e-Social Science and the doctorate

Peter HalfpennyESRC National Centre for e-Social Science

New Forms of Doctorate

London Knowledge Lab

10 November 2008

Outline

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

Database

HPC

Audio data

Analysis

Computing

Social Scientist

Computing

HPC

AnalysisData

Archive

Video data

Experiment

Many separate accesses, multiple interfaces

Future research e-Infrastructure

Seamless integration of data, analytic tools and compute resources

Social scientist

Social scientist

Social scientist

Grid

Middle-ware

Simple interface

Single sign on

Data

Data

Storage

Storage

ComputingAnalysis

Analysis

Experiment

HPC

HPC

e-Infrastructure

Future research e-Infrastructure

Seamless integration of data, analytic tools and compute resources

Social scientist

Social scientist

Social scientist

Grid

Middle-ware

Simple interface

Single sign on

Data

Data

Storage

Storage

ComputingAnalysis

Analysis

Experiment

HPC

HPC

e-Infrastructure

Key features of e-social science

1. Benefit from the digital data deluge• data born digital

- every interaction with a computer leaves a trace

- computers are everywhere

• digitisation projects- books, pictures, archives, newspapers, sounds

• discoverable- search engines – Google

- semantic grid – machine-processable descriptions

Key features of e-social science

2. Computer power on tap• High Performance Computers

- available to all UK academics

- accessible via the National Grid Service

• Clusters of ordinary computers- harness wasted power from idle desktop PCs

• No computational task too big- weather prediction, earthquake modelling

- population modelling

Key features of e-social science

3. Collaboration• Asynchronous

- Portals – iGoogle; Facebook

- Virtual Research Environments

NCeSS Portal

ourSpaces

• My tools• My collaborators• Our activities• My tags• New resources• Search• Upload• Explore• Messages

Key features of e-social science

3. Collaboration• Asynchronous

- Portals – iGoogle; Facebook

- Virtual Research Environments

• Synchronous- Voice over Internet – Skype

- High bandwidth teleconferencing

- Access Grid

Typical Views of Access GridETF Management Meeting

Lecture

SeminarSC Global Workshop Performance ArtSeminar

Key features of e-social science

3. Collaboration• Asynchronous

- Portals – iGoogle; Facebook

- Virtual Research Environments

• Synchronous- Voice over Internet – Skype

- High bandwidth teleconferencing

- Access Grid

• Support collaboratories- distributed, virtual research centres

From the Grid to Web 2.0

Early e-Science emphasised HPC• delivered over the Grid

- like electricity, gas, etc

- the ‘plumbing’

• heavyweight middleware- needed programmers

- out of reach of most social scientists

The first Grid book

• Ian Foster• Carl Kesselman• 1998• 700 pages• £46

The second edition

• Ian Foster• Carl Kesselman• 2004• 750 pages• and a website• £42

From the Grid to Web 2.0

Originated in 2004• name of a commercial conference

Users become producers• Blogs, Wikis, social networking

• sharing photos, videos

• 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

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

• technology alone does not provide solutions

• technology embedded in social practices

e-social science & research cycle

literature search• boundless

• machine translation

• personal and shared bibliographic databases

literature review• text mining

e-social science & research cycle

data discovery• boundless

• fully documented – provenance and use

• multi-modal

data access• authorisation via ‘role’

data integration• matching, imputation, statistical methods

e-social science & research cycle

data security• virtual safe settings

analysis• boundless

• data mining

• pattern matching for visual data

• mixed methods / multi-modal

Digital Replay System

system log

video

transcript

code tree

Collaborative video analysis

e-social science & research cycle

presentation of results• multi-modal

• dynamic

• non-linear hyperlinking

• visualisation

• mapping

Grid-Enabled Micro-Econometric Data Analysis

London Profiler

Higher Education

Higher Education

Higher Education

e-social science & research cycle

simulation• micro-simulation

• agent-based modelling

real-time data collection and analysis• sensor networks

• GPRS / GPS

practical knowledge / skill• ‘how to’ videos

implications for the doctorate

location• student and supervisor(s) not co-located

topic choice• multidisciplinarity

fieldwork• digital technology enabled

data• re-use

implications for the doctorate

loneliness• networking

supervision• channels of communication

thesis• digital, multi-modal, hyperlinked

examination• originality

implications for the doctorate

collaboration• 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• 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• 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?