Opening talk at the "Interdisciplinary Data Resources to Address the Challenges of Urban Living” Workshop at the Urban Big Data Centre, University of Glasgow, 4 April 2016

1. David De Roure
@dder
Emerging forms of
Data and Analytics
DIRECTOR, UNIVERSITY OF OXFORD E-RESEARCH CENTRE

2. Emerging forms of…
Data

3. ChristineBorgman

4. Engineering
Cyber
Linguis.cs
English
Oxford
Mar.n
School
Saïd
ARC IT Services
ECI Geography SKA
CUDA
Physics
Computer
Science
Maths
History
Oxford
Internet
Ins.tute
Music
Archaeology
Classics
Zoology
Museums
Wolfson
Law
Bodleian
Libraries
Pharmacology
Biochemistry
TORCH DH

5. Energy Efficient
Computing
Infrastructure
(STFC)
De-identified admin
(inc. health) data
Business
data
Open data
(public sector)
Social media
data
Research
data
Longitudinal
survey data
Open data
Securely held data
Environment
data
Business and LG Data
Research Centres
(ESRC)
Admin Data Research
Centres (ESRC)
High Performance
Data Environment
(NERC)
Clinical
data
Medical Bioinformatics (MRC)
Understanding Populations
(ESRC)
Clinical Practice Datalink
(MHRA, NIHR)
100,000 Genome Project NHS)
Research Data Facility (EPSRC)
European Bioinformatics
Institute (EMBL)
Bioscience E-Infrastructure
(BBSRC)
Square Kilometre Array (STFC)
Digital Transformations
(AHRC)
Archive
data
Open Data
Institute
Commercial
Research
Understanding Populations
(ESRC)

6. New Research Questions
▶ Social media data offers
the possibility of studying
social processes as they
unfold at the level of
populations, as an
alternative to traditional
surveys or interviews.
▶ The data from social media
is described as "qualitative
data on a quantitative
scale" and requires
innovative analysis
techniques.
Social media data and
real time analytics

7. https://twitter.com/CR_UK/status/446223117841494016/
Some people's smartphones
had autocorrected the word
"BEAT" to instead read
"BEAR".
"Thank you for choosing an
adorable polar bear," the
reply from the WWF said.
"We will call you today to set
up your adoption."
http://www.bbc.com/news/technology-26723457

8. http://www.parliament.uk/business/committees/committees-a-z/commons-select/science-and-technology-committee/news/report-responsible-use-of-data/

9. theODI.org

10. Social Media Triangle
social media
data and
analytics
social media for
engagement with
research
social media
as a subject
of research
Sam McGregor

11. New Forms of Data
▶ Internet data, derived from social
media and other online interactions
(including data gathered by
connected people and devices, eg
mobile devices, wearable
technology, Internet of Things)
▶ Tracking data, monitoring the
movement of people and objects
(including GPS/geolocation data,
traffic and other transport sensor
data, CCTV images etc)
▶ Satellite and aerial imagery (eg
Google Earth, Landsat, infrared,
radar mapping etc) http://www.oecd.org/sti/sci-tech/new-data-for-
understanding-the-human-condition.htm

12. Emerging forms of…
Risk

13. A rehearsal for the future
▶ The Internet of Things
describes a world in which
everyday objects are
connected to a network so that
data can be shared
▶ But it is really as much about
people as the inanimate object
▶ It is impossible to anticipate
all the social changes that
could be created by connecting
billions of devices
https://www.gov.uk/government/publications/internet-of-things-blackett-review

14. There is no such thing as the Internet of Things
There is no such thing as a closed system
Humans are creative and subversive
The Rise of the Bots A Swarm of Drones
Accidents happen (in the lab, bin)
Holding machines to account Software vulnerability
Where are the throttle points?
@dder

15. PETRAS Privacy, Ethics, Trust, Reliability, Acceptability, and Security
for the Internet of Things
• The fusion of the cyber, physical and human elements
• Scale: from 1mm3 devices to large infrastructure systems
• Managing devices throughout their (decades long) lifetimes
• New and evolving threat landscape
• Continue to operate when partially compromised
The Challenges are numerous
• Safety vs Security
• Security vs Efficiency
• Hardening vs Adaptive Response
Tradeoffs

16. Data Detect Store AnalyticsFilter Analysts

17. Emerging forms of…
Analytics

18. More people
More machines
Data Deluge
HPC
Conven.onal
Computa.on
Emerging
Data and
Analy.cs
Social
Networks
Science 2.0
e-Science
Internet of Things
Social Machines
Web Science
Big Data Machine learning AI

19. 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)
Social Machines

21. Scientists
Talk
Forum
Image
Classification
data reduction
Citizen Scientists

22. “Panoptes has been designed so
that it’s easier for us to update
and maintain, and to allow
more powerful tools for project
builders. It’s also open source
from the start, and if you find
bugs or have suggestions about
the new site you can note them
on Github (or, if you’re so
inclined, contribute to the
codebase yourself).”
"
http://blog.zooniverse.org/2015/06/29/a-whole-new-zooniverse/
http://monsterspedia.wikia.com/wiki/File:Argus-Panoptes.jpg
Panoptes

23. Ecosystem
Perspec.ve
• We see a community of
living, hybrid organisms,
rather than a set of
machines which happen to
have humans amongst
their components
• Their successes and
failures inform the design
and construction of their
offspring and successors

24. time
Social Machine instances
@dder

25. Observer of
one social
machine
Observers using third
party observatory
Observer of
multiple social
machines
Human
participants in
Social
Machine
Human participants in
multiple Social Machines
Observer of Social
Machine infrastructure
1
4
2
3
5
6
SM
SM
SM
Social Machine
Observing Social
Machines
7
@dder
De Roure, D.,
Hooper, C., Page,
K., Tarte, S., and
Willcox, P. 2015.
Observing Social
Machines Part 2:
How to Observe?
ACM Web Science

26. Methods of Observa.on
Tarte, S. Willcox, P., Glaser, H. and De Roure, D. 2015. Archetypal Narratives
in Social Machines: Approaching Sociality through Prosopography. ACM Web
Science 2015.
Tiropanis, T., Hall, W., Shadbolt, N., De Roure, D., Contractor, N. and
Hendler, J. 2013. The Web Science Observatory, IEEE Intelligent Systems
28(2) pp 100–104.
Understanding the design
and emergent behaviours of
co-created sociotechnical
constructions at scale
Macroscope
Observatory
Prosopography

27. Emerging forms of…
Scholarship

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

29. A computationally-enabled
sense-making network of
expertise, data, software,
models and narratives
Big Data, in a
Big Data Centre

30. The R Dimensions
reproducible repeatable replicable reusable
referenceable retrievable reviewable rerunnable
replayable re-interpretable reprocessable
recomposable reconstructable repurposable
reliable respecXul reputable revealable
recoverable restorable reparable refreshable
@dder 14 April 2014
sci method
access
understand
new use
social
cura.on
De Roure, D. 2014. The future
of scholarly communications.
Insights: the UKSG journal,
27, (3), 233-238.
DOI 10.1629/2048-7754.171

31. Principles of Robotics
1. Robots are multi-use tools. Robots should not be designed solely
or primarily to kill or harm humans, except in the interests of
national security.
2. Humans, not robots, are responsible agents. Robots should be
designed; operated as far as is practicable to comply with existing
laws & fundamental rights & freedoms, including privacy.
3. Robots are products. They should be designed using processes
which assure their safety and security.
4. Robots are manufactured artefacts. They should not be designed
in a deceptive way to exploit vulnerable users; instead their
machine nature should be transparent.
5. The person with legal responsibility for a robot should be
attributed.
https://www.epsrc.ac.uk/research/ourportfolio/themes/engineering/activities/principlesofrobotics/

32. Human Digital Physical Triangle
human
digital physical
social
media
IoT
automation
and scale

33. Growing connectivity of human, digital and
physical, together with increasing
empowerment and automation, facilitates
emergent social and technical processes at
speed and at scale.
1. How can they be observed?
2. How can they be predicted?
3. How can they be designed?
4. How can they be contained?

34. David De Roure
david.deroure@oerc.ox.ac.uk
Thanks to Christine Borgman, Susan Halford, Wendy Hall,
Chris Lintott, Emil Lupu, Sam McGregor, Nigel Shadbolt,
Ségolène Tarte, Farida Vis, Alan Winfield, Pip Willcox.
http://www.slideshare.net/davidderoure/emerging-forms-of-data-and-analytics