realtime analytics
– Computational infrastructure
– Dataflows vs datasets (and curation infrastructure)
– Correlation vs causation
– Increasing automation
– Machine-to-Machine in Internet of Things

david.deroure@oerc.ox.ac.uk
www.oerc.ox.ac.uk/people/dder
@dder
Slide and image credits: Fiona Armstrong, Christine
Borgman, Iain Buchan, Mandy Chessell, Neil Chue Hong,
Nigel Shadbolt, Pip Willcox, Jun Zhao, Guardian newspaper

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