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What is … e-Social Science?

Peter Halfpenny ESRC National Centre for e-Social Science NCRM Research Methods Festival Oxford, 30 June – 3 July 2008. What is … e-Social Science?. Outline. 10 examples of ‘wouldn’t it be good if …?’ What is e-science? What is e-social science? What is NCeSS? What can NCeSS do for you?.

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What is … e-Social Science?

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  1. Peter Halfpenny ESRC National Centre for e-Social Science NCRM Research Methods Festival Oxford, 30 June – 3 July 2008 What is …e-Social Science?

  2. Outline 10 examples of ‘wouldn’t it be good if …?’ What is e-science? What is e-social science? What is NCeSS? What can NCeSS do for you?

  3. Wouldn’t it be good if … 1. we could easily find all research data relevant to a particular topic? • whatever terminology is used • allowing for variations in terminology across different datasets • using a single website to discover all data

  4. Data Chronicles • search on a term  list of data sources • each data source  documentation  publications  relations to other terms • each term  relations to terms in other data sources  debates about terms • part implemented for drugs, alcohol and tobacco

  5. Data Chronicles

  6. Data Chronicles

  7. Wouldn’t it be good if … 2. we could easily apply occupational classifications to our data? using any available alternative scale without manual coding or re-coding with guaranteed data security using a single website for all countries, time periods, classifications and file formats regularly updated

  8. GEODE • Grid Enabled Occupational Data Environment • data  index  output classification / scale • 100+ alternative index schemes • 500+ alternative output measures • varying translation rules • searchable, standardised information about indices and output measures

  9. GEODE

  10. GEODE

  11. Wouldn’t it be good if … 3. we could combine datasets that usedifferent geographical units? e.g. post coded data, census geography instantly – despite complexity extract data in different formats from several databases using different interfaces convert each dataset to common target geography combine converted datasets into one for analysis

  12. Different source geographies

  13. ConvertGrid • Spatial variations in HE participation rates • Data • 1991 Census – persons aged 16-19 • 1991 Census Ward • Neighbourhood Statistics – no. entering HE • 1998 Electoral Ward • Experian - average house price • 1999 Postcode Sectors

  14. ConvertGrid

  15. Wouldn’t it be good if … 4. we could bring all our multi-modal data together? transcribed talk audio video digital records system logs location …

  16. Digital Replay System code tree video transcript system log

  17. Digital Replay System

  18. Digital Replay System

  19. Wouldn’t it be good if … 5. we could analyse talk in its context? non-verbal behaviour back-channels, e.g. head nods combine lexical, prosodic and gestural features Nottingham Multi-Modal Corpus 250,000 words of one- and two-party talk text, audio, video integrate recording, data management, coding and analysis

  20. Headtalk read view annotate sort analyse

  21. automatic trackingof marked feature Headtalk

  22. Wouldn’t it be good if … 6. we could capture the analysis of video data? as analysts point at movements and talk about their observations annotating the video collaboratively but in distributed locales

  23. MiMeG • Mixed Media Grid • Collaborative video analysis

  24. Wouldn’t it be good if … 7. we could collaborate at a distance? • without endless travel • with richer interaction than phone and email

  25. Access Grid • Advanced tool for video-conferencing • Used for lectures at a distance, seminars, research meetings and interviews • Example of collaborative tools – Virtual Research Environments (VREs) • Supporting ‘collaboratories’ – distributed, virtual research centres

  26. Access Grid

  27. Wouldn’t it be good if … 8. we could visualise our results? plots maps instant changes GEMEDA Grid-Enabled Micro-Econometric Data Analysis

  28. GEMEDA area toggle gender buttons ethnic group buttons

  29. GEMEDA

  30. Wouldn’t it be good if … 9. we could map all our data? at different levels of detail and zoom in and out

  31. London Profiler

  32. Wouldn’t it be good if … 10. we could predict the future? where to site clinics? how many new houses will be needed? what will be the demand for elderly care?

  33. MoSeS • Modelling and Simulation for e-Social Science • model • a complete representation of UK population • at a fine spatial scale • simulation • to produce forecasts • relating demographics to service provision • health, transport, housing

  34. MoSeS

  35. MoSeS

  36. Finally, wouldn’t it be good if … all resources I’ve described were integrated? • in a single collaborative working environment • social networking / researcher network • resources management – data, models, reports – upload, annotate, search • project workspaces • analysis tools • visualisation tools

  37. My tools My collaborators Our activities My tags New resources Search Upload Explore Messages ourSpaces

  38. Virtual Research Environment • NCeSS portal • schedule • document archive • wiki • blog • discussion forum • access grid

  39. NCeSS Portal

  40. What is e-science? “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) That enabling infrastructure is the Grid Now commonly know as e-Infrastructure

  41. 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.

  42. Database DataArchive HPC HPC Social Scientist Audio data Video data Experiment Computing Computing Analysis Analysis Research infrastructure today Many separate accesses, multiple interfaces

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

  44. What is NCeSS? major ESRC investment co-ordinating Hub at Manchester 7 major research Nodes across the UK100+ investigators developing the e-Infrastructure advanced digital tools and services for (collaborative) social research

  45. Where to find out more NCeSS display here at the Festival - in the JCR private dining room From our website: www.ncess.ac.uk

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