Transcript Wouldn`t it be good if … ICTs enabled advances in social research

e-Social Science and the doctorate
Peter Halfpenny
ESRC National Centre for e-Social Science
New Forms of Doctorate
London Knowledge Lab
10 November 2008
Outline
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What is e-social science?
Three key features of e-social science
From the Grid to Web 2.0
e-social science and the research cycle
Implications for the doctorate
What is NCeSS?
What can NCeSS do for you?
What is e-social science?
 Harnessing innovations in digital technologies
 Integrating them into an e-infrastructure
• networked – across the Internet
• interoperable – seamless, single sign-on
• scalable – to any magnitude
 Automating the tedious, time-consuming,
error-prone bits – into workflows
 enabling social science
• new methods of research
• overcoming past limitations
Research infrastructure today
Lots of computer-based support
Data
Archive
Analysis
Computing
Experiment
HPC
Social Scientist
Audio data
Computing
Analysis
Video data
Database
HPC
Many separate accesses, multiple interfaces
Future research e-Infrastructure
Seamless integration of data, analytic tools and compute resources
Social scientist
HPC
Data
Grid
Middleware
Storage
Analysis
Social scientist
Simple
interface
Social scientist
Single
sign on
Data
HPC
Computing
Analysis
Storage
e-Infrastructure
Experiment
Future research e-Infrastructure
Seamless integration of data, analytic tools and compute resources
Social scientist
HPC
Data
Grid
Middleware
Storage
Analysis
Social scientist
Simple
interface
Social scientist
Single
sign on
Data
HPC
Computing
Analysis
Storage
e-Infrastructure
Experiment
Key features of e-social science
1. Benefit from the digital data deluge
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data born digital
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digitisation projects
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every interaction with a computer leaves a trace
computers are everywhere
books, pictures, archives, newspapers, sounds
discoverable
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search engines – Google
semantic grid – machine-processable descriptions
Key features of e-social science
2. Computer power on tap
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High Performance Computers
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Clusters of ordinary computers
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available to all UK academics
accessible via the National Grid Service
harness wasted power from idle desktop PCs
No computational task too big
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weather prediction, earthquake modelling
population modelling
Key features of e-social science
3. Collaboration
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Asynchronous
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Portals – iGoogle; Facebook
Virtual Research Environments
NCeSS Portal
ourSpaces
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My tools
My collaborators
Our activities
My tags
New resources
Search
Upload
Explore
Messages
Key features of e-social science
3. Collaboration
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Asynchronous
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Portals – iGoogle; Facebook
Virtual Research Environments
Synchronous
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Voice over Internet – Skype
High bandwidth teleconferencing
Access Grid
ETF Management Meeting
Lecture
Typical Views of Access Grid
Seminar
Seminar
SC
Global Workshop
Performance Art
Key features of e-social science
3. Collaboration
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Asynchronous
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Synchronous
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Portals – iGoogle; Facebook
Virtual Research Environments
Voice over Internet – Skype
High bandwidth teleconferencing
Access Grid
Support collaboratories
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distributed, virtual research centres
From the Grid to Web 2.0
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Early e-Science emphasised HPC
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delivered over the Grid
- like electricity, gas, etc
- the ‘plumbing’
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heavyweight middleware
- needed programmers
- out of reach of most social scientists
The first Grid book
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Ian Foster
Carl Kesselman
1998
700 pages
£46
The second edition
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Ian Foster
Carl Kesselman
2004
750 pages
and a website
£42
From the Grid to Web 2.0
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Originated in 2004
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name of a commercial conference
Users become producers
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Blogs, Wikis, social networking
sharing photos, videos
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tagging
mashups
Exponential growth of Web 2.0
From the Grid to Web 2.0
From the Grid to Web 2.0
e-social science & research cycle
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Seminar series focuses on the thesis
Consider this in the context of the full
research life-cycle
From initial idea to final output
Socio-technology approach
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technology alone does not provide solutions
technology embedded in social practices
e-social science & research cycle
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literature search
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boundless
machine translation
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personal and shared bibliographic databases
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literature review
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text mining
e-social science & research cycle
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data discovery
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boundless
fully documented – provenance and use
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multi-modal
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data access
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authorisation via ‘role’
data integration
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matching, imputation, statistical methods
e-social science & research cycle
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data security
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virtual safe settings
analysis
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boundless
data mining
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pattern matching for visual data
mixed methods / multi-modal
Digital Replay System
code
tree
video
transcript
system
log
Collaborative video analysis
e-social science & research cycle
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presentation of results
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multi-modal
dynamic
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non-linear hyperlinking
visualisation
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mapping
Grid-Enabled Micro-Econometric
Data Analysis
London Profiler
Higher Education
Higher Education
Higher Education
e-social science & research cycle
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simulation
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micro-simulation
agent-based modelling
real-time data collection and analysis
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sensor networks
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GPRS / GPS
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practical knowledge / skill
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‘how to’ videos
implications for the doctorate
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location
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student and supervisor(s) not co-located
topic choice
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multidisciplinarity
fieldwork
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digital technology enabled
data
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re-use
implications for the doctorate
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loneliness
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networking
supervision
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channels of communication
thesis
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digital, multi-modal, hyperlinked
examination
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originality
implications for the doctorate
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collaboration
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is there a role for the lone scholar?
technology developer as partner?
the original e-science vision:
“e-Science is about global collaboration in key areas
of science and the next generation of
infrastructure that will enable it.”
John Taylor, former DG of Research Councils,
UK Office of Science and Technology (as was)
A word from the top
“We are now living in an increasingly complex,
dynamic and diverse society. This means that
there is a pressing need to create better
resources to answer some of the more complex
research and policy questions this poses.
Developments in technology, particularly e-social
science, are creating path-breaking new
opportunities to link, model and mine large
datasets.”
Ian Diamond, Chief Executive, ESRC
Preface to the
National Strategy for Data Resources
for Research in the Social Sciences
What is e-social science?
 using the e-Infrastructure to:
• locate, access, share, integrate, analyse and
visualise digitised data seamlessly across the
Internet on a hitherto unrealisable scale
• facilitate collaboration across distributed
teams
• enable advances in social research that would
not otherwise have been possible.
What is NCeSS?
 major ESRC investment
 co-ordinating Hub at Manchester
 8 major research Nodes across the UK
100+ investigators
 developing the e-Infrastructure
 advanced digital tools and services for
(collaborative) social research
What can NCeSS do for you?
 ICTs and social research
• three variants
ICTs and social research
1. social research on technologies
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studies of innovation
uses
markets
digital divides
NCeSS ‘social shaping’ research
• barriers to uptake, facilitators
ICTs and social research
2. social research using existing ICTs
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computer assisted interviewing
statistical analysis
qualitative data ‘analysis’
web-based surveys
NCeSS develop refinements
• e.g. data-mining, text-mining
ICTs and social research
3. social research enabled by e-infrastructure
• data discovery
• data manipulation
• data integration
• data analysis
• collaboration
• modelling
• simulation
• visualisation
NCeSS
‘applications’
research
Where to find out more
From our website: www.ncess.ac.uk
Thank you
Questions?
Pardon?