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  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 Analysis Data Archive Video data Experiment Many separate accesses, multiple interfaces

Future research e-Infrastructure Seamless integration of data, analytic tools and compute resources Social scientist Grid Middle- ware Simple interface Single sign on Data Storage Computing Analysis Experiment HPC e-Infrastructure

Future research e-Infrastructure Seamless integration of data, analytic tools and compute resources Social scientist Grid Middle- ware Simple interface Single sign on Data Storage Computing Analysis Experiment 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 Grid ETF Management MeetingLecture Seminar SC Global WorkshopPerformance 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 pages £46

The second edition Ian Foster Carl Kesselman 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

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

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:

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